Three new frontier AI models shipped inside a single month, and they can’t agree on who’s in charge. Google’s Gemini 4 Argon went fully public October 13. OpenAI’s GPT-6.1 Sol arrived the same day as Opus 5.5 but stayed boxed into ChatGPT Work and Codex rather than ordinary Chat. By October 21, 2026, independent leaderboards were already contradicting each other about which one leads, and the gaps between their scores are small enough that the lead flips depending on which benchmark you trust.
This llm leaderboard snapshot pulls together official pricing, release notes, and multiple third-party benchmark rankings to show where Claude Opus 5.5, GPT-6.1 Sol, and Gemini 4 Argon actually stand against each other, not just what each company’s own press release claims. The short version: no single leaderboard crowns an outright champion, the three models are priced within a few dollars of each other per million tokens, and the right pick depends heavily on whether you’re optimizing for raw coding accuracy, output volume, or cost per task.
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What Changed: Claude Opus 5.5, GPT-6.1 Sol, and Gemini 4 Argon in Plain English
Before comparing numbers, it helps to know what each release actually is, because none of these three are simple “next version” bumps.
Claude Opus 5.5: Anthropic’s efficiency-focused flagship refresh
Anthropic describes Claude Opus 5.5 as the first model in its new Claude 5.5 family, and the company’s own release notes say it performs at the level of Claude Fable 5.1 on most work while costing 40% less to run than Opus 5. That’s an important distinction: Fable 5.1 is a separate, comparably strong Anthropic model, not an older version Opus 5.5 simply replaced. Opus 5.5 carries the API identifier claude-opus-5-5, launched at $4 per million input tokens and $20 per million output tokens, undercutting Opus 5’s $5/$25 rate by 20% on raw token price and by 40% on typical workload cost once Anthropic’s efficiency gains are factored in. Fast mode has been available in Claude Code and on the Claude Platform since Opus 5.5’s September 22, 2026 launch, offering roughly 2.5x speed for $8 per million input tokens and $40 per million output tokens, according to Claude’s own release notes. Opus 5.5 ships to Claude Pro, Max, Team, and Enterprise users, plus Amazon Web Services, Google Cloud, and Microsoft Azure.
GPT-6.1 Sol: OpenAI’s cheaper near-Astra tier, not the outright flagship
GPT-6.1 Sol is easy to misread as OpenAI’s top model. It isn’t. That title still belongs to GPT-6 Astra. GPT-6.1 Sol is positioned as an upgrade to GPT-6 Sol, delivering what OpenAI calls “near-Astra intelligence” for agentic coding, computer use, and professional work at roughly one-fifth of Astra’s standard API token price. It launched September 22, 2026, under the API model name gpt-6.1-sol, priced at $2 per million input tokens, $0.10 per million cached input tokens, and $10 per million output tokens. OpenAI’s own documentation is explicit that, at launch, GPT-6.1 Sol was available to Plus, Pro, Business, Enterprise, and Edu users inside ChatGPT Work and Codex, but was not yet offered in ordinary ChatGPT Chat. OpenAI’s October DevDay recap continued describing it the same way: a model option for Work and Codex workflows, separate from the GPT-6, GPT-5.6, and GPT-6 Pro models available in regular Chat.
Gemini 4 Argon: Google’s security-first model that went fully public
Gemini 4 Argon had an unusual rollout. Google first announced it on October 1, 2026, through the Fairwind Program, a limited release aimed at trusted cybersecurity defenders rather than the general public, as The Verge reported at the time. Broad commercial availability followed on October 13, 2026, opening Argon up across the Gemini API, Google AI Studio, the Gemini platform, Gemini for business, Google Antigravity, the Gemini app, and AI Mode in Search. Google says Argon’s maximum output jumped from 64,000 tokens to 1 million tokens, the largest single-response ceiling of the three models covered here. Introductory API pricing runs $2 per million input tokens and $10 per million output tokens through November 30, 2026, with cached input tokens discounted 95%. After that date, Google has already confirmed the standard rate doubles to $4 input and $20 output per million tokens.
Google also expanded the Fairwind program to additional trusted cyber defenders at the same time Argon went broadly available, a detail worth remembering if your organization does security work and wants early access to future Gemini releases.
