OpenAI slashes GPT-5.6 prices by up to 80% as businesses push back on AI costs

OpenAI cuts prices on smaller models as businesses scrutinize AI spend

July 30 (Reuters) - OpenAI slashed prices of its low- and mid-tier AI models on Thursday, a move that may intensify competition in the industry as U.S. companies battle cheaper Chinese rivals for customers increasingly wary of the technology's ballooning costs. The ChatGPT maker lowered the cost of its smaller GPT-5.6 Luna model by 80% and its mid-tier Terra by 20%, while leaving the price of its biggest and flagship Sol model unchanged. The cuts show that rising cost scrutiny by businesses facing hefty AI bills is forcing American labs to rethink pricing. Many tech CEOs have also said in recent months that cheaper AI options are key to ⁠the technology's widespread adoption. OpenAI's new pricing also turns up the heat on Anthropic, whose Claude models dominate enterprise and developer use but sit at the costlier end of the market. Both companies have been under pressure from open-source Chinese rivals such as Z.ai's GLM-5.2 that nearly match their performance at a lower cost. Analysts have said that cutting prices could boost usage of OpenAI's and Anthropic's technology, but strain their finances ahead of highly anticipated initial public offerings. While Thursday's cuts affect only OpenAI's smaller and mid-tier models, the company said it would still benefit businesses broadly as those models can now do ⁠work that recently required a top-tier system at far lower cost. The new pricing means businesses using OpenAI's technology will have to pay less for every million "tokens", or the units used to measure AI usage, they run through the models. Sending text to Luna drops to 20 cents per million tokens from $1 and Terra's to $2 from $2.50, ⁠while generating responses falls to $1.20 and $12 from $6 and $15, respectively. Anthropic's mid-tier Claude Sonnet 4.6 model, meanwhile, costs $3 per million input tokens and $15 per million output tokens, above the rates for Terra. OpenAI said the lower prices were partly enabled ⁠by efficiency gains from GPT-5.6, including the model's ability to improve code and optimize performance during internal development. Overall, prices of tokens have been falling in the past year, but the cost of completing ⁠a task is rising as AI firms shift from flat subscriptions to usage-based pricing. That is leaving companies with unpredictable and often higher bills as usage per task becomes harder to estimate. Reporting by Aditya Soni in Bengaluru and Deepa Seetharaman in San Francisco; Editing by Devika Syamnath Our Standards: The Thomson Reuters Trust Principles., opens new tab

OpenAI cuts prices for two of its GPT-5.6 AI models as companies grow sensitive to costs

OpenAI on Thursday announced it is slashing the price of two of its latest artificial intelligence models, GPT-5.6 Terra and GPT-5.6 Luna, roughly three weeks after their public release. The company is facing pressure to cater to a more cost-sensitive customer base, where enterprises have been less inclined to deploy expensive models without a clear picture of the return on their investments. It's also working to fend off competition from Chinese startups and tech giants Google and Microsoft, which have been touting cost-effective models. OpenAI launched three models as part of its GPT-5.6 series, including Sol, the most powerful offering, Terra, the mid-tier model, and Luna, its fastest offering. The company said Thursday that it's reducing the price of Terra by 20% to $2 per million input tokens and $12 per million output tokens. It's cutting the cost of Luna by 80% to 20 cents per million input tokens and $1.20 per million output tokens. Sol's pricing remains the same. "Our strategy remains focused on advancing both capability and efficiency so each generation of intelligence can accomplish more work at a lower cost," OpenAI said in a release. OpenAI kickstarted the AI boom with the launch of ChatGPT in 2022, prompting companies across the U.S. to rush to deploy the technology and incentivize adoption within their workforces. The era of so-called tokenmaxxing was born, where employers encouraged staffers to use as much AI as possible without worrying about costs.

AI price wars: OpenAI cuts GPT-5.6 Luna prices by 80% as model competition shifts toward cost

