Google Releases Gemini 3.7 Flash AI Model Just 3 Weeks After Last Update as Flagship Pro Stalls

Google announces Gemini 3.7 Flash just three weeks after previous release

Google is announcing a new Gemini model today, but it's not the long-awaited 3.5 Pro. Gemini 3.7 Flash is now rolling out to replace 3.6 Flash, which itself was released only three weeks ago. This new "workhorse" model is allegedly the product of core optimizations and developer feedback, offering improved coding and agentic performance. And Google is hoping to counter the lower cost of some competing models with a lower "introductory price" for 3.7 Flash. According to Senior Director Tulsee Doshi, Gemini 3.7 Flash is noticeably better at coding than the previous Flash release. She cites a jump in the FrontierCode 1.1 Main test from 34.4 to 43.6 percent and DeepSWE v1.1 going from 49 to 65.3 percent. As for the vibes, Gemini 3.7 Flash's WebDev Arena score has risen to 1588 from 1538. People turning to Gemini and hoping it will "know" things may also see modest improvements in Gemini 3.7 Flash. The GDP.pdf benchmark, which measures how well a model can process complex documents, has gone up to 34 percent versus 22 percent with 3.6 Flash. AutomationBench tests how well models can execute common business workflows, and Gemini 3.7 Flash rose to 30.4 percent from 3.6's 17 percent score. Those numbers certainly are higher. But are they sufficiently different to support a new model release just three weeks after the last one? This may be more about maintaining the appearance of constant improvements in Google's AI. Throughout 2024 and 2025, Google rapidly made up ground to rival the best AI coming out of competing AI labs. Things appear to have slowed in 2026, though. At I/O back in May, Google promised that the flagship Gemini 3.5 Pro would launch in June, but that never happened. Developers and businesses that have invested in Google's AI tools will have to make do with a slightly better Flash model for now. Google is hoping a lower price will keep developers engaged with Gemini. Gemini 3.7 Flash will be available through the end of the year at a rate of $0.75/1M input tokens and $3.75/1M output tokens, which is half of what 3.6 Flash costs. OpenAI recently dropped the price of its GPT 5.6 models, with the Flash-like Luna version at $0.20/1M input tokens and $1.20/1M output tokens. Given the breakneck speed with which Google has been releasing new Gemini models, it absolutely could have gotten 3.5 Pro out the door at any point this summer. The fact that we have now seen multiple Flash models edging closer to 4.0 suggests Google doesn't want 3.5 Pro to be compared to the latest releases from OpenAI and Anthropic. Reports suggest that Gemini's coding capabilities haven't kept up with recent advances from other AI labs, which comes as Google is also seeing an exodus of AI talent. Interested parties can begin using Gemini 3.7 Flash today -- well, maybe. It's live in the Gemini API, AI Studio, and Gemini Enterprise. For individuals, the availability is weirdly narrow. Gemini 3.7 Flash is now powering the Gemini Spark agent in the Gemini app, but only if you have an AI Pro or Ultra subscription. It's not an option in the regular chatbot interface, which continues to run on 3.6 Flash for now.

Google cuts Gemini 3.7 Flash prices as enterprise AI economics diverge and Pro cadence slows

The new model targets coding and agent workflows with improved efficiency and lower costs, even as rivals raise prices Google has launched Gemini 3.7 Flash, with updates focused on coding, automation, and agent workflows, alongside lower pricing for production deployments. The release, just three weeks after Gemini 3.6 Flash, reflects what the company described as rapid iteration driven by developer feedback. Google positioned the model as its "most intelligent workhorse model yet for coding and agents," aimed at software engineering and multi-step workflows. Gemini 3.7 Flash is priced at $0.75 per million input tokens and $3.75 per million output tokens -- roughly half the cost of its predecessor -- signaling a push to make production deployments more economically viable.

Google unveils Gemini 3.7 Flash AI model for coding, agent workflows

Aug 13 (Reuters) - Alphabet's (GOOGL.O), opens new tab Google launched Gemini 3.7 Flash on Thursday, its latest AI model designed for software coding and automated business tasks, but offered no details on when its flagship Pro model will be released. Investors have been closely watching for Gemini 3.5 Pro, Google's premium model, as a test of whether its DeepMind AI unit can keep pace with rivals Anthropic and OpenAI. Google had said in July Gemini 3.5 Pro was being tested with partners and would be coming "soon". Here are a few details on Gemini 3.7 Flash: Reporting by Juby Babu in Mexico City; Editing by Shilpi Majumdar Our Standards: The Thomson Reuters Trust Principles., opens new tab

Google's cheap model is now two versions ahead of its flagship

Gemini 3.7 Flash arrives three weeks after the last Flash release, while the Pro model it was meant to sit beneath is months late and may never ship Google has released Gemini 3.7 Flash with sharp gains on coding benchmarks and introductory pricing of $0.75 per million input tokens. Gemini 3.5 Pro remains months behind schedule, and Google will not say whether it is still coming. Google has released Gemini 3.7 Flash, and still will not say when its flagship model is coming. The workhorse model posts large gains on coding, which is the ground Google has been losing. Gemini 3.5 Pro, the model this one is meant to sit beneath, remains months behind schedule. The numbers are real. On FrontierCode 1.1 the new model scores 43.6% against 34.4% for its predecessor, on DeepSWE v1.1 it reaches 65.3% against 49.0%, and on AutomationBench it more than doubles, from 17.0% to 30.4%. Google is pricing it to be used. Input costs $0.75 per million tokens and output $3.75 until the end of December, after which both double. It also powers Gemini Spark for AI Pro and Ultra subscribers across more than 160 countries. The safety work is pitched at the frontier categories. Google says it added safeguards against cyber offence and chemical, biological, radiological and nuclear misuse, in line with its Frontier Safety commitments. What stands out is the cadence. This lands three weeks after the last Flash release, and Google put out three Flash models in July alone, including a security-tuned variant. The Pro line has not moved in that time. Google's next Pro model is months behind schedule after its coding performance fell short of internal targets, which is awkward given coding is where the money is. It may not arrive at all. Axios reports Google could skip 3.5 Pro entirely and go straight to Gemini 4 Pro, and the company declined to discuss the model's fate. Sundar Pichai told investors in July that Google intends to ship models faster and is already spending heavily on compute to train Gemini 4. Shipping the cheap tier every three weeks is one way to look faster while the expensive one stalls. There is a cost inside the building. The delay has been hard on DeepMind morale, at a moment when rival labs are hiring.

