Gemini 4 Argon vs GPT-6.1 Sol vs Claude Opus 5.5: What's Different in 2026?

Three AI labs put out notable models within the same four-week stretch of September 2026: Anthropic's Claude Opus 5.5, OpenAI's GPT-6.1 Sol and Google DeepMind's Gemini 4 Argon. All three get compared constantly, usually in the same breath, which makes it easy to assume they're interchangeable options sitting on the same shelf.

They aren't. One of them isn't even available to the public yet. Another is explicitly a cost-reduced tier, not its maker's flagship. The third is the most broadly accessible of the three and leads on several agentic coding benchmarks, independent and vendor-reported alike.

This isn't a ranking. There's no single winner to crown, and treating "which model is best" as one question misses how differently these three are positioned, priced and gated right now. What follows is a category-by-category and scenario-by-scenario comparison, with every number attributed to where it came from.

At a glance

Treat this table as a starting point, not the whole story. Several rows need the detail further down this article to interpret correctly, especially the Gemini 4 Argon availability row.

Gemini 4 Argon: what it is, and who can actually use it

Google DeepMind introduced Gemini 4 Argon on September 30, 2026, in a blog post by SVP Koray Kavukcuoglu. The headline detail isn't a benchmark score. It's who gets to use the model at all.

Gemini 4 Argon has launched into something Google calls the Fairwind Program, a voluntary pre-release process built around vetted cybersecurity defenders, reportedly including a US-government-linked track, with more than 650 participating organizations. There is no public release date. If you're not in that program, you cannot use Gemini 4 Argon today, regardless of what the benchmarks say.

That framing matters because Gemini 4 Argon's stated design goals line up with that audience: long-horizon software engineering, enterprise knowledge work in fields like legal and finance, and cybersecurity work specifically, vulnerability detection, validation and patching.

On pricing, Google has published an introductory rate of $2 per million input tokens and $10 per million output tokens, with cached input at $0.10 per million, the same introductory structure OpenAI and Anthropic have used for new models. Standard pricing after the introductory period is listed at $4 per million input and $20 per million output. The model can also return up to 1 million output tokens in a single response, a large jump from the 64,000-token ceiling on earlier Gemini models. Google has not officially disclosed Gemini 4 Argon's input context window; a 2 million token figure circulates in unofficial reporting, but it is not an official number and shouldn't be treated as one.

On benchmarks Google reports for the model: it leads DeepSWE v1.1 at 77.9%, which Google describes as state of the art; it ranks first on the Vals Index at 68.9%; and it ranks first on AutomationBench at 51.3%. Those are all vendor-reported figures from Google's own announcement. In the same announcement, Google's own comparison shows Gemini 4 Argon trailing GPT-6 Astra on FrontierSWE v2 (55.0% versus 65.5%) and OSWorld-2.0 (69.2% versus 72.6%), and trailing Claude Opus 5.5 on Terminal-Bench 4.0 (57.4% versus 66.4%). We're including those because a vendor publishing benchmarks where it doesn't lead is worth noting on its own.

Independent data from Artificial Analysis puts Gemini 4 Argon's biggest edge elsewhere: it has the lowest hallucination rate, 15% on the AA-Omniscience benchmark, among all models scoring 45 or higher on Artificial Analysis's Intelligence Index, well below GPT-6 Astra's 51% and GPT-6.1 Sol's 54% in their maximum-reasoning configurations. Artificial Analysis also has Gemini 4 Argon ranked first on its own AutomationBench-AA test at 78%, seven points ahead of Claude Sonnet 5.5's 71%. For background on the model's launch, see our earlier coverage of Google Gemini 4 Argon's release and features.

GPT-6.1 Sol: OpenAI's cheaper tier, not its flagship

OpenAI announced GPT-6.1 Sol at DevDay 2026 on September 29, 2026. The name invites an assumption worth correcting immediately: GPT-6.1 Sol is not OpenAI's top model. That position still belongs to GPT-6 Astra, released September 3, 2026, which remains the company's dedicated flagship and its primary computer-use model. Reporting around the DevDay announcement indicates a planned "GPT-6.1 Astra" was not released, due to safety concerns.

