On April 23, 2026,\u00a0OpenAI\u00a0formally launched GPT-5.5, ending weeks of rumor and leak-driven speculation with a release that is both more concrete and more restrained than some of the hype suggested. The model is official, it is rolling out first in ChatGPT and Codex, and it is being positioned not as a broad consumer reinvention but as a stronger engine for coding, computer use, knowledge work, and research-heavy agent workflows.\u00a0(1)<\/p>\n\n\n\n
That positioning is the key to understanding the launch. GPT-5.5 arrives in the middle of a weekly frontier-model arms race:\u00a0Anthropic\u00a0shipped Claude Opus 4.7 on April 16, 2026,\u00a0Google\u00a0has Gemini 3.1 Pro in public preview, and OpenAI itself has been iterating rapidly through GPT-5.4 and specialized security offerings. Taken together, GPT-5.5 looks less like a single blockbuster reveal and more like OpenAI\u2019s clearest signal yet that the next battle is over who can complete real work most reliably, not who can post the prettiest benchmark chart.\u00a0(2)<\/p>\n\n\n\n
The confirmed facts are straightforward. OpenAI announced GPT-5.5 on April 23, 2026, alongside a system card and launch article. In public-facing materials, the company described the model as its \u201csmartest and most intuitive\u201d yet and emphasized sustained task execution rather than a flashy new interface. Media coverage indicates that OpenAI briefed reporters directly rather than staging a mass-market keynote, with\u00a0Greg Brockman\u00a0telling journalists that the model is notable for doing more with less guidance.\u00a0(1)<\/p>\n\n\n\n
The rollout is tiered. In ChatGPT, GPT-5.5 Thinking is available to Plus, Pro, Business, and Enterprise users; GPT-5.5 Pro is available to Pro, Business, and Enterprise users. In Codex, GPT-5.5 is available for Plus, Pro, Business, Enterprise, Edu, and Go plans. OpenAI\u2019s current pricing page also shows that Free and Go do not get GPT-5.5 Thinking inside ChatGPT, while Business and Enterprise get broader GPT-5.5 access plus enterprise controls.\u00a0(1)<\/p>\n\n\n\n
The API story is more cautious. OpenAI said GPT-5.5 and GPT-5.5 Pro are\u00a0not<\/strong>\u00a0launching to the API on day one because serving the model at scale requires additional safety and security work. The company says API access is coming \u201cvery soon,\u201d with list pricing of $5 per 1 million input tokens and $30 per 1 million output tokens for GPT-5.5, and $30 \/ $180 for GPT-5.5 Pro. Meanwhile,\u00a0Microsoft\u00a0said GPT-5.5 would become generally available in Microsoft Foundry the next day, underscoring how central enterprise distribution has become to frontier-model launches.\u00a0(3)<\/p>\n\n\n\n On geography, OpenAI did\u00a0not<\/strong>\u00a0publish a GPT-5.5-specific country map. The practical implication is that GPT-5.5 availability follows OpenAI\u2019s standing supported-country rules for ChatGPT and API services. That means the model is available only where those services are officially supported; the company does not publish a separate \u201cunsupported list,\u201d only the supported-country lists themselves. For a global audience, that matters because regional restrictions are policy-level rather than GPT-5.5-specific.\u00a0(4)<\/p>\n\n\n\n The pricing change that matters most is not a new ChatGPT sticker price but a new\u00a0model<\/strong>\u00a0price. OpenAI\u2019s own docs make clear that GPT-5.5 is priced above GPT-5.4 in the API, while the company argues that lower token usage can offset some of that increase in real workflows. The available public documentation did not pair the launch with a new consumer subscription-price announcement; the clearest consumer figure still publicly surfaced in Help Center materials is ChatGPT Plus at $20 per month.\u00a0(1)<\/p>\n\n\n\n One important correction to rumor-driven coverage: the official docs put GPT-5.5 at a\u00a01 million-token<\/strong>\u00a0context window for the API when it arrives, and\u00a0400K<\/strong>\u00a0inside Codex. We found no evidence in OpenAI\u2019s launch materials for viral claims of a 10 million-token GPT-5.5 context window. Publicly confirmed day-one ChatGPT access for Edu or Government plans was also not stated; what is confirmed is Codex access on Edu, while Government appears in broader Codex billing materials rather than the GPT-5.5 launch note itself.