Gemini 3.7 Flash is here with better coding, reasoning, and more

The new model performs better at PDF document comprehension, code accuracy, web development, and more. Google first introduced us to Gemini 3.6 Flash in late July. At the time, the model was Google's smartest workhorse model to date. It sure didn't take long for that model to become old news. The company is already launching its successor, Gemini 3.7 Flash. In a blog post, the Mountain View-based firm states that this new model takes developer feedback into consideration, along with algorithmic improvements. The result is improved performance across software engineering, knowledge work, and web development workflows. To sweeten the deal, Google is offering the model at the same introductory price that came with 3.6 Flash. According to the tech giant, Gemini 3.7 Flash is better at coding tasks, such as debugging and issue resolution. It's also said to have higher first-pass code accuracy and improved performance in generating production-ready code. The company goes on to mention that the model generates more functional layouts, provides feature-complete apps in fewer prompts, and delivers improved reasoning and accuracy for finance, law, and biosciences. It appears that Google really focused on the developer experience with this one. For instance, it's said that the new model "better adapts to roadblocks, clarifies intent when needed, and follows instructions with greater fidelity." Along with that, Google claims the model also puts more effort into multi-step planning and tool calls. As for the price, it will cost $0.75/1M input tokens and $3.75/1M output tokens. However, Google only guarantees these prices through the end of the year. The company doesn't mention what the prices will be after this introductory price expires. Gemini 3.7 Flash is available for AI Pro and Ultra subscribers through Gemini Spark. Google says that Spark will start using the model starting today. It will also be available to developers and enterprise customers through Google Antigravity, Google AI Studio, Android Studio, Gemini Enterprise Agent Platform, and the Gemini Enterprise app.

Gemini 3.7 Flash launches three weeks after last model, live in Spark

Just three weeks after the last release, Google today announced Gemini 3.7 Flash, which continues the company's accelerated cadence. This new model is a "direct result of developer feedback and algorithmic innovations that [Google looks] forward to bringing to future models." The company touts "substantial improvements" across software engineering, web development, and knowledge work. The coding improvements include "strong gains" over 3.6 Flash for debugging and issue resolution. Specifically, the DeepSWE v1.1 benchmark goes from 49.0% to 65.3%, while it's 34.4% to 43.6% on FrontierCode 1.1 Main. For web development, Gemini 3.7 Flash "generates more functional layouts and feature-complete apps in fewer prompts." Last month's model had an Elo score of 1538 on Arena.ai's WebDev Arena, and this release comes in at 1588. For UI generation, the model shows high design adherence and parity based on a reference input, whether it's a screenshot, an image, or a full design system. In finance, law, biosciences, and other "knowledge-dense fields," there are improvements in reasoning and accuracy: * "It significantly outperforms 3.6 Flash on the GDP.pdf benchmark (34.0% vs 22.0%), an eval for testing a model's ability to process complex documents." * "It also surpasses 3.6 Flash in AutomationBench, demonstrating it can more effectively complete real-world business workflows (30.4% vs 17.0%)." Developers should notice that Gemini 3.7 Flash "better adapts to roadblocks, clarifies intent when needed, and follows instructions with greater fidelity." It thinks more diligently, putting in more effort into multi-step planning and tool calls. A more disciplined execution means less manual oversight and fewer retries across engineering workflows. On the safety front, the model has "updated safeguards against misuse in the domains of Chemical, Biological, Radiological, and Nuclear (CBRN) and cyber offense, while enabling beneficial use cases, in accordance with our approach to bioresilience and our cyber program." Until the end of 2026, Gemini 3.7 Flash is available at an introductory price of $0.75/1M input tokens and $3.75/1M output tokens, which is half the price of the previous model at launch. In the Gemini app, 3.7 Flash today is just rolling out to Spark (AI Pro and Ultra subscription required). The model improvements will make the personal agent "more efficient for knowledge work with improved tool use for Google Workspace apps." It's also available in Google Antigravity, AI Studio, Android Studio, Gemini Enterprise Agent Platform, and the Gemini Enterprise app.

New Gemini Flash model arrives before Gemini 3.5 Pro

Yes, but: The company has yet to deliver Gemini 3.5 Pro, a promised update to its larger version of Gemini as the search giant continues to trail Anthropic and OpenAI at the frontier. Driving the news: Google said Gemini 3.7 Flash offers better performance in coding and knowledge work and is also more responsive to developers. * "It better adapts to roadblocks, clarifies intent when needed, and follows instructions with greater fidelity," Google said in a blog post. "It thinks more diligently, putting in more effort into multi-step planning and tool calls." * The company said its introductory pricing for the model will be 75 cents per million input tokens and $3.75 per million output tokens -- half of the initial price for Gemini 3.6 Flash. * The new model is also being added to Gemini Spark, the AI agent available to the Google AI Pro and Ultra subscribers. Zoom in: The new model will also ship with updated guardrails to prevent misuse, Google says. The big picture: Google's release comes amid a flurry of new models from U.S. competitors, including SpaceXAI's Grok, and Chinese providers, such as DeepSeek.

Google's Gemini 3.7 Flash targets coding and agents with a 50% introductory price cut