To quote an ancient Jedi Master "Begun, the AI price wars have!" OpenAI is sharply reducing the prices of two models in its GPT-5.6 frontier series, cutting GPT-5.6 Luna, the smallest and fastest model in the series, by 80% and GPT-5.6 Terra, the mid-tier model, by 20%, while adding a premium Fast mode for its flagship GPT-5.6 Sol model. The cuts place Luna much closer to the lowest-cost commercial models in the market and arrive just a few days after Anthropic released its highly performant Claude Opus 5 at the same price as Opus 4.8, and Google introduced Gemini 3.6 Flash and Gemini 3.5 Flash-Lite, two rival models built around lower inference costs, faster execution and more efficient agent workloads. OpenAI is successfully undercutting Google's price per intelligence and attempting to sway Anthropic users, who may not mind paying more, with a speed boost. OpenAI says Luna will now cost $0.20 per million input tokens and $1.20 per million output tokens, for a combined input-plus-output price of $1.40 per million tokens. Terra will cost $2 per million input tokens and $12 per million output tokens, for a combined price of $14. Pricing for Sol Standard remains unchanged at $5 per million input tokens and $30 per million output tokens. OpenAI is also adding Sol Fast mode at twice the Standard price: $10 per million input tokens and $60 per million output tokens. The company says Fast mode delivers up to 2.5 times the throughput without changing the model's underlying intelligence. OpenAI co-founder and CEO Sam Altman took to X to announce the changes as "major price cuts today." VentureBeat Frontier AI model API pricing comparison Pricing is shown per one million tokens. Total cost is calculated as input price plus output price. Cached-input pricing is excluded to keep the comparison consistent across providers. OpenAI moves Luna into the low-cost tier The most consequential change is the Luna price cut. When OpenAI introduced the GPT-5.6 series, Luna was priced at $1 per million input tokens and $6 per million output tokens, for a combined total of $7. The new pricing reduces that combined figure to $1.40. That places Luna below Google's Gemini 3.5 Flash-Lite, which costs a combined $2.80 per million input and output tokens, and far below Gemini 3.6 Flash at $9. Luna also now costs less than OpenAI's own GPT-5.4 and Terra models by a wide margin. It is not the cheapest model in the broader market. Xiaomi's MiMo-V2.5 Flash, DeepSeek's flash model and several other APIs remain less expensive on a pure token basis. But the reduction brings an OpenAI frontier-series model into direct competition with the market's low-cost inference tier. OpenAI says the GPT-5.6 series represents its frontier model family, with Sol positioned at the top of the lineup, Terra as the middle tier and Luna as the smallest and fastest option. The lineup was initially released in late June 2026 through a limited rollout by U.S. government request, before broader access, with each model intended to offer a different tradeoff among intelligence, latency and cost. Sol is aimed at the most complex reasoning-heavy and agentic workloads, including advanced coding, multi-step planning and tool-using systems, while Terra is designed for general production use where a balance of capability and efficiency is required. Luna is positioned for high-throughput, low-latency tasks such as summarization, classification, routing, and lightweight real-time assistants where cost per request is the primary constraint. Terra drops to match Google's Gemini 3.1 Pro pricing Terra's 20% reduction moves its combined price from $17.50 to $14 per million tokens. At that level, Terra now matches Google's Gemini 3.1 Pro Preview pricing for context windows of 200,000 tokens or less. It also undercuts OpenAI's GPT-5.4, which remains priced at $2.50 per million input tokens and $15 per million output tokens, offering the same intelligence for about 1/13th the cost, as Krea AI's Nic Dunz noted on X: The adjustment creates a wider separation between OpenAI's three GPT-5.6 tiers. Luna costs one-tenth as much as Terra on a simple combined input-plus-output basis, while Terra costs 60% less than Sol Standard. Sol Fast moves in the opposite direction. At a combined $70 per million tokens, it is the most expensive model configuration in the comparison below, reflecting OpenAI's decision to charge a premium for latency-sensitive workloads rather than lower Sol's base price. Cuts follow Google's low-cost Gemini releases and Anthropic's Claude Opus 5 OpenAI's pricing changes come only about a week and a half after Google introduced its own low-cost Gemini 3.6 Flash and Gemini 3.5 Flash-Lite. Google priced Gemini 3.6 Flash at $1.50 per million input tokens and $7.50 per million output tokens. Gemini 3.5 Flash-Lite costs $0.30 per million input tokens and $2.50 per million output tokens. Google framed both models around the economics of agent deployment, arguing that lower token usage, fewer reasoning steps and reduced tool calls could lower the total cost of long-running software engineering and knowledge-work tasks. Gemini 3.6 Flash reportedly uses 17% fewer output tokens than Gemini 3.5 Flash on the Artificial Analysis Index, with savings reaching as high as 65% on some long-horizon engineering workloads. Gemini 3.5 Flash-Lite is positioned as the fastest model in Google's 3.5 series. However, OpenAI's models are more performant than Google's, according to third party analysis outfits like Artificial Analysis, with even the Luna model outperforming Gemini 3.6 Flash and the older Gemini 3.1 Pro model, making the cost-per intelligence much more favorable to OpenAI. As AI coding startup Cognition noted on X, GPT-5.6 now "sits on the pareto curve of price/performance efficiency," posting an animation of the GPT-5.6 series moving left on a chart representing intelligence on the y axis and cost on the x, showing that the models now offer among the most superior intelligence for lowest cost on the market. And yet, rival Anthropic's Claude Opus 5 remains about as performant as GPT-5.6 Sol, yet is 6% cheaper. The model costs $5 per million input tokens and $25 per million output tokens -- the same rates as Opus 4.8 -- but Anthropic says it delivers nearly all the intelligence of its more expensive Fable 5 model at roughly half the cost. Unlike OpenAI's Luna and Terra changes, Anthropic did not reduce the Opus API sticker price. Instead, it effectively lowered the price per unit of capability by replacing Opus 4.8 with a more capable model at the same $30 combined input-and-output rate. Anthropic also added an adjustable effort setting that allows developers to trade reasoning depth for speed and token savings. That distinction matters for enterprise buyers. OpenAI is directly cutting per-token rates, Google is pairing lower prices with reductions in token use and tool calls, and Anthropic is emphasizing stronger task performance at an unchanged price. All three approaches target the same operational metric: the total cost of completing production work, rather than the advertised cost of an individual token alone. The timing highlights how quickly pricing has become a competitive lever among frontier model providers. OpenAI's response does not introduce a new model generation. Instead, it changes the economics of deploying models that were released only recently. The market shifts from model access to model economics The cuts indicate that access to frontier-level capability is no longer the only point of competition. The next question for enterprises is how cheaply and predictably those models can run in production. OpenAI is still not the lowest-priced provider on a pure token basis. But Luna's 80% reduction materially changes its position, moving it from the middle of the market into a pricing tier populated by smaller models from Google, Xiaomi, DeepSeek, MiniMax and other vendors. That matters most for high-volume applications, where relatively small differences in token pricing can compound across coding agents, document systems, internal search tools and automated workflows. OpenAI's latest move therefore looks less like a routine adjustment and more like a repositioning of the GPT-5.6 series. Sol remains the premium option, Terra moves closer to competing pro-tier systems, and Luna becomes the company's direct answer to the industry's growing low-cost model segment.

