Google Launches Gemini 3.7 Flash AI Model Three Weeks After Last Release, Cuts Pricing by 50%

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 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

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 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 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.