Google is rolling out Gemini 3.7 Flash, a new version of its workhorse AI model that puts coding, agentic workflows and knowledge work at the center of the upgrade -- while temporarily cutting API prices in half. The release arrives just three weeks after the release of Gemini 3.6 Flash, an unusually short turnaround that Google attributes to developer feedback and algorithmic improvements. For enterprise developers, the more consequential story may be the combination of those intelligence gains with lower inference costs: through the end of 2026, Gemini 3.7 Flash costs $0.75 per million input tokens and $3.75 per million output tokens. Starting Jan. 1, 2027, pricing rises to $1.50 per million input tokens and $7.50 per million output tokens. That means the current discount is temporary, but it gives teams deploying high-volume coding and business agents several months to evaluate whether Google's claimed reductions in retries and manual oversight translate into lower total operating costs. The launch also underscores Google's rapid iteration on its Flash line while its next flagship Pro model remains absent. Google did not provide a release date for Gemini 3.5 Pro with Thursday's announcement, Reuters reported, despite the model having previously been described as undergoing partner testing. Axios similarly noted that 3.7 Flash arrives before the anticipated Pro release. A three-week upgrade focused on getting work done Google describes Gemini 3.7 Flash as its "most intelligent workhorse model yet for coding and agents." The company says the model is better at adapting when it encounters roadblocks, clarifying intent when necessary and following instructions with greater fidelity. Those improvements matter beyond benchmark scores. In an enterprise coding agent, a model that makes fewer unnecessary changes, recovers from errors and executes multi-step plans more reliably can reduce the number of human interventions needed to complete a task. The same principle applies to business agents operating across documents and applications, where an incorrect tool call or poorly interpreted instruction can derail an otherwise useful workflow. Google says 3.7 Flash "thinks more diligently," applying more effort to multi-step planning and tool calls. Its stated goal is more disciplined execution with fewer retries and less manual supervision. That represents an interesting evolution from Gemini 3.6 Flash. Google's developer documentation described 3.6 as reducing reasoning steps, conversational turns and tool calls compared with earlier models while attempting to limit execution-loop spiraling. With 3.7, the emphasis shifts toward putting sufficient effort into planning while improving the quality of execution -- potentially a more useful optimization than simply minimizing the number of steps an agent takes. Google DeepMind said in a post accompanying the release that 3.7 Flash shows gains in debugging and issue resolution, generates more functional web layouts and applications with fewer prompts, and improves reasoning and accuracy on real-world business workflows. Coding gains are substantial, but not universal Google's benchmarks show a large generational improvement in several software engineering tests. On FrontierCode 1.1 Main, which measures production code quality, Gemini 3.7 Flash scores 43.6%, up from 34.4% for Gemini 3.6 Flash. That also narrowly exceeds the 42.7% Google reports for Claude Sonnet 5 and 41.3% for GPT-5.6 Terra. On DeepSWE v1.1, a long-horizon software engineering evaluation, 3.7 Flash reaches 65.3%, compared with 49.0% for its predecessor. GPT-5.6 Terra remains ahead at 69.6% in Google's table. Web development shows another notable gain. Gemini 3.7 Flash receives an Elo score of 1588 on Code Arena, versus 1538 for 3.6 Flash, 1541 for Claude Sonnet 5 and 1523 for GPT-5.6 Terra. Google says the new model can produce more functional layouts and feature-complete applications in fewer prompts while more closely following reference screenshots, images and design systems. The broader benchmark table is more mixed, which is important for enterprises evaluating the model against particular workloads rather than looking for a single "best" model. Gemini 3.7 Flash scores 85.8% on Terminal-bench 2.1, compared with 87.4% for GPT-5.6 Terra. Terra also leads Google's comparisons on Terminal-bench 3.0 and OSWorld-2.0. Claude Sonnet 5 leads the Agent's Last Exam multimodal desktop and operating-system tasks with a 33.3% pass rate, versus 26.3% for Gemini 3.7 Flash. In other words, Google's own results do not show 3.7 Flash universally displacing higher-priced competitors. They instead suggest a model that has become substantially more competitive in coding and agent workloads while occupying a lower price tier. Enterprise workflows may be the more important test The gains extend beyond software development. On AutomationBench, which Google describes as measuring enterprise workflow automation, Gemini 3.7 Flash scores 30.4%, up sharply from 17.0% for 3.6 Flash. Google's table lists Claude Sonnet 5 at 10.7% and GPT-5.6 Terra at 23.6%. The model also reaches 34.0% on GDP.PDF, an evaluation of complex PDF comprehension, compared with 22.0% for 3.6 Flash, 28.0% for Claude Sonnet 5 and 24.7% for GPT-5.6 Terra. That combination is relevant for enterprise agents because many practical deployments require more than generating text or code. An agent may need to interpret a long report, identify relevant information, decide which tool to invoke, update another system and produce a document for a human reviewer. Reliability across that chain can matter more than performance on an isolated reasoning benchmark. Google is putting that thesis into practice with Gemini Spark. Google AI Pro and Ultra subscribers can use 3.7 Flash in Spark, the company's personal AI agent. Google says the upgrade improves Spark's knowledge work and tool use across Google Workspace applications, including workflows that consolidate files, draft emails and update status documents. For enterprises, 3.7 Flash is also available through the Gemini Enterprise Agent Platform and Gemini Enterprise app. Price becomes part of the model competition Gemini 3.7 Flash's introductory pricing is a notable bid to embed the model into enterprise workflows. Until Dec. 31, developers pay $0.75 per million input tokens and $3.75 per million output tokens. Context caching costs $0.075 per million tokens during the introductory period. Google says standard prices will double on Jan. 1, 2027, to $1.50 for input and $7.50 for output, with context caching rising to $0.15. For comparison, Gemini 3.6 Flash's standard API pricing is $1.50 per million input tokens and $7.50 per million output tokens. Google's benchmark table lists Claude Sonnet 5 at $2 and $10, respectively, while GPT-5.6 Terra is listed at $2 and $12. The economics become more pronounced for autonomous agents because a single user request can produce a long sequence of model calls, reasoning tokens and tool interactions. A model that costs less per token but requires substantially more retries may not ultimately be cheaper. Conversely, Google's combination of lower introductory token pricing and claimed improvements in first-pass accuracy could materially change the cost of running high-volume coding or document-processing agents if those gains carry over to production. That is the metric enterprise teams will ultimately need to test: not price per million tokens in isolation, but cost per successfully completed task. Google's AI shake-up raises the stakes for Gemini Gemini 3.7 Flash arrives amid a broader debate over whether Google is losing ground at the AI frontier. The company has not released Gemini 3.5 Pro, despite saying in May that the flagship model would arrive the following month. By July, Google said it remained in partner testing and would become broadly available when ready; Thursday's announcement offered no further timetable. Google's latest released general-purpose Pro model therefore remains Gemini 3.1 Pro, introduced in February. Reuters reported in July that Gemini 3.5 Pro missed its original target after falling short of internal goals, particularly in coding, even as Google began training what it calls its most ambitious model yet, Gemini 4. The delay coincides with a major overhaul of Google's AI leadership announced last week. Google DeepMind co-founder and Nobel Prize Winner Demis Hassabis has relinquished day-to-day control of the company's famed DeepMind AI division to become its chair and, simultaneously, to take on the role of Alphabet's chief scientist. Meanwhile, former DeepMind CTO Koray Kavukcuoglu now runs the unit as a senior vice president reporting directly to CEO Sundar Pichai. Kavukcuoglu controls Gemini model development, frontier research, the Gemini app and developer teams -- effectively consolidating the full Gemini chain under a more product-focused operator. Chief scientist Jeff Dean, Gemini co-lead Oriol Vinyals, Quoc Le and Sanjay Ghemawat left to establish the research startup Discovery Loop. Those exits followed Gemini co-lead Noam Shazeer's move to OpenAI and Nobel Prize-winning AlphaFold scientist John Jumper's departure for Anthropic. Reuters reported that internal disagreements, constrained compute allocation and Google's bureaucracy contributed to slower releases and weaknesses in coding. Outside interpretations range from organizational repair to a more fundamental retreat. SemiAnalysis has argued that Google is increasingly prioritizing the highly profitable business of supplying cloud infrastructure to AI companies -- including Gemini competitors -- over keeping its own models at the absolute frontier. That analysis also claimed Google had effectively canceled 3.5 Pro, although Google has not confirmed that and continues to describe the model as delayed. The Verge offered a more measured assessment: the departures and model delays are serious, but Google retains enormous advantages through Search, Workspace, Android, Cloud, custom AI chips and consumer distribution. Google says the Gemini app has surpassed 950 million monthly users, giving it a reach that does not depend entirely on owning the highest-scoring model. Current benchmarks similarly depict a company behind the overall leaders but still firmly competitive. Artificial Analysis places Claude Opus 5 at 63 on its overall model Intelligence Index, while Google reports a score of 56 for Gemini 3.7 Flash -- an improvement from 52 for 3.6 Flash but not a return to the top. Arena's early human-preference results are more favorable, provisionally ranking 3.7 Flash ninth overall and eighth for web development. The resulting picture is not that Google has abandoned advanced AI, but that it has become stronger at rapidly shipping efficient Flash models while struggling to deliver the premium flagship required to reclaim broad leadership. Gemini 4 will now serve as the clearest test of whether the leadership reorganization fixes that execution gap. Available now across Google's developer stack Developers can access Gemini 3.7 Flash through the Gemini API in Google AI Studio and Android Studio, as well as Google's Antigravity environment. Enterprises can deploy it through Gemini Enterprise Agent Platform and Gemini Enterprise, while consumers with Google AI Pro or Ultra subscriptions can access the model through Spark in supported countries. Google is also shipping updated safeguards covering chemical, biological, radiological and nuclear risks and cyber-offense misuse, according to the company. The unusually fast jump from Gemini 3.6 Flash to 3.7 Flash points toward a model development cycle in which algorithmic improvements can reach production products without waiting for a new flagship generation. Ars Technica also highlighted the three-week interval between the two releases, while Google says the techniques behind the update will inform future models. For developers, that faster cadence creates its own operational question. Models can improve quickly, but production teams still have to benchmark new releases against their own repositories, prompts, tool schemas and failure modes before changing a deployment. Gemini 3.7 Flash gives those teams a particularly strong incentive to run that evaluation. Google's own numbers show major improvements in production coding, web development, document comprehension and workflow automation without claiming leadership everywhere. At its introductory price, Google is effectively betting that developers will value a model that is competitive enough with more expensive systems while being cheap enough to run repeatedly inside agents. Whether that advantage survives the return to full pricing in January will depend less on leaderboard positions than on how reliably 3.7 Flash completes real work.