Why Three Frontier Labs Shipped New Models in the Same Month
It’s not a coincidence that Anthropic, OpenAI, and Google all pushed major releases within a three-week window of each other in September and October 2026. Each company’s own documentation frames its release as closing a specific gap against the others, which tells you almost as much about the competitive dynamics as the benchmark scores do. Anthropic frames Opus 5.5 primarily as a cost play: the headline claim isn’t “smarter,” it’s “40% less to run than Opus 5” and “a fifth of the cost per task” on FrontierCode relative to GPT-6 Astra. OpenAI frames GPT-6.1 Sol the same way, as “near-Astra intelligence… at one-fifth of Astra’s standard API input and output token prices.” Google frames Gemini 4 Argon differently, leading with the 1-million-token output jump and a Vals Index ranking claim rather than a cost argument, which fits a company trying to win on raw capability rather than compete purely on price.
That pattern matters for buyers. Two of the three companies are explicitly positioning their newest release as a cheaper way to get flagship-adjacent performance rather than a new performance ceiling. Only Gemini 4 Argon is being marketed by its maker as an outright capability upgrade over the model it replaced. If you’re choosing based on “which lab is trying hardest to win on price,” the answer is Anthropic and OpenAI; if you’re choosing based on “which lab says it moved the ceiling,” that’s Google’s pitch with Argon.
Full Specs Comparison: Claude Opus 5.5 vs GPT-6.1 Sol vs Gemini 4 Argon
Here’s how the three models stack up on the specifications each company has actually confirmed, pulled from official pricing pages and release notes rather than marketing copy.
| Spec | Claude Opus 5.5 | GPT-6.1 Sol | Gemini 4 Argon |
|---|---|---|---|
| Developer | Anthropic | OpenAI | |
| Release date | September 22, 2026 | September 22, 2026 | October 13, 2026 (global) |
| Predecessor | Claude Opus 5 | GPT-6 Sol | Gemini 3 generation |
| Flagship tier? | Yes, Anthropic’s top model | No, GPT-6 Astra remains the flagship | Yes, Google’s current frontier model |
| API model identifier | claude-opus-5-5 | gpt-6.1-sol | gemini-4-argon |
| Standard input price (per 1M tokens) | $4 | $2 | $2 (through Nov 30, 2026) |
| Standard output price (per 1M tokens) | $20 | $10 | $10 (through Nov 30, 2026) |
| Cached input price | $0.20/M (cache read) | $0.10/M | 95% off standard input price |
| Fast/turbo variant | Fast mode: $8/$40 per M, ~2.5x speed | Ultrafast (Pro 500 tier only) | Not offered |
| Max output tokens | Not separately published | Not separately published | 1,000,000 (up from 64,000) |
| Primary chat access | Claude Pro, Max, Team, Enterprise | ChatGPT Work and Codex only (not Chat) | Gemini app, AI Mode in Search (AI Pro/Ultra) |
| Cloud platform availability | AWS, Google Cloud, Microsoft Azure | OpenAI API, ChatGPT plans | Google Cloud, Antigravity, AI Studio |
| Status as of Oct 21, 2026 | Active, current flagship | Active, mid-tier release | Active, globally available |
The pricing columns alone explain a lot of the leaderboard confusion you’ll see below: GPT-6.1 Sol and Gemini 4 Argon’s introductory rate both start at $2 input/$10 output, while Claude Opus 5.5 launched at twice that price. Whether that premium is justified depends entirely on which benchmark you’re reading.
How the Leaderboards Disagree: BenchLeader, LiveBench, and TensorFeed Compared
This is where the “llm leaderboard” search intent gets messy, because the independent rankings genuinely do not agree with each other. None of these third-party scores are confirmed by the model-makers themselves, so treat every figure below as a single-source claim from the ranking site in question rather than an official result.
BenchLeader’s October 21, 2026 overall ranking lists Claude Opus 5.5 first at a score of 72.7, with Gemini 4 Argon second at 71.0 and a separate model called Muse Wonder Full third at 70.7, a gap of just 1.7 points between first and second place. BenchLM, a different ranking methodology, reports that Claude Opus 5.5 and GPT-6.1 Sol are statistically tied once you apply its 90% confidence-interval rule, which suggests the “winner” on that board is really a coin flip.