\u00a0(1)<\/p>\n\n\n\n The clearest upgrade is in long-horizon execution. OpenAI says GPT-5.5 matches GPT-5.4 on per-token latency in real-world serving while reasoning more effectively across larger contexts, using fewer tokens and fewer retries. The company also says GPT-5.5 was co-designed, trained, and served on\u00a0NVIDIA\u00a0GB200 and GB300 NVL72 systems, which reinforces the launch\u2019s subtext: this is as much an inference-efficiency story as a model-capability story.\u00a0(1)<\/p>\n\n\n\n In coding, the gains look material. OpenAI\u2019s flagship launch numbers show 82.7% on Terminal-Bench 2.0, 58.6% on SWE-Bench Pro, and 73.1% on its internal Expert-SWE evaluation, all above GPT-5.4. OpenAI\u2019s qualitative claim is that GPT-5.5 is better at holding context across large codebases, debugging ambiguous failures, checking assumptions with tools, and carrying changes through the surrounding system. That is exactly the profile developers care about in agentic coding: not just code generation, but persistence, state tracking, and verification.\u00a0(1)<\/p>\n\n\n\n The model also broadens OpenAI\u2019s \u201ccomputer-use\u201d story. On OSWorld-Verified, which measures autonomous operation of real computer environments, GPT-5.5 reached 78.7%. On MMMU Pro it scored 81.2% without tools and 83.2% with tools, suggesting stronger visual reasoning when it can combine perception with action. OpenAI pairs those numbers with a broader claim that GPT-5.5 feels closer to software that can \u201cuse the computer with you\u201d: see the screen, click, type, navigate, and validate. In practical terms, that matters far more for enterprise automation than marginal gains on generic trivia benchmarks.\u00a0(1)<\/p>\n\n\n\n The knowledge-work angle is just as important. GPT-5.5 scored 84.9% on GDPval, 60.0% on FinanceAgent v1.1, 88.5% on internal investment-banking modeling tasks, 54.1% on OfficeQA Pro, and 98.0% on Tau2-bench Telecom without prompt tuning. OpenAI says it is already using related workflows internally for communication triage, large tax-form review, and automated business reporting. Whether or not one accepts the company\u2019s marketing language, those examples reveal the intended buyer: finance teams, support operations, legal workflows, research groups, and software organizations trying to use agents as labor multipliers.\u00a0(1)<\/p>\n\n\n\n Long context improved substantially versus GPT-5.4, but the story is mixed rather than absolute. In OpenAI\u2019s own Graphwalks tests, GPT-5.5 improved sharply over GPT-5.4 at both 256K and 1M settings. But one 1M \u201cparents\u201d variant still trails Claude Opus 4.6\u2019s published score by a significant margin. That is a good reminder that \u201c1 million context\u201d is not one capability but many: retrieval, compression, attention stability, and multi-hop reasoning can all behave differently inside the same nominal window.\u00a0(1)<\/p>\n\n\n\n Notably, OpenAI did\u00a0not<\/strong>\u00a0make memory or personalization the headline of the launch. Those remain product-level ChatGPT features attached to plans, not the defining technical theme of GPT-5.5. The model is being sold first and foremost as a workflow engine. That is an inference from the release materials, but it is a strong one: almost every prominent example and benchmark on the launch page focuses on coding, documents, tools, computer use, or scientific work.\u00a0(1)<\/p>\n\n\n\n Safety is where the launch becomes more nuanced. OpenAI says GPT-5.5 underwent full pre-deployment evaluations, targeted red-teaming for advanced biology and cybersecurity capabilities, and feedback from nearly 200 early-access partners. The system card says the company is releasing GPT-5.5 with its \u201cstrongest set of safeguards to date.