Google launches Gemini 3.7 Flash AI model for coding

Gemini 3.7 Flash arrives three weeks after the previous Flash update, at half the price, as Google has yet to release a promised update to its larger model Google $GOOGL introduced Gemini 3.7 Flash on Thursday, a model aimed at coding and autonomous AI workflows, even as Gemini 3.5 Pro -- a previously promised upgrade to its larger flagship model -- has not yet materialized, according to Axios. Gemini 3.7 Flash follows its predecessor by roughly three weeks, and Google says the new model handles coding work more effectively, pointing to gains in areas like fixing bugs, resolving issues, and generating code ready for deployment. On the FrontierCode 1.1 benchmark, 3.7 Flash scored 43.6% compared with 34.4% for its predecessor, and on DeepSWE v1.1 it scored 65.3% versus 49.0%, the company said. The company is marketing the model to businesses developing autonomous AI systems as a cheaper alternative, Reuters reported. The company said Gemini 3.7 Flash will be priced at $0.75 per million input tokens and $3.75 per million output tokens through year-end -- a 50% discount from what Gemini 3.6 Flash originally cost. Beyond coding, Google said 3.7 Flash delivers improved performance in knowledge-dense fields such as finance, law, and biosciences, outperforming its predecessor on the GDP.pdf benchmark for complex document processing (34.0% versus 22.0%) and on AutomationBench, which tests real-world business workflow completion (30.4% versus 17.0%). Google is also bringing the new model to Gemini Spark, the AI agent service it offers to Google AI Pro and Ultra subscribers across more than 160 countries. Google described Gemini Spark at its I/O developer conference as a personal AI agent that runs continuously on Google Cloud to complete tasks on a user's behalf across Gmail, Google Docs, and other Workspace tools. Google said the 3.7 Flash update makes Spark more capable at multi-step workflows involving those applications. The release comes amid leadership upheaval at Google DeepMind. The shake-up last week saw Demis Hassabis hand leadership of Google DeepMind to his deputy, Koray Kavukcuoglu, while the pair of engineers who originally led Gemini's technical development departed to found their own venture, according to Reuters. As for Gemini 3.5 Pro, Axios reported that Google wouldn't say what it plans to do with the model, and given that the company has acknowledged it is already working toward Gemini 4 with promising early signals, the release of 3.5 Pro may be abandoned altogether, with Gemini 4 Pro taking its place.