OpenAI cuts prices on smaller models as businesses scrutinise AI spend

The ChatGPT maker lowered the cost of its smaller GPT-5.6 Luna model by 80% and its mid-tier Terra by 20%, while leaving the price of its biggest and flagship Sol model ⁠unchanged. OpenAI slashed prices of its low- and mid-tier AI models on Thursday, a move that may intensify competition in the industry as US companies battle cheaper Chinese rivals for customers increasingly wary of the technology's ballooning costs. The ChatGPT maker lowered the cost of its smaller GPT-5.6 Luna model by 80% and its mid-tier Terra by 20%, while leaving the price of its biggest and flagship Sol model ⁠unchanged. The ⁠cuts show that rising cost scrutiny by businesses facing hefty AI bills is forcing American labs to rethink pricing. Many tech CEOs have also said in recent months that cheaper AI options are key to the technology's widespread adoption. OpenAI's new pricing also turns up the heat on Anthropic, whose Claude models dominate enterprise and developer use but sit at the costlier end of the market. Both companies have been under pressure from open-source ⁠Chinese rivals such as Z.ai's GLM-5.2 that nearly match their performance at a lower cost. Analysts have said that cutting prices could boost usage of OpenAI's and Anthropic's ⁠technology, but strain their finances ahead of highly anticipated initial public offerings. While Thursday's cuts affect only OpenAI's smaller and mid-tier models, the company said it would still benefit businesses broadly as those models can now do work that recently required a top-tier system at far lower cost. The new pricing means businesses using OpenAI's technology will have to pay less for every million "tokens", or the units used to measure AI usage, they run through the models. Sending text to Luna drops to 20 cents per million tokens from $1 and Terra's to $2 from $2.50, while generating responses falls to $1.20 and $12 from $6 and $15, respectively. Anthropic's mid-tier Claude Sonnet 4.6 model, meanwhile, costs $3 per million input ⁠tokens and $15 per million output tokens, above the rates for Terra. OpenAI said the lower prices were partly enabled by efficiency gains from GPT-5.6, including the model's ability to improve code and optimize performance during internal development. Overall, prices of tokens have been falling in the past year, but the cost of completing a task is rising as AI firms shift from flat subscriptions to usage-based pricing. That is leaving companies with unpredictable and often higher bills as usage per task becomes harder to estimate.