\u201d But the same document also says GPT-5.5 is a step up in cyber capability, remains \u201cHigh\u201d in bio and cyber risk categories, and in some internal resampling work showed slightly more low-severity misaligned agent behavior than GPT-5.4 Thinking. That is not a contradiction. It is the emerging pattern of frontier AI in 2026: useful models are becoming more capable and more operationally risky at the same time.\u00a0(5)<\/p>\n\n\n\n OpenAI\u2019s benchmark strategy for GPT-5.5 is revealing in itself. The company leaned heavily on workflow-centric evaluations such as Terminal-Bench, GDPval, OSWorld, BrowseComp, Toolathlon, and FinanceAgent rather than classic classroom-style staples like MMLU or HumanEval. GPQA Diamond and MMMU Pro are present; MMLU and HumanEval are not prominent in the launch materials. That suggests OpenAI increasingly believes buyers care more about \u201ccan it finish the task?\u201d than about leaderboard familiarity.\u00a0(1)<\/p>\n\n\n\n In coding and agentic execution, GPT-5.5\u2019s official results are strong. Terminal-Bench 2.0 at 82.7% is clearly ahead of GPT-5.4\u2019s 75.1% and ahead of OpenAI\u2019s published comparator scores for Claude Opus 4.7 and Gemini 3.1 Pro. GDPval at 84.9% also beats GPT-5.4 and both named frontier competitors in OpenAI\u2019s chart, which matters because GDPval is designed around realistic work products across 44 occupations rather than single-answer tests. In plain English, the benchmark picture says GPT-5.5 is especially good at turning fuzzy instructions into completed, tool-verified deliverables.\u00a0(1)<\/p>\n\n\n\n Where the launch looks less like a rout is in pure academic and browsing-style tests. On GPQA Diamond, the leading models are clustered very tightly in the mid-90s, which means GPT-5.5 is competitive but not obviously dominant. On Humanity\u2019s Last Exam without tools, OpenAI\u2019s own table shows Claude Opus 4.7 ahead; with tools, GPT-5.5 is only roughly at parity. On BrowseComp, Gemini 3.1 Pro is higher than GPT-5.5 in OpenAI\u2019s own comparison. The practical lesson is clear: GPT-5.5\u2019s strongest case is not \u201cbest at everything,\u201d but \u201cparticularly good at sustained execution-heavy work.\u201d\u00a0(1)<\/p>\n\n\n\n The scientific-reasoning story is better than the academic one. OpenAI published gains on GeneBench, BixBench, and FrontierMath, and it highlighted a Ramsey-number proof result from an internal GPT-5.5-based research harness. That is still a mix of benchmark evidence and internal anecdote, not independent replication. But it does suggest that OpenAI is now comfortable marketing \u201cco-scientist\u201d workflows, especially in biology and quantitative analysis, rather than reserving those claims for future roadmap slides.\u00a0(1)<\/p>\n\n\n\n Third-party evaluation adds useful texture.\u00a0Artificial Analysis\u00a0says GPT-5.5 now tops its Intelligence Index by three points and that a medium-effort GPT-5.5 run can match Claude Opus 4.7 max-effort performance at much lower cost. But the same firm also reports a high hallucination rate on its Omniscience benchmark: GPT-5.5 has the highest factual recall in that test, yet still hallucinates more than Claude Opus 4.7 or Gemini 3.1 Pro by that benchmark\u2019s definition. This does\u00a0not<\/strong>\u00a0mean \u201c86% of GPT-5.5 outputs are false.\u201d It means that on one private retrieval-heavy benchmark, GPT-5.5 still inserts unsupported content too often relative to the leaders.\u00a0(6)<\/p>\n\n\n\n Partner previews point in the same general direction, with obvious caveats.\u00a0CodeRabbit\u00a0says early internal testing shows better issue-finding, better precision, and stronger signal in code review and debugging workflows.\u00a0Harvey\u00a0says GPT-5.5 improved its BigLaw Bench score from 91.0% on GPT-5.4 to 91.7% in research preview testing. These are useful data points for software and legal buyers, but they are still early-access, vendor-specific evaluations rather than full neutral public bake-offs.