Google launches Gemini 3.7 Flash for coding, AI agent projects

Google LLC today launched its most capable entry-level artificial intelligence model yet. Gemini 3.7 Flash is rolling out three weeks after its predecessor. Despite the short release cycle, Google engineers managed to implement significant output quality improvements. The company says that Gemini 3.7 Flash outperformed comparable models from Anthropic PBC and OpenAI Group PBC across nine benchmarks. One of the evaluations in which the AI earned first place is FrontierCode 1.1 Main. It comprises 100 programming tasks spanning multiple languages. The benchmark requires models to not only produce working code, but also comply with other requirements that often crop up in enterprise software projects. Code must undergo bug testing before it's submitted and follow project-specific style guides. Compared to its predecessor, Gemini 3.7 is particularly adept at generating user interfaces. Google says that layouts designed by the model more closely align with reference images uploaded by the user. Gemini 3.7 Flash can process up to 1 million tokens worth of images, video and text per prompt. Its prompt responses comprise up to 64,000 tokens of text. "Gemini 3.7 Flash delivers a noticeably improved developer experience over 3.6 Flash," Tulsee Doshi, a senior director of product management at Google, wrote in a blog post. "It better adapts to roadblocks, clarifies intent when needed, and follows instructions with greater fidelity. It thinks more diligently, putting in more effort into multi-step planning and tool calls." The model also lends itself to other tasks besides programming. Google tested it using GDP.pdf benchmark, a benchmark that requires neural networks to answer questions about business documents. It answered 34% of the questions correctly, which put it 6% and 9.3% ahead of Claude Sonnet 5 and GPT-5.6 Terra, respectively. Furthermore, Google says that Gemini 3.7 Flash can power AI agent ensembles. Google didn't specify the model's architecture. Gemini 3.7 Flash's model card indicates that it's based on the same architecture as the company's previous-generation Gemini 3.6 Flash model. That algorithm, in turn, is derived from Gemini 3 Pro, which features a transformer-based mixture of experts architecture. Gemini 3.7 Flash's model card also lacks information about how it was trained. Developers often train entry-level neural networks by distilling the output of a more capable AI in the same algorithm series. Meta Platforms Inc., for example, created its recently released Muse Glimmer language model by distilling Muse Spark. Google will enable developers to access Gemini 3.7 Flash for half the price of Gemini 3.6 Flash through the end of the year. Additionally, the company is bringing the model to Gemini Spark, a consumer-focused AI agent that debuted in March. It can browse the web and perform actions in other Google services.

Google Launches Gemini 3.7 Flash Model With These Capabilities

Gemini 3.7 Flash is claimed to offer improved developer experience Gemini 3.7 Flash, the latest AI model from the Mountain View-based tech giant, was launched globally on Thursday, the company announced. The new AI model succeeds the Gemini 3.6 Flash, which was released earlier this year, in July, along with the Gemini 3.5-Lite model. The company claims that the new Gemini 3.7 model delivers enhanced capabilities in terms of software engineering, knowledge work, and web development workflows. Currently being rolled out for developers, enterprises, and individual users, the tech giant is offering Gemini 3.7 Flash at an introductory price. The company is also upgrading Gemini Spark with the new Gemini 3 series model. Gemini 3.7 Flash Price, Availability Google has announced that the Gemini 3.7 Flash is offered at an introductory price of half the original Gemini 3.6 Flash AI model cost per million tokens. The tech giant has started rolling out the new Gemini 3 series model, and developers can access it via Google Antigravity, Google AI Studio, and Android Studio. Similarly, the Gemini 3.7 Flash model is available to enterprises via the Gemini Enterprise Agent Platform and the Gemini Enterprise app. On the other hand, individual Google AI Pro and Google Ultra subscribers can access the latest Gemini model via the Gemini app in select regions. Moreover, the company is upgrading Gemini Spark, its new personal AI agent, to Gemini 3.7 Flash, allowing users to access the AI model via the same interface. Gemini 3.7 Flash Capabilities, Features As previously mentioned, Google claims that the Gemini 3.7 Flash offers enhanced capabilities over its predecessor in multiple departments. The AI model is claimed to provide improved intelligence for complex workflows, coding, workflow automation, document comprehension, web development, and long-horizon software engineering. On FrontierCode 1.1 Main, Gemini 3.7 Flash outperformed Gemini 3.6 Flash, Anthropic's Claude Sonnet 5, and OpenAI's GPT 5.6 Terra by scoring 43.6 percent, while its rivals scored 34.4 percent, 42.7 percent, and 41.3 percent, respectively. Gemini 3.7 Flash outperformed its rivals on various benchmarking platforms Photo Credit: Google Similarly, on DeepSWE V1.1, Gemini 3.7 Flash scored 65.3 percent, outperforming Gemini 3.6 Flash's 48.6 percent, Claude Sonnet 5's 53.8 percent, and Meta's Muse Spark 1.2's 54.9 percent scores. However, the GPT-5.6 Terra scored 69.6 percent, which is significantly higher than Gemini 3.7 Flash's score. In terms of web development, the Gemini 3.7 Flash model scored 1,588 points on Code Arena, while Gemini 3.6 Flash, Claude Sonnet 5, GPT-5.6 Terra, and Muse Spark 1.2 managed to score 1,538, 1,541, 1,523, and 1,535 points, respectively. Google's new Gemini 3.7 Flash also outperformed its predecessor and rivals in the Expert PDF Document Comprehension test on GDP.pdf, scoring 34 percent, compared to Gemini 3.6 Flash, Claude Sonnet 5, GPT-5.6 Terra, and Muse Spark 1.2's scores of 22 percent, 28 percent, 24.7 percent, and 16 percent. Similarly, for Enterprise Workflow Automation, Gemini 3.7 Flash scored 30.4 percent on the Automation Bench, outperforming Gemini 3.6 Flash, Claude Sonnet 5, and GPT-5.6 Terra by a significant margin.