OpenAI Goes After The Jugular Of China's Open-Weight AI Models, Cuts Token Prices By Up To 80%

Let the AI price wars begin. OpenAI has just fired a veritable volley across the bow of China's growing number of AI labs, sacrificing its sky-high margins to try to starve the budding open-weight AI economy. OpenAI is now trying to starve out China's AI labs by cutting token prices by as much as 80% on GPT-5.6 Luna OpenAI has just slashed the token-based pricing for GPT-5.6 Luna by 80 percent, with input tokens now priced at just $0.2 per 1 million from their earlier perch at $1, and output tokens priced at just $1.20 per 1 million vs. the earlier price of $6. With these pricing cuts, OpenAI's GPT-5.6 Luna now gives the biggest bang for your buck, eclipsing even the relative attractiveness of DeepSeek's V4 Pro model. Of course, this comes as China's open-weight models appear to be going in the opposite direction, with Moonshot having priced the Kimi K3 at $3 per 1 million of input tokens and a whopping $15 for every 1 million of output tokens. With around 3GW of dedicated inference-related compute running on NVIDIA's GPUs, OpenAI had quite a lot of room heretofore to implement these cuts. It also has around 2GW of training compute. In contrast, China's AI labs are probably running with just around 500MW of inference-related compute, that too made up of older NVIDIA GPUs as well as local ones from Huawei. Even so, one should never bet against China in a pricing war. And so, we now wait for China's response to OpenAI's aggressive gambit. Follow Wccftech on Google to get more of our news coverage in your feeds.

QUICK SPARK: OpenAI Cuts AI Model Prices as Businesses Push Back on Rising Costs

OpenAI is cutting prices on some of its artificial intelligence models as businesses grow increasingly cautious about rising AI expenses and competition intensifies across the industry. The ChatGPT maker lowered the cost of its smaller GPT-5.6 Luna model by 80% and reduced pricing for its mid-tier Terra model by 20%, while keeping its flagship Sol model unchanged, Reuters reported. OpenAI said efficiency improvements in its latest models helped enable the price cuts, allowing smaller systems to handle tasks that previously required more expensive, higher-capability models. The price cuts come as enterprises face growing uncertainty around AI expenses, with many moving away from flat subscription plans toward usage-based models that can lead to unpredictable bills as adoption increases. For investors, the pricing reset highlights the intensifying battle for AI market share. OpenAI is competing against Anthropic's Claude models, which have gained traction among enterprise customers, as well as lower-cost open-source models from Chinese AI developers challenging U.S. AI leaders on price and performance. While cheaper models could drive broader adoption and increase usage volumes, analysts warn the strategy could pressure margins for AI companies investing billions into infrastructure and computing capacity. This content was partially produced with the help of AI tools and was reviewed and published by Benzinga editors. Market News and Data brought to you by Benzinga APIs To add Benzinga News as your preferred source on Google, click here.

OpenAI Cuts Prices on Select Models to Make High-Volume Work Economical | PYMNTS.com

The company said in a Thursday blog post that it made these changes to improve the models' performance per dollar across enterprise workloads. Users can select the right model for the outcome they seek, balancing the stakes, cost of error, urgency and scale of each workflow, and the changes to GPT-5.6 provides them with more flexibility to optimize that calculation, according to the post. "The GPT-5.6 family expands the range of those choices," OpenAI said in the post. "Businesses can apply the maximum useful intelligence at every stage while paying the right price for the value it creates." OpenAI described GPT-5.6 Luna as its fastest and most affordable model, GPT-5.6 Terra as its balanced model for everyday work, and Sol as its frontier model. "We are building a resilient infrastructure portfolio and matching each workload to the systems best suited to run it," OpenAI said. "That approach supports both ends of the price-performance curve. At the lower-cost end, the new Luna and Terra prices make high-volume work economical at much greater scale. At the frontier end, Fast mode gives API customers faster access to Sol when response time is important." OpenAI announced July 8 that it was publicly launching the GPT-5.6 Sol, Terra and Luna models the following day after initially limiting their release at the request of the U.S. government. The company had said on June 26 that it previewed the models' capabilities as part of its ongoing engagement with the government. When OpenAI released the models on July 9, OpenAI CEO Sam Altman told CNBC that GPT-5.6 Sol was 54% more token efficient on agentic coding jobs and "as good or better" than competing models on the market. "Every enterprise now is thinking about spend and the value they're getting in exchange for AI, and this is what we really want to do," Altman said. The PYMNTS Intelligence report "New Data Shows How Tech Sectors Are Turning AI Into Strategy" found that when choosing to fund AI projects over the next 12 months, a majority of firms filter the technology through their unique definition of value. The report found that 60% of cybersecurity firms, 65% of software-as-a-service firms and 65% payments firms seek near-term financial results. For all PYMNTS AI coverage, subscribe to the daily AI Newsletter.