\u00a0(7)<\/p>\n\n\n\n The biggest benchmark caveat is that OpenAI itself flags contamination and setup issues. On SWE-Bench Pro, the launch page explicitly notes that labs have reported evidence of memorization on that evaluation. It also notes that some GPT-5.5 results were run at xhigh reasoning effort in a research environment that may differ from production ChatGPT behavior. In short, the benchmark sheet is informative, but it is not a substitute for testing your own workload. That warning has become standard in 2026 for a reason.\u00a0(1)<\/p>\n\n\n\n Launch-day coverage from\u00a0The Verge,\u00a0Axios, and\u00a0TechCrunch\u00a0converged on the same basic frame: GPT-5.5 is a serious technical upgrade, especially for coding and autonomous work, but it is also one more move in a brutally compressed competition cycle where product differentiation is getting harder to explain to ordinary users. That is why the most repeated phrase in coverage was not \u201cAGI\u201d or \u201cmultimodal revolution,\u201d but Brockman\u2019s description of a model that needs less guidance and feels more intuitive in agentic work.\u00a0(8)<\/p>\n\n\n\n Independent expert reaction was more favorable than cynical, but not uncritical.\u00a0Simon Willison, who had preview access, called GPT-5.5 fast, effective, and highly capable, while also drawing attention to the API price jump and suggesting GPT-5.4 may remain the saner default for many developers. That is a recurring theme across launch-day analysis: GPT-5.5 looks genuinely better, but the economic question is whether it is enough better to justify a 2x list-price increase over GPT-5.4.\u00a0(9)<\/p>\n\n\n\n Broader strategic commentary remains unsettled.\u00a0Benedict Evans\u00a0argued even before this launch that OpenAI\u2019s challenge is not merely to maintain technical leadership, but to hold an advantage in a market where competitors increasingly match the core model layer and differentiation shifts to distribution, product design, and economics. GPT-5.5 strengthens OpenAI\u2019s position in that fight, but it does not make the underlying strategic problem disappear. In that sense, the release supports Evans\u2019s thesis rather than disproving it.\u00a0(10)<\/p>\n\n\n\n The community response across forums was split from the first hour. On the positive side, developers on Hacker News and in the OpenAI ecosystem were immediately interested in token efficiency, rollout timing, and Codex access \u2014 all signs that they see GPT-5.5 as a working tool, not just a benchmark object. On the negative side, Reddit threads quickly filled with complaints that the jump looked incremental relative to hype, that Anthropic\u2019s recent launches still felt more dramatic, or that higher prices would eat the gains. One OpenAI community commenter bluntly argued that API-linked pricing means ChatGPT-bought Codex credits now go \u201chalf as far.\u201d These are anecdotal reactions, not a scientific sample, but they illustrate the release\u2019s core tension: more capability, less obvious emotional wow-factor, and more scrutiny on cost.\u00a0(11)<\/p>\n\n\n\n A final note on rumor versus fact: pre-launch chatter around a codename, \u201cSpud,\u201d was partly echoed in launch-day reporting, but OpenAI\u2019s own public materials did not use that codename. Likewise, some viral posts inflated the context window or described sweeping hallucination collapses that do not appear in official documentation. The safe reading is simple: GPT-5.5 is confirmed, strong, and material; many of the grander claims attached to it online remain either marketing rhetoric or unsupported speculation.\u00a0(12)<\/p>\n\n\n\n OpenAI\u2019s own published comparison makes GPT-5.5 look strongest against Claude Opus 4.7 and Gemini 3.1 Pro in coding, office-style task completion, and some computer-use scenarios. But the same official tables also show that Gemini still has an edge in some tool-use browsing tests, Claude remains very competitive in long-context and \u201chard question\u201d performance, and the pure academic gap at the frontier is often narrow enough that pricing and workflow fit matter more than who wins by one point. <\/p>\n\n\n\n The most important competitive conclusion is that GPT-5.5 strengthens OpenAI against\u00a0Artifical Analysis-style \u201cwho is best overall?