Google unveils Gemini 3.7 Flash AI model for coding, agent workflows

Alphabet's Google launched Gemini 3.7 Flash on Thursday, its latest AI model designed for software coding and automated business tasks, but offered no details on when its flagship Pro model will be released. Investors have been closely watching for Gemini 3.5 Pro, Google's premium model, as a test of whether its DeepMind AI unit can keep pace with rivals Anthropic and OpenAI. Google had ⁠said ⁠in July Gemini 3.5 Pro was being tested with partners and would be coming "soon". Here are a few details on Gemini 3.7 Flash: The company is pitching the model as a lower-cost option for businesses building autonomous AI systems that can plan tasks, use software tools and complete multi-step workflows with less human intervention. Gemini 3.7 Flash is released three weeks after Gemini 3.6 Flash. It has shown improved ⁠performance on coding tasks, including debugging, issue resolution and production-ready code generation, according to a Google blog post. To drive adoption, Google is offering Gemini ⁠3.7 Flash at an introductory rate of 75 cents per million input tokens and $3.75 per million output tokens through the end of the year, half the original cost of Gemini 3.6 Flash. The model is also being rolled out immediately to Gemini Spark, Google's subscription-based AI agent service available to Google AI Pro and Ultra customers in more than 160 countries. Google co-founder Sergey Brin in recent months has urged key AI staff to go all in on the company's Gemini model as parent Alphabet seeks to close the gap with rivals, Reuters exclusively reported on Wednesday. Last week, the tech ⁠giant announced a sweeping leadership overhaul of its Google DeepMind AI division in which its chief, Demis Hassabis, stepped aside in favor of his deputy, Koray Kavukcuoglu. At the same time, the two original technical co-leads of Gemini quit to co-found a startup. CEO Sundar Pichai mounted a robust defense of Google's AI strategy during its earnings call in July, pushing back on concerns that the company has fallen behind rivals after delaying the flagship model and ceding ground in AI coding.

Google Gemini 3.7 Flash launched with Software Code Agent

Mountain View-based giant Google launched its all-new Gemini 3.7 Flash AI model, which has been upgraded to integrate with software tools to help with coding, software development, and complex knowledge work. As part of the Flash 3.7 launch, Google is also offering an attractive introductory offer available till the end of 2026. Here are all the new features in Google Flash 3.7. * Make Telecom Talk My Trusted Source Google Announces Gemini 3.7 Flash for Agents Google has launched Gemini 3.7 Flash, a model in its Flash series. This artificial intelligence model focuses on software and web development, as well as AI agent workflows. The company calls it a powerful "workhorse" for coding and agents. Improvements help developers create and grow production AI applications. Gemini 3.7 Flash is built to improve performance in software engineering, coding, and complex knowledge work. Google says the model produces accurate first-pass code and follows instructions better. It also adheres more strongly to design principles when creating user interfaces and web applications. The latest model places heavy emphasis on AI. AI agents are built to perform multi-step tasks using tools and applications rather than just responding to prompts. Gemini 3.7 Flash is designed to improve planning, tool use, and workflow management with less manual assistance.

How Gemini 3.7 Flash Defeats GPT-5.6 Terra at Long Context

Google DeepMind and OpenAI have unveiled two significant updates in the AI landscape: Gemini 3.7 Flash and GPT-5.6 Ultra-Fast Mode. According to Universe of AI, Gemini 3.7 Flash builds on its predecessor with a notable 43.6% code quality success rate and excels in tasks like long video understanding, where it outperforms comparable models. Meanwhile, GPT-5.6 Ultra-Fast Mode introduces an impressive processing speed of 750 tokens per second, using advanced Cabus chips to support real-time applications across industries. These advancements highlight the growing focus on both efficiency and specialized enterprise use cases. Explore how Gemini 3.7 Flash balances cost-effectiveness with robust long-context capabilities for tasks like document summarization and video analysis. Additionally, gain insight into the industries poised to benefit from GPT-5.6 Ultra-Fast Mode, including customer support and financial analysis, where rapid processing is critical. This overview examines the evolving dynamics between these models and their potential to shape enterprise AI strategies in the coming years. Gemini 3.7 Flash: A Balanced Performer for Enterprise Needs Google DeepMind's Gemini 3.7 Flash builds upon the success of its predecessor, Gemini 3.6 Flash, by incorporating substantial improvements in performance and user-focused refinements. Released just three weeks after the earlier model, it integrates developer feedback and algorithmic upgrades to provide a mid-tier solution that balances cost-effectiveness with robust functionality. While it does not directly compete with high-tier models like OpenAI's GPT-5.6 Soul, it offers distinct advantages in specific areas. Key performance metrics for Gemini 3.7 Flash include: * Code quality improvement: Achieved a 43.6% success rate, up from 34.4% in Gemini 3.6 Flash. * Long video understanding: Reached 85.4%, outperforming GPT-5.6 Terra's 78.9% in this category. * Long context performance: Improved to 97%, compared to 93.5% for GPT-5.6 Terra. * Web development ELO score: Increased to 1588, a notable jump from 1538 in the previous version. These enhancements position Gemini 3.7 Flash as a strong contender for tasks requiring long-context comprehension, such as video analysis, document summarization and web development. Its competitive pricing strategy, valid through the end of 2026, makes it an appealing choice for enterprises seeking cost-effective AI solutions. However, prices are expected to rise in 2027, reflecting its growing market demand and value. GPT-5.6 Ultra-Fast Mode: Redefining Speed in AI OpenAI's GPT-5.6 Ultra-Fast Mode introduces a new level of processing speed, achieving up to 750 output tokens per second, 14 times faster than its standard mode. This remarkable performance is driven by the integration of advanced Cabus chips, which enhance computational efficiency and enable real-time applications across various industries. The Ultra-Fast Mode is specifically designed for time-sensitive, high-volume tasks, including: * Customer support and voice-based interactions, where rapid response times are critical. * Commerce and live research activities that demand real-time data processing. * Financial analysis and rapid incident response for dynamic decision-making. These capabilities make GPT-5.6 Ultra-Fast Mode a fantastic tool for industries that rely on real-time operations. While currently available via a waitlist, OpenAI has yet to release detailed pricing information. Nonetheless, the model's unparalleled speed and versatility are expected to attract significant interest from enterprises aiming to streamline workflows and enhance operational efficiency. Take a look at other insightful guides from our broad collection that might capture your interest in Google DeepMind. Shaping the Competitive AI Landscape The release of Gemini 3.7 Flash and GPT-5.6 Ultra-Fast Mode underscores the accelerating pace of AI innovation and its growing impact across industries. Both models use advanced hardware and refined algorithms to address diverse enterprise needs, from long-context comprehension to real-time data processing. In parallel, Meta's Muse Spark 1.2 has entered the competitive landscape, showing promising results in early benchmarks. While Gemini 3.7 Flash targets mid-tier markets with its cost-effective approach, OpenAI's GPT-5.6 Ultra-Fast Mode focuses on high-speed, high-volume use cases. Additionally, anticipation is building for Google DeepMind's Gemini 4 lineup, which is expected to challenge high-tier models like GPT-5.6 Soul and further intensify competition in the AI sector. As the industry evolves, these advancements highlight the importance of tailoring AI solutions to meet specific enterprise demands. The competitive dynamics between major players like Google DeepMind, OpenAI and Meta are likely to drive further innovation, pushing the boundaries of what AI can achieve in both performance and application. Driving the Future of AI Innovation The advancements represented by Gemini 3.7 Flash and GPT-5.6 Ultra-Fast Mode demonstrate the fantastic potential of AI technologies in reshaping enterprise operations. With faster processing speeds, improved benchmarks and tailored applications, these models are poised to redefine how businesses use AI for competitive advantage. As competition among industry leaders intensifies, the stage is set for even greater breakthroughs, paving the way for the next generation of AI solutions that will further enhance efficiency, scalability and innovation across sectors. Media Credit: Universe of AI Disclosure: Some of our articles include affiliate links. If you buy something through one of these links, Geeky Gadgets may earn an affiliate commission. Learn about our Disclosure Policy.