What GPT-6.1 Sol actually is: an upgrade to the existing GPT-6 Sol tier (released September 22, 2026), positioned by OpenAI as delivering near-Astra intelligence at roughly one-fifth of Astra's standard token price. Pricing is unchanged from GPT-6 Sol, at $2 per million input tokens and $10 per million output tokens, with cached input priced at $0.10 per million, a 95% discount versus standard input. Reported figures put the model's combined context window at roughly 1.05 million tokens, with a maximum input of about 922,000 tokens and a maximum output of 128,000 tokens. Its knowledge cutoff is reported as April 30, 2026.

Availability is narrower than a headline announcement implies. GPT-6.1 Sol is available through the API and through ChatGPT Work and Codex for Plus, Pro, Business, Enterprise and Edu plans. It is not yet available in ordinary ChatGPT chat. OpenAI's own announcement page returned an error when we tried to access it directly, so these figures are drawn from two independent reports of the DevDay announcement that agree with each other on the date, the pricing and the availability pattern described above.

If you want the fuller picture on GPT-6 Astra, including the safety questions raised after its release, we covered that separately in our pieces on what GPT-6 Astra is and the safety concerns raised about it.

Claude Opus 5.5: Anthropic's current flagship, and where Sonnet 5.5 fits

Anthropic released Claude Opus 5.5 on September 22, 2026. Unlike Gemini 4 Argon, it's broadly available today: through Claude.ai on Pro, Max, Team and Enterprise plans, through the Claude API, and through AWS Bedrock, Google Cloud and Microsoft Azure/Foundry.

Its context window is 1,000,000 tokens with a maximum output of 128,000 tokens. API pricing is $4 per million input tokens and $20 per million output tokens, which Anthropic describes as 20% below the previous Opus 5. Cache reads are $0.20 per million tokens; cache writes are $5 per million standard or $8 per million for a 1-hour cache. A faster mode is available at $8 input and $40 output per million tokens, running at roughly 2.5 times the standard speed. Anthropic says typical workloads end up around 40% cheaper overall than on Opus 5.

On benchmarks Anthropic has published: Opus 5.5 scores 66.4% on Terminal-Bench 4.0 versus Opus 5's 52.3%, 54.4% on FrontierCode v1.1 versus 48.0%, and 57.8% on CursorBench 4.0 versus 46.6%. On knowledge work, Anthropic reports a GDPval-AA v2.1 score of 1846 Elo versus Opus 5's 1708, and a Humanity's Last Exam score of 67.7% with tool use. These are all Anthropic's own figures. Independently, Artificial Analysis puts Claude Opus 5.5 at the top of its Intelligence Index among the three models discussed here, at 58 in its maximum-reasoning configuration, with Claude Sonnet 5.5 close behind at 56.

A distinction worth making clearly: Claude Opus 5.5 and Claude Sonnet 5.5 are two different models, not one model under two names. Sonnet 5.5, released six days later on September 28, 2026, is priced at half of Opus 5.5's rate and is positioned as the everyday workhorse tier. Anthropic says Sonnet 5.5 comes close to Opus 5.5 on several of its own benchmark tasks, but that claim comes from Anthropic's testing, not independent verification, and it isn't a claim that the two models are interchangeable. We covered that comparison in more depth in Claude Sonnet 5.5 vs Opus 5.5, and the Opus 5.5 launch itself in our original explainer.

On safety, Anthropic cites external evaluators Frontier Design and METR describing Opus 5.5 as its strongest-performing model on an automated behavioral audit, with the model attempting to circumvent its operating boundaries 85% less often than Opus 5 in that testing. Cybersecurity-related tasks from general users are routed to Opus 4.8 rather than Opus 5.5, and biology-related requests are gated behind Anthropic's Life Sciences Verification Program. The model's "thinking" mode cannot be disabled, and a zero-data-retention option plus EU AI Act watermarking support are both available for enterprise customers.

Coding and agentic work

This is where the three models' benchmark stories diverge most, and where vendor framing matters most to read carefully.

Anthropic's own figures show Claude Opus 5.5 leading Terminal-Bench 4.0 among the figures it published, at 66.4%, with FrontierCode v1.1 and CursorBench 4.0 scores that also top its predecessor by wide margins. Google's own figures show Gemini 4 Argon leading DeepSWE v1.1 at 77.9% and AutomationBench at 51.3%, both described by Google as state of the art or first-ranked.