OpenAI sharply cuts prices for some AI models to accelerate adoption

OpenAI cut the price of its GPT-5.6 Luna model by 80% and its midtier Terra model by 20%, while keeping pricing for its top-end Sol model unchanged. Companies will now pay 20 cents per million input tokens for Luna, down from $1 previously, while the cost to generate responses falls from $6 to $1.20. For Terra, pricing drops to $2 per million input tokens and $12 for generated responses, versus $2.50 and $15 previously. The pricing revision reflects growing pressure from companies looking to keep AI spending under control, as well as competition from cheaper Chinese models. It also increases pressure on Anthropic, whose Claude models remain among the most expensive on the market. OpenAI says improvements in its models now allow tasks that were previously reserved for the most advanced systems to be performed at a significantly lower cost. The group said the price cuts were made possible by efficiency gains in GPT-5.6, notably in software development and the optimization of its own infrastructure. While the per-token cost continues to decline, overall corporate spending on AI is still trending higher, driven by a gradual shift to usage-based billing that makes costs more variable and harder to forecast.

OpenAI sharply cuts prices for some AI models to speed adoption

OpenAI has cut the price of its GPT-5.6 Luna model by 80% and its mid-tier Terra model by 20%, while keeping the price of its top-end Sol model unchanged. Companies will now pay 20 cents per million input tokens for Luna, down from $1 previously, while the cost to generate responses falls from $6 to $1.20. For Terra, prices are reduced to $2 per million input tokens and $12 for generated responses, versus $2.50 and $15 previously. This pricing overhaul reflects mounting pressure from companies looking to rein in their AI spending, as well as competition from cheaper Chinese models. It also increases pressure on Anthropic, whose Claude models remain among the most expensive in the market. OpenAI believes improvements in its models now make it possible to carry out tasks once reserved for the most advanced systems at a significantly lower cost. The group says these price cuts were made possible by efficiency gains in GPT-5.6, notably in software development and optimization of its own infrastructure. While the per-token cost continues to fall, overall corporate AI spending is still trending higher, driven by the gradual shift to usage-based billing, which makes costs more variable and harder to forecast.

OpenAI cuts prices on smaller models as businesses scrutinize AI spend

July 30 (Reuters) - OpenAI slashed prices of its low- and mid-tier AI models on Thursday, a move that may intensify competition in the industry as U.S. companies battle cheaper Chinese rivals for customers increasingly wary of the technology's ballooning costs. The ChatGPT maker lowered the cost of its smaller GPT-5.6 Luna model by 80% and its mid-tier Terra by 20%, while leaving the price of its biggest and flagship Sol model unchanged. The cuts show that rising cost scrutiny by businesses facing hefty AI bills is forcing American labs to rethink pricing. Many tech CEOs have also said in recent months that cheaper AI options are key to the technology's widespread adoption. OpenAI's new pricing also turns up the heat on Anthropic, whose Claude models dominate enterprise and developer use but sit at the costlier end of the market. Both companies have been under pressure from open-source Chinese rivals such as Z.ai's GLM-5.2 that nearly match their performance at a lower cost. Analysts have said that cutting prices could boost usage of OpenAI's and Anthropic's technology, but strain their finances ahead of highly anticipated initial public offerings. While Thursday's cuts affect only OpenAI's smaller and mid-tier models, the company said it would still benefit businesses broadly as those models can now do work that recently required a top-tier system at far lower cost. The new pricing means businesses using OpenAI's technology will have to pay less for every million "tokens", or the units used to measure AI usage, they run through the models. Sending text to Luna drops to 20 cents per million tokens from $1 and Terra's to $2 from $2.50, while generating responses falls to $1.20 and $12 from $6 and $15, respectively. Anthropic's mid-tier Claude Sonnet 4.6 model, meanwhile, costs $3 per million input tokens and $15 per million output tokens, above the rates for Terra. OpenAI said the lower prices were partly enabled by efficiency gains from GPT-5.6, including the model's ability to improve code and optimize performance during internal development. Overall, prices of tokens have been falling in the past year, but the cost of completing a task is rising as AI firms shift from flat subscriptions to usage-based pricing. That is leaving companies with unpredictable and often higher bills as usage per task becomes harder to estimate. (Reporting by Aditya Soni in Bengaluru and Deepa Seetharaman in San Francisco; Editing by Devika Syamnath)