Google rolls out Gemini 3.7 Flash with improved coding, AI agents and web development

Google has introduced Gemini 3.7 Flash, its latest Flash model for coding, AI agents, web development, and knowledge-intensive tasks. Tulsee Doshi, Senior Director of Product Management at Google, said Gemini 3.7 Flash builds on the company's Flash series, with improvements driven by developer feedback and algorithmic innovations that Google plans to carry into future models. Gemini 3.7 Flash The release comes three weeks after Gemini 3.6 Flash and brings improvements across software engineering, knowledge work, and web development workflows. The model is designed to improve coding accuracy, handle multi-step tasks, and work with tools more effectively. It is available at an introductory price of half the original Gemini 3.6 Flash cost per million tokens. Coding and web development Gemini 3.7 Flash brings improvements to software engineering tasks, including debugging, issue resolution, first-pass code accuracy, and production-ready code generation. The model's coding benchmark results include: * FrontierCode 1.1 Main: 43.6%, compared with 34.4% for Gemini 3.6 Flash * DeepSWE v1.1: 65.3%, compared with 49.0% for Gemini 3.6 Flash For web development, Gemini 3.7 Flash can generate more functional layouts and feature-complete apps with fewer prompts. For UI generation, it supports reference inputs including a screenshot, image, or full design system, with design adherence and parity based on the reference. On Arena.ai's WebDev Arena, Gemini 3.7 Flash achieved an Elo score of 1588, compared with 1538 for Gemini 3.6 Flash. Knowledge work and developer experience Gemini 3.7 Flash also improves reasoning and accuracy in knowledge-intensive fields such as finance, law, and biosciences. * GDP.pdf: 34.0%, compared with 22.0% for Gemini 3.6 Flash. The benchmark evaluates a model's ability to process complex documents. * AutomationBench: 30.4%, compared with 17.0% for Gemini 3.6 Flash. The benchmark evaluates the completion of real-world business workflows. Google says the model also improves developer workflows by: * Adapting to roadblocks * Clarifying intent when needed * Following instructions with greater fidelity * Putting more effort into multi-step planning * Handling tool calls with more deliberate execution Gemini Spark update Gemini Spark will start using Gemini 3.7 Flash today. Spark is Google's personal AI agent that runs 24/7 and takes action on the user's behalf while remaining under their direction. The update brings improved tool use with Google Workspace apps and supports complex, multi-skill workflows. Examples include: * Consolidating files * Drafting emails * Updating status documents Safety Gemini 3.7 Flash ships with updated Frontier Safety safeguards for potential misuse involving Chemical, Biological, Radiological, and Nuclear (CBRN) applications and cyber offense. Google says the updates are part of its work on bioresilience and its cyber program. Pricing and availability Gemini 3.7 Flash is available at an introductory price of: * Input: $0.75 per 1 million tokens * Output: $3.75 per 1 million tokens * Introductory pricing ends: December 31, 2026 * From January 1, 2027: $1.50 per 1 million input tokens and $7.50 per 1 million output tokens The model is available through: * Developers: Google Antigravity, Gemini API, Google AI Studio, and Android Studio * Enterprises: Gemini Enterprise Agent Platform and Gemini Enterprise app * Individuals: Spark in the Gemini app for Google AI Pro and Ultra subscribers in supported countries Gemini Spark is available to Google AI Pro and Ultra subscribers in more than 160 countries.

Gemini 3.7 Flash Arrives: Why Google Is Betting on Faster AI for Agentic Workflows

Google launched Gemini 3.7 Flash on August 13, 2026, just three weeks after Gemini 3.6 Flash. The new model targets software work, AI agents, document tasks, and multi-step business jobs. Google calls it a workhorse model, with a focus on strong results at a lower cost. Reuters notes that Google still has not shared a launch date for Gemini 3.5 Pro, the expected high-end model. Gemini 3.7 Flash targets a harder task than a normal chatbot. A chatbot can answer one request and stop. An AI agent must plan a task, use tools, read the result, fix errors, and take the next step. A long task may need many model calls. Google reports a sharp gain on AutomationBench, where Gemini 3.7 Flash scored 30.4%, up from 17.0% for . That marks a 78.8% relative rise. Google says the model can handle roadblocks, follow detailed instructions, plan tasks, and use tools with better control.

Google releases Gemini 3.7 Flash AI model for coding tasks By Investing.com

Investing.com -- Alphabet's Google introduced Gemini 3.7 Flash on Thursday, a new artificial intelligence model built for software coding and automated business operations. The company did not provide a timeline for the release of its flagship Pro model. The tech giant is marketing the model as a budget-friendly choice for companies developing autonomous AI systems capable of planning tasks, utilizing software tools and executing multi-step workflows with reduced human oversight. Gemini 3.7 Flash arrives three weeks after the launch of Gemini 3.6 Flash. The new model demonstrates better performance in coding tasks, including debugging, issue resolution and production-ready code generation, according to a Google blog post. Google set an introductory price of 75 cents per million input tokens and $3.75 per million output tokens through the end of the year, which represents half the original cost of Gemini 3.6 Flash. The model is now available through Gemini Spark, Google's subscription-based AI agent service for Google AI Pro and Ultra customers in more than 160 countries. Investors continue to await Gemini 3.5 Pro, Google's premium model, as a measure of whether its DeepMind AI unit can maintain competitive standing with rivals Anthropic and OpenAI. Google stated in July that Gemini 3.5 Pro was undergoing testing with partners and would launch soon. This article was generated with the support of AI and reviewed by an editor. For more information see our T&C.