LiveBench tells a different story entirely. On its broader task suite, Claude Fable 5.1, again, a separate Anthropic model, not Opus 5.5, ranks first overall at 88.0. GPT-6 Astra follows at 86.1, with standout scores of 92.7 in coding and 93.7 in browser use. GPT-6.1 Sol scores 85.4 overall but matches Astra closely on the sub-scores that matter most for agentic work: 92.6 in coding and 96.0 in browser use, actually beating Astra on that second metric. Gemini 4 Argon posts 84.1 overall on LiveBench, with a standout 92.0 in data analysis, the highest of any model listed. DeepSeek’s V4.1 Flash 1017 checkpoint, released October 17, 2026, trails at 79.2 overall but still manages 89.1 in coding and 96.0 in browser use, numbers that look remarkable given its lower price point (a dynamic covered in more depth in our Grok 4.7 vs Claude vs DeepSeek pricing comparison).
Benchmark reports on these three models remain scattered and third-party, with no single verified leaderboard tying them together. Third-party pages report Claude Opus 5.5 leading on some coding benchmarks, including Terminal-Bench 4.0 (see our dedicated Terminal-Bench 4.0 breakdown), while Gemini 4 Argon leads on several other benchmarks, according to ComputingForGeeks’ benchmark breakdown. No comparable GPT-6.1 Sol score accompanies those reports. Google, meanwhile, makes its own claim rather than relying on third-party rankings: it says Gemini 4 Argon ranks first on the Vals Index, an evaluation that spans finance, coding, legal work, and tax tasks. That’s Google’s own positioning, not an independently verified result, but it’s worth noting because it targets exactly the kind of enterprise knowledge work these models are increasingly sold for.
Put together, four different ranking systems produce four different top models: BenchLeader favors Opus 5.5, LiveBench favors Fable 5.1 (not even one of our three subjects), BenchLM calls Opus 5.5 and GPT-6.1 Sol a tie, and Google’s self-reported Vals Index favors Argon. If you came here looking for a single definitive llm leaderboard entry, that’s the honest answer: it doesn’t exist yet, and anyone presenting one ranking as the final word on this llm leaderboard race is oversimplifying.
Coding and Agentic Benchmarks: What Each Company Actually Published
Away from third-party leaderboards, each company has published its own internal test results, which carry the usual caveat that a vendor is grading its own product, but they’re still useful for understanding what each model claims to be good at.
Anthropic’s own release notes for Opus 5.5 cite FrontierCode, a test that measures whether an agent’s code changes would actually get merged. At default (medium) effort, Anthropic reports Opus 5.5 scoring 54.6%, which the company says is higher than every other model it tested, including a 53.3% score for GPT-6 Astra, notably not GPT-6.1 Sol, at roughly one-fifth of the cost per task. Anthropic also cites AutomationBench, built by Zapier to test whether an agent can carry out real cross-app business workflows, saying Opus 5.5 outscores both Opus 5 and GPT-5.6 Sol at every effort level. A third internal reference, Perplexity’s WANDR benchmark for large data-collection tasks, is cited by Anthropic as showing Opus 5.5 outperforming Fable 5.1 and Opus 5 at a lower cost per task.
OpenAI’s comparison point for GPT-6.1 Sol is cost-efficiency rather than raw accuracy. The company reports an average cost of $5.47 per task at maximum reasoning effort for GPT-6.1 Sol, against $23.21 per task for Claude Opus 5.5, a more than four-fold difference. That’s an OpenAI-reported figure from its own testing, not an independently confirmed leaderboard result, and it doesn’t specify which task set produced those numbers, so treat it as directional rather than exact.
Google’s coding claims for Gemini 4 Argon lean on the same Vals Index mentioned above, plus Google’s description of “more direct answers, less hedging and repetition, improved progress updates during long tasks, and stronger coding performance” compared with earlier Gemini releases. Google hasn’t published a FrontierCode-style merge-rate statistic for Argon in the materials available as of October 21, 2026.