\u201d debates while doing even more for OpenAI\u2019s sales story. Against best-in-class closed rivals, GPT-5.5 is now easier to sell as a premium execution model. Against\u00a0Meta\u00a0and\u00a0Mistral AI, the argument is different: OpenAI is selling outcome quality and managed enterprise controls, while the open or lower-cost challengers are selling deployability and economics. Against\u00a0xAI, the comparison is still harder because xAI\u2019s public docs are thinner on crawlable detail, but OpenAI currently offers the clearer public story around enterprise workflows, safety process, and broad product integration.\u00a0(6)<\/p>\n\n\n\n For software development, GPT-5.5 looks consequential. OpenAI\u2019s official coding gains, CodeRabbit\u2019s early review data, and Simon Willison\u2019s preview impressions all point in the same direction: the model is not just \u201csmarter,\u201d but more useful in the loops developers actually care about \u2014 planning, verifying, debugging, and keeping scope under control. That makes GPT-5.5 more important for IDEs, repo agents, CI workflows, and code review than for casual chatbot use.\u00a0(1)<\/p>\n\n\n\n For business adoption, the story is broader than coding. GDPval, spreadsheet-modeling scores, OfficeQA, and Tau2-bench Telecom all support OpenAI\u2019s claim that GPT-5.5 is now squarely aimed at customer support, finance, operations, legal analysis, and document-heavy work. The addition of enterprise controls on Business and Enterprise plans \u2014 SAML SSO, MFA, encryption, no training on business data by default, and data residency in ten regions \u2014 makes the launch less about a novel model and more about a broader bid to become the default workplace AI substrate.\u00a0(1)<\/p>\n\n\n\n For education, the launch is more mixed. GPT-5.5 Pro is described by OpenAI testers as notably useful in education, and Edu is confirmed for Codex access, but OpenAI did not publish a dedicated GPT-5.5 education package or a multilingual performance breakout at launch. That matters for universities and international buyers, because there is still a gap between \u201cthe model is better\u201d and \u201cthe model is demonstrably better across non-English academic tasks.\u201d As of this launch, that evidence is incomplete.\u00a0(1)<\/p>\n\n\n\n For global markets, the immediate regional takeaway is operational rather than cultural. GPT-5.5 availability follows OpenAI\u2019s supported-country structure, which includes\u00a0Japan, the\u00a0United States, and much of\u00a0Europe\u00a0where OpenAI already operates. We did\u00a0not<\/strong>\u00a0find a GPT-5.5-specific regional carve-out in the official launch materials. But for multinational procurement teams across\u00a0Asia\u00a0and Europe, the more important issue may be what was\u00a0not<\/strong>\u00a0disclosed: no multilingual benchmark table, no country-by-country feature matrix, and no day-one API availability.\u00a0(4)<\/p>\n\n\n\n Over the next six to twelve months, GPT-5.5 is likely to matter less as a \u201cnew chatbot\u201d and more as a catalyst for three market shifts. First, it will intensify the fight over premium coding and agentic enterprise work, where Anthropic and Google remain very close competitors. Second, it will push more customers to compare\u00a0cost per completed workflow<\/strong>, not cost per token \u2014 a framing OpenAI is clearly trying to normalize. Third, it increases pressure on the rest of the market to publish workflow-heavy benchmarks and better safety evidence, because GPT-5.5\u2019s real claim is not that it speaks more elegantly, but that it finishes harder tasks more reliably.\u00a0(8)<\/p>\n\n\n\n The likely competitive responses are already visible. Anthropic can be expected to lean harder into Claude Code, enterprise coding credibility, and safety narratives. Google\u2019s strongest answer remains price-performance plus search and workspace integration. Meta and Mistral will keep pressing the open-weight and low-cost angle. Microsoft\u2019s next-day Foundry availability suggests OpenAI will continue to rely heavily on enterprise distribution. And OpenAI itself appears to be threading a narrower path: ship faster, make the models more agentic, but hold back API release until safety and operational controls catch up.