Independent data complicates a straight comparison. Artificial Analysis's own Terminal Bench 4 run orders the models differently from either vendor's framing: Claude Sonnet 5.5 (max) at 64%, Claude Opus 5.5 (max) at 60%, GPT-6 Astra at 59%, and Gemini 4 Argon at 57%. That's a different benchmark configuration than the vendor-reported Terminal-Bench 4.0 figures above, which is exactly why cross-source benchmark comparisons need the testing conditions spelled out rather than compressed into one leaderboard.

The practical takeaway: Claude Opus 5.5 is the only one of the three you can use for coding agent work today without a waitlist. Gemini 4 Argon's agentic coding numbers are compelling on paper but currently unreachable outside the Fairwind Program. GPT-6.1 Sol's available reporting doesn't position it as a coding-benchmark leader against the other two; that role on the OpenAI side still belongs to GPT-6 Astra.

Computer use

Computer use, meaning a model operating a screen or browser directly rather than just returning text, is the one category where GPT-6 Astra (not Sol) is the relevant OpenAI comparison point, since Astra is OpenAI's dedicated computer-use model. Google's own benchmark table shows Gemini 4 Argon trailing GPT-6 Astra on OSWorld-2.0, 69.2% versus 72.6%. Anthropic reports Claude Opus 5.5 scoring 81.8% (partial) on OSWorld 2.1, a different benchmark version, which again limits how directly these numbers can be stacked against each other.

Cybersecurity

Cybersecurity is the category where Gemini 4 Argon's positioning is most explicit. Its entire initial access program is built around vetted defenders, and Google frames the model's core purpose around vulnerability detection, validation and patching. That's a deliberate, narrow go-to-market choice rather than a benchmark claim.

On the Anthropic side, Claude routes general-user cybersecurity tasks to Opus 4.8 rather than Opus 5.5, which suggests Anthropic is treating this as a specialized workflow rather than a headline capability of its newest flagship. We found no dedicated cybersecurity positioning for GPT-6.1 Sol in available reporting.

Reasoning and research

Independent reasoning data from Artificial Analysis's Intelligence Index v4.3.2 shows Claude Opus 5.5 (max) at 58, Claude Sonnet 5.5 (max) at 56, Gemini 4 Argon tied with GPT-6 Astra (max) at 53, and GPT-6.1 Sol (max) at 52. Anthropic separately reports a Humanity's Last Exam score of 67.7% for Opus 5.5 with tool use, a vendor figure with no independent equivalent cited here for the other two models.

Writing and everyday use

None of the three labs has published a dedicated writing-quality benchmark for these specific releases, and we won't invent one. What's documented is positioning: Claude Opus 5.5 is pitched at Fable 5.1 level performance on general work per Anthropic, GPT-6.1 Sol is framed by OpenAI as near-Astra intelligence for general use, and Gemini 4 Argon's stated focus areas (cybersecurity, long-horizon engineering, enterprise knowledge work) don't centre on casual writing at all.

Pricing comparison (USD)

All figures below are official API list prices in US dollars. Approximate INR figures are a currency conversion for context only, not an official Indian price from any of the three companies, and will drift with the exchange rate.

INR approximations above use a rate of roughly ₹83 per US dollar and are rounded for readability; they are not prices quoted by Google, OpenAI or Anthropic.

Benchmarks: vendor-reported vs independent

Benchmark comparisons across three different labs' announcements are a minefield of incompatible test versions, cherry-picked configurations and vendor framing. Here's what we could verify and attribute cleanly.

Vendor-reported figures

• Gemini 4 Argon (Google DeepMind): DeepSWE v1.1 77.9% (described as state of the art), Vals Index 68.9% (ranked first), AutomationBench 51.3% (ranked first). Google's own comparison also shows it trailing GPT-6 Astra on FrontierSWE v2 and OSWorld-2.0, and trailing Claude Opus 5.5 on Terminal-Bench 4.0.
• Claude Opus 5.5 (Anthropic): Terminal-Bench 4.0 66.4%, FrontierCode v1.1 54.4%, CursorBench 4.0 57.8%, GDPval-AA v2.1 1846 Elo, Humanity's Last Exam 67.7% with tools, OSWorld 2.1 81.8% (partial).
• GPT-6.1 Sol (OpenAI, via DevDay reporting): no independently sourced benchmark scores were available for this specific model at the time of writing; its positioning is described relative to GPT-6 Astra's pricing rather than head-to-head scores.