Gemini 3.7 Flash vs 3.6 Flash: Google's latest AI upgrade for coders

Google just did something unusual in the AI race: it shipped a meaningfully better model without waiting for a new training run. The Gemini 3.7 Flash was released only three weeks after the previous version of the software - Gemini 3.6 Flash - and rather than being considered another pretraining of the model, it is described as an enhanced version of the 3.6 Flash based on better algorithms of reasoning. Also read: Our focus is to build durable products that are adjacent to our main business: Urban Company's Rishabhdhwaj Singh What's actually better The improvement has been aimed at coders and developers. In the FrontierCode 1.1 Main test of production code quality, 3.7 Flash scores 43.6%, against 34.4% of 3.6 Flash. In the DeepSWE v1.1 benchmark test of long-horizon software engineering, 3.7 Flash scores 65.3%, compared to 49.0% for 3.6 Flash. Google claims that the model demonstrates improvements in debugging and issue fixing, not just in Q&A precision, and creates more feature-complete web applications in fewer prompts. This is important because independent tests show that the model's advantage lies in evaluations that demand sustained reasoning through a multi-step process, not in answering one particular question correctly - the type of task that requires an agent to examine files, make edits, and debug its own mistakes, all while maintaining the context. On tasks involving documents, 3.7 Flash scores 34.0%, significantly higher than 3.6 Flash, which scores 22.0% on the GDP.pdf benchmark of complex document processing. On the AutomationBench test of completing business workflows, 3.7 Flash scores 30.4% against 17.0% of 3.6 Flash. Also read: Top AI features of the Google Pixel 11 series It's not a clean sweep, though. On CharXiv Reasoning, a chart-comprehension test, 3.7 Flash actually regresses slightly to 84.5% without tools, down from 85.2% for 3.6 Flash. If your workflow leans on chart-heavy analysis, that's worth flagging before you switch defaults. The pricing catch This is where it gets really exciting for anybody operating agents at scale. Gemini 3.7 Flash will be priced at $0.75 per 1M input tokens and $3.75 per 1M output tokens - a reduction of 50% from the list price of the original 3.6 Flash and more or less equivalent to one-third of the cost of their competitor's state-of-the-art models. But it should be noted that these prices are introductory prices that will lapse on December 31, 2026. From January 1, 2027, it will be priced at $1.50 per 1M input tokens and $7.50 per 1M output tokens - the same price as the existing 3.6 Flash. What stayed the same Besides the fine-tuning of the algorithm, this is not a more substantial or fundamentally new model. It takes text, image, audio, and video input within the context of a 1M token window, producing an output of up to 64K tokens, and both the models have identical restrictions on headline contexts, cost, multimodal input capabilities, caching, code execution, function calling, and use of computer in preview mode. Knowledge cutoff remains unchanged, which is March 2026. Should you switch? If you are on 3.6 Flash right now, then the math is pretty simple: 3.7 will just be an upgrade that gives you zero negative cost trade-off during the promotion period, while beating 3.6 by far on the benchmarks of importance for actual development work. The regression on chart reasoning is too small to make people regret going for 3.7, but it is something that should be taken into account in case you use visual data analysis in your pipeline and have a regression testing suite. What is interesting to see is how Google behaves after the expiration of the promotion period in 2027.

Google introduces Gemini 3.7 Flash AI model, claims it outperforms Claude Sonnet 5

oogle claims Gemini 3.7 Flash delivers improvements across software engineering, knowledge work, and web development workflows. Google has introduced Gemini 3.7 Flash, its latest AI model designed for coding. The company says the new model is its "most intelligent workhorse model yet for coding and agents," and brings major improvements over Gemini 3.6 Flash. Google claims Gemini 3.7 Flash delivers improvements across software engineering, knowledge work, and web development workflows. In comparison charts shared by the company, Gemini 3.7 Flash also scores higher than Claude Sonnet 5 across several tests. Keep reading for all the details about Gemini 3.7 Flash. Gemini 3.7 Flash: Capabilities Google claims Gemini 3.7 Flash performs better at debugging, fixing issues and generating production-ready code. On the FrontierCode 1.1 Main benchmark, it scored 43.6 per cent, compared with 34.4 per cent scored by Gemini 3.6 Flash. On DeepSWE v1.1, 3.7 Flash scored 65.3 per cent, up from 49 per cent achieved by the previous model. The model also brings improvements to web development. Google says it can create more functional layouts and feature-complete apps in fewer prompts. It can also better match a given design, screenshot or reference image. Gemini 3.7 Flash has also improved in areas such as finance, law and biosciences. On the GDP.pdf benchmark, it scored 34 per cent, compared with 22 per cent by Gemini 3.6 Flash. On AutomationBench, it scored 30.4 per cent, compared with 17 per cent scored by the older model. Also read: OpenAI may soon show ads on ChatGPT in India, here's who will see them Google also claims that Gemini 3.7 Flash "better adapts to roadblocks" and follows instructions more closely. "It thinks more diligently, putting in more effort into multi-step planning and tool calls," the company said. In Google's comparison charts, Gemini 3.7 Flash also beats Claude Sonnet 5 on FrontierCode 1.1, DeepSWE v1.1, Code Arena, GDP.pdf and AutomationBench. Gemini 3.7 Flash: Availability Gemini 3.7 Flash is available at an introductory price of $0.75 per 1 million input tokens and $3.75 per 1 million output tokens. Google says this pricing will remain through the end of the year. Developers can access the model through Google Antigravity and the Gemini API via Google AI Studio and Android Studio. Businesses can use it through Gemini Enterprise Agent Platform and the Gemini Enterprise app. For individual users, the new AI model is available via Gemini Spark