\u00a0(2)<\/p>\n\n\n\n For consumers, the verdict is modest but positive: GPT-5.5 is a real upgrade, but most people will only feel it on harder tasks, and only paid users get the main ChatGPT benefits today. For businesses, the verdict is stronger: this is the clearest OpenAI release yet for spreadsheets, documents, support workflows, computer use, and enterprise agents. For developers, the verdict is the strongest of all: GPT-5.5 looks like a serious new top-tier option \u2014 but not one that removes the need to test against Claude and Gemini on your own real workload, tooling stack, and budget.\u00a0(20)<\/p>\n\n\n\n <\/p>\n","protected":false},"excerpt":{"rendered":" On April 23, 2026,\u00a0OpenAI\u00a0formally launched GPT-5.5, ending weeks of rumor and leak-driven speculation with a release that is both more concrete and more restrained than some of the hype suggested. The model is official, it is rolling out first in…<\/p>\n","protected":false},"author":4,"featured_media":1998,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[15,17,3],"tags":[],"class_list":["post-1997","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-agent","category-company","category-llm"],"_links":{"self":[{"href":"https:\/\/www.aicritique.org\/us\/wp-json\/wp\/v2\/posts\/1997","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.aicritique.org\/us\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.aicritique.org\/us\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.aicritique.org\/us\/wp-json\/wp\/v2\/users\/4"}],"replies":[{"embeddable":true,"href":"https:\/\/www.aicritique.org\/us\/wp-json\/wp\/v2\/comments?post=1997"}],"version-history":[{"count":2,"href":"https:\/\/www.aicritique.org\/us\/wp-json\/wp\/v2\/posts\/1997\/revisions"}],"predecessor-version":[{"id":2000,"href":"https:\/\/www.aicritique.org\/us\/wp-json\/wp\/v2\/posts\/1997\/revisions\/2000"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.aicritique.org\/us\/wp-json\/wp\/v2\/media\/1998"}],"wp:attachment":[{"href":"https:\/\/www.aicritique.org\/us\/wp-json\/wp\/v2\/media?parent=1997"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.aicritique.org\/us\/wp-json\/wp\/v2\/categories?post=1997"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.aicritique.org\/us\/wp-json\/wp\/v2\/tags?post=1997"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}What Actually Changed<\/h2>\n\n\n\n
How Good the Benchmarks Really Look<\/h2>\n\n\n\n
How Media and Experts Read the Launch<\/h2>\n\n\n\n
Where GPT-5.5 Sits Against Rivals<\/h2>\n\n\n\n
Model<\/th> What it is<\/th> Context \/ deployment posture<\/th> Pricing \/ economics signal<\/th> Competitive read<\/th> Source basis<\/th><\/tr><\/thead> GPT-5.5<\/td> OpenAI\u2019s new frontier \u201creal work\u201d model<\/td> 1M context in the API when released; 400K in Codex; ChatGPT + Codex first, API later<\/td> $5 \/ 1M input and $30 \/ 1M output; Pro at $30 \/ $180<\/td> Best official OpenAI showing in coding, GDPval, and OSWorld; still not a universal winner<\/td> (1)<\/td><\/tr> GPT-5.4<\/td> Previous OpenAI frontier model for professional work<\/td> 1M context; already in ChatGPT, API, and Codex<\/td> $2.5 \/ 1M input and $15 \/ 1M output<\/td> Cheaper and still strong; likely to remain attractive for cost-sensitive API work<\/td> (13)<\/td><\/tr> GPT-5<\/td> OpenAI\u2019s August 2025 flagship<\/td> Unified reasoning\/speed system in ChatGPT<\/td> Product-first positioning rather than this launch\u2019s explicit workflow benchmarks<\/td> Big consumer milestone; GPT-5.5 is the more enterprise-agentic refinement<\/td> (14)<\/td><\/tr> GPT-4.1<\/td> OpenAI\u2019s API-focused 2025 model family<\/td> 1M context; API only<\/td> Lower-cost, efficient API family<\/td> Still relevant for API builders; much less agentically ambitious than GPT-5.5<\/td> (15)<\/td><\/tr> Claude Opus 4.7<\/td> Anthropic\u2019s current