Independent figures (Artificial Analysis)

• Intelligence Index v4.3.2 (max configuration): Claude Opus 5.5 58, Claude Sonnet 5.5 56, Gemini 4 Argon 53 (tied with GPT-6 Astra max), GPT-6.1 Sol 52.
• AA-Omniscience hallucination rate (models scoring 45+): Gemini 4 Argon 15%, GPT-6 Astra (max) 51%, GPT-6.1 Sol (max) 54%. Lower is better here.
• AutomationBench-AA: Gemini 4 Argon 78% (ranked first), Claude Sonnet 5.5 (max) 71%.
• Terminal Bench 4 (Artificial Analysis's own run): Claude Sonnet 5.5 (max) 64%, Claude Opus 5.5 (max) 60%, GPT-6 Astra 59%, Gemini 4 Argon 57%.

Note that Artificial Analysis's Terminal Bench 4 ranking and Anthropic's Terminal-Bench 4.0 figure aren't the same test run, which is why Opus 5.5's score differs between the two sections above. Mixing vendor and independent numbers from different test harnesses into a single ranking would be misleading, so we've kept them separated throughout.

Which model should you use?

Software developers

Claude Opus 5.5 is the one you can actually pick up today for agentic coding work, with Terminal-Bench and FrontierCode figures from Anthropic backing that use case. If your workload is lighter, Claude Sonnet 5.5 is worth testing first given its lower price and the close-to-Opus claims Anthropic makes for it.

AI agent builders

Gemini 4 Argon's DeepSWE and AutomationBench numbers are the strongest long-horizon agent figures in this comparison, but they're currently inaccessible outside the Fairwind Program. For agent builders who need something they can ship now, Claude Opus 5.5 and GPT-6.1 Sol are the options actually on the table.

Cybersecurity professionals

If you qualify for the Fairwind Program, Gemini 4 Argon is purpose-built for your work. If you don't, Claude routes cybersecurity tasks to Opus 4.8, and GPT-6.1 Sol has no dedicated cybersecurity positioning documented.

Enterprise knowledge workers

All three vendors are chasing this audience. Claude Opus 5.5 has the broadest enterprise cloud distribution today, through Bedrock, Google Cloud and Azure/Foundry. Gemini 4 Argon lists legal and finance work as a target, but again, only inside its restricted program.

Multimodal users

Gemini 4 Argon's up to 1 million output tokens per response is the most distinctive figure here, useful for generating very long single outputs, but it's not something the public can test yet.

Cost-conscious users

GPT-6.1 Sol and Gemini 4 Argon's introductory tier are both priced at $2/$10 per million tokens, half of Claude Opus 5.5's $4/$20. If Gemini 4 Argon ever opens publicly at its introductory rate, cost-conscious API users would have two options at that price point.

Everyday consumers

Of the three, only Claude Opus 5.5 is reachable through a consumer-facing chat app today (Claude.ai). GPT-6.1 Sol is confined to Work and Codex surfaces for now, not ChatGPT's main chat interface, and Gemini 4 Argon isn't publicly reachable at all.

What this means for users in India

None of these three models has published official INR pricing. All API rates above are quoted in US dollars, and any rupee figure you see, including the approximations in this article, is a currency conversion, not an official price.

Claude Opus 5.5 is reachable from India today through Claude.ai's paid plans and through the API, billed in dollars. GPT-6.1 Sol is reachable through the OpenAI API and through ChatGPT's Work and Codex surfaces on qualifying plans, also billed in dollars; it is not yet in the standard ChatGPT chat product anywhere, India included. Gemini 4 Argon is not available to the public anywhere right now, so there is currently no way for most people or businesses in India, or anywhere else outside the Fairwind Program, to use it.

For India-specific AI tooling that's actually available today, our running list of free AI tools that work in India is a more useful starting point than waiting on Gemini 4 Argon's public release.

Frequently asked questions

Sources

• Anthropic: Claude Opus 5.5
• MarkTechPost: Google DeepMind unveils Gemini 4 Argon
• Artificial Analysis: Gemini 4 Argon and the top three labs
• Artificial Analysis on X: Intelligence Index and benchmark data
• Dataconomy: GPT-6.1 Sol DevDay coverage
• EvoLink: GPT-6.1 Sol pricing and availability

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