top flagship<\/td> Broad product and API availability<\/td> $5 \/ 1M input and $25 \/ 1M output<\/td> Often comparable or better on some long-context and hard-reasoning tasks; still a top coding rival<\/td> (2)<\/td><\/tr> Gemini 3.1 Pro<\/td> Google\u2019s advanced reasoning model in public preview<\/td> 1M context; Vertex AI \/ Gemini ecosystem<\/td> $2 \/ 1M input and $12 \/ 1M output up to 200K input<\/td> Likely the strongest price-performance pressure on GPT-5.5 among closed frontier models<\/td> (16)<\/td><\/tr> Llama 4 Maverick<\/td> Meta\u2019s leading open-weight Llama 4 release<\/td> 10M context; open deployment story<\/td> Meta estimates roughly $0.19\u2013$0.49 per 1M tokens<\/td> Far cheaper and open-weight, but not in the same top closed-model tier for frontier agentic work<\/td> (17)<\/td><\/tr> Grok 4.20<\/td> xAI\u2019s current flagship chat\/coding model<\/td> Marketed as xAI\u2019s fastest and most intelligent model<\/td> Public static docs in our crawl did not clearly surface token prices<\/td> Strong ecosystem push, but thinner public benchmarking and governance evidence than OpenAI\/Anthropic\/Google<\/td> (18)<\/td><\/tr> Mistral Small 4<\/td> Mistral\u2019s low-cost hybrid reasoning\/coding model<\/td> 256K context<\/td> $0.15 \/ 1M input and $0.60 \/ 1M output<\/td> Not a GPT-5.5 substitute at the frontier, but a major economic threat in production workflows<\/td> (19)<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n What It Means for Markets and What Comes Next<\/h2>\n\n\n\n
Sources<\/h2>\n\n\n\n
\n
https:\/\/openai.com\/index\/introducing-gpt-5-5\/<\/code>\u00a0(1)<\/li>\n\n\n\nhttps:\/\/openai.com\/index\/gpt-5-5-system-card\/<\/code>\u00a0and\u00a0https:\/\/deploymentsafety.openai.com\/gpt-5-5<\/code>\u00a0(5)<\/li>\n\n\n\nhttps:\/\/help.openai.com\/en\/articles\/11909943-gpt-53-and-gpt-54-in-chatgpt<\/code>\u00a0<\/li>\n\n\n\nhttps:\/\/chatgpt.com\/pricing\/<\/code>\u00a0(20)<\/li>\n\n\n\nhttps:\/\/help.openai.com\/en\/articles\/6950777-what-is-chatgpt-plus<\/code>,\u00a0https:\/\/help.openai.com\/en\/articles\/7947663-chatgpt-supported-countries<\/code>,\u00a0https:\/\/help.openai.com\/en\/articles\/5347006-openai-api-supported-countries-and-territories<\/code>\u00a0(21)<\/li>\n\n\n\nhttps:\/\/openai.com\/index\/introducing-gpt-5-4\/<\/code>,\u00a0https:\/\/openai.com\/index\/introducing-gpt-5\/<\/code>,\u00a0https:\/\/openai.com\/index\/gpt-4-1\/<\/code>\u00a0(13)<\/li>\n\n\n\nhttps:\/\/azure.microsoft.com\/en-us\/blog\/openais-gpt-5-5-in-microsoft-foundry-frontier-intelligence-on-an-enterprise-ready-platform\/<\/code>\u00a0(22)<\/li>\n\n\n\nhttps:\/\/www.anthropic.com\/news\/claude-opus-4-7<\/code>,\u00a0https:\/\/platform.claude.com\/docs\/en\/about-claude\/pricing<\/code>\u00a0(2)<\/li>\n\n\n\nhttps:\/\/docs.cloud.google.com\/vertex-ai\/generative-ai\/docs\/models\/gemini\/3-1-pro<\/code>,\u00a0https:\/\/cloud.google.com\/gemini-enterprise-agent-platform\/generative-ai\/pricing<\/code>\u00a0(16)<\/li>\n\n\n\nhttps:\/\/www.llama.com\/<\/code>\u00a0(17)<\/li>\n\n\n\nhttps:\/\/docs.x.ai\/developers\/models<\/code>\u00a0(18)<\/li>\n\n\n\nhttps:\/\/docs.mistral.ai\/models\/model-cards\/mistral-small-4-0-26-03<\/code>\u00a0(19)<\/li>\n\n\n\nhttps:\/\/artificialanalysis.ai\/articles\/openai-gpt5-5-is-the-new-leading-AI-model<\/code>\u00a0(6)<\/li>\n\n\n\nhttps:\/\/www.coderabbit.ai\/blog\/gpt-5-5-benchmark-results<\/code>\u00a0(7)<\/li>\n\n\n\nhttps:\/\/www.harvey.ai\/blog\/gpt-5-5-research-preview-results<\/code>\u00a0(23)<\/li>\n\n\n\nhttps:\/\/simonwillison.net\/tags\/llm-reasoning\/<\/code>\u00a0and\u00a0https:\/\/simonw.substack.com\/p\/gpt-55-chatgpt-images-20-qwen36-27b<\/code>\u00a0(9)<\/li>\n\n\n\nhttps:\/\/www.theverge.com\/ai-artificial-intelligence\/917612\/openai-gpt-5-5-chatgpt<\/code>,\u00a0https:\/\/www.axios.com\/2026\/04\/23\/openai-releases-spud-gpt-model<\/code>,\u00a0https:\/\/techcrunch.com\/2026\/04\/23\/openai-chatgpt-gpt-5-5-ai-model-superapp\/<\/code>\u00a0(8)<\/li>\n\n\n\nhttps:\/\/www.ben-evans.com\/benedictevans\/2026\/2\/19\/how-will-openai-compete-nkg2x<\/code>\u00a0(10)<\/li>\n<\/ul>\n\n\n\n