API Pricing Breakdown: Input, Output, and Cached Tokens
Token pricing is the clearest, most verifiable comparison point between these three models, since every number below comes directly from each company’s own pricing documentation.
| Model / Tier | Input ($/1M tokens) | Cached Input ($/1M tokens) | Output ($/1M tokens) |
|---|---|---|---|
| Claude Opus 5.5 (standard) | $4.00 | $0.20 (cache read) | $20.00 |
| Claude Opus 5.5 Fast mode | $8.00 | Not published | $40.00 |
| Claude Opus 5 (predecessor, for reference) | $5.00 | Not published | $25.00 |
| GPT-6.1 Sol | $2.00 | $0.10 | $10.00 |
| Gemini 4 Argon (through Nov 30, 2026) | $2.00 | 95% off input price | $10.00 |
| Gemini 4 Argon (from Dec 1, 2026) | $4.00 | 95% off input price | $20.00 |
Two things stand out. First, Gemini 4 Argon’s price is a moving target: it matches GPT-6.1 Sol’s $2/$10 rate today, but doubles to match Claude Opus 5.5’s $4/$20 rate the moment the introductory window closes on November 30, 2026. Anyone budgeting a long-running project around Argon’s current price needs to plan for that jump now, not in December. Second, Claude Opus 5.5’s Fast mode, at $8 input and $40 output, has been generally available in Claude Code and on the Claude Platform, offering roughly 2.5x speed.
Subscription Plans and Consumer Pricing
Most individual users won’t touch the raw API, so here’s what each company charges for its consumer and team subscription tiers, limited strictly to the figures each company has published.
| Provider | Plan | Price | Notes |
|---|---|---|---|
| Anthropic (Claude) | Pro | $20/month (or $200 billed annually) | Includes Opus 5.5 access |
| Anthropic (Claude) | Team (per seat) | $25/month billed monthly | Standard seat tier |
| Anthropic (Claude) | Team Premium (per seat) | $125/month billed monthly | Higher-tier seat |
| Anthropic (Claude) | Enterprise | Not publicly listed | Up to $500/month in pooled API credits |
| OpenAI (ChatGPT) | Free | $0 | Available to everyone; no GPT-6.1 Sol |
| OpenAI (ChatGPT) | Pro 100 | $100/month | GPT-6.1 Sol in Work/Codex |
| OpenAI (ChatGPT) | Pro 200 | $200/month | $100/month billed annually, $125/month billed monthly |
| OpenAI (ChatGPT) | Pro 500 | $500/month | Includes GPT-6 Astra Ultrafast + GPT-6.1 Sol Ultrafast |
| Google (Gemini) | Google AI Pro | Not listed | 5TB storage, Argon access in Gemini app |
| Google (Gemini) | Google AI Ultra | Not confirmed in this snapshot | 20TB+ storage, Antigravity access |
The OpenAI Pro 500 tier deserves a second look: at $500 a month, it’s the only plan among the three companies that bundles the absolute flagship model (GPT-6 Astra, in an “Ultrafast” configuration) alongside the cheaper GPT-6.1 Sol, also in an Ultrafast variant. That’s a meaningfully different value proposition than Claude’s Pro plan at $20/month, which gets you standard Opus 5.5 access but not a guaranteed-speed tier without separately paying Fast mode’s per-token premium.
Context Windows, Output Limits, and Platform Availability
Gemini 4 Argon’s jump to a 1-million-token output ceiling, up from 64,000 tokens on the previous Gemini generation, is the single biggest structural change among the three releases. That matters for workloads that need a model to generate very long single outputs, like full codebase refactors, long legal documents, or exhaustive data transformations, rather than workloads that fit comfortably in shorter responses. Neither Anthropic nor OpenAI has published an equivalent standalone output-token ceiling for Opus 5.5 or GPT-6.1 Sol in their current documentation, which doesn’t mean they’re smaller, just that the companies haven’t chosen to market that number the way Google has.
Platform reach also differs. Claude Opus 5.5 is the most cloud-portable of the three, available natively through Amazon Web Services, Google Cloud, and Microsoft Azure in addition to Anthropic’s own API and Claude apps, useful if your infrastructure is locked into a specific cloud vendor but you still want Claude’s model quality. Gemini 4 Argon’s reach is understandably deep inside Google’s own ecosystem: Google Antigravity (an agentic coding interface), Android Studio, AI Mode in Google Search, and Gemini for business all got Argon access as part of the October 13 rollout, with automotive integration (Gemini in Android Auto) following October 20. GPT-6.1 Sol’s distribution is the narrowest of the three in one specific way: OpenAI has kept it out of standard ChatGPT Chat entirely, restricting it to Work and Codex contexts across Plus, Pro, Business, Enterprise, and Edu plans.
Enterprise, Developer, and Research Program Expansions
Model releases are only half the October 2026 story. All three companies also expanded the programs that surround their models, and those programs often matter more than the raw benchmark gap for enterprise buyers deciding where to commit budget.
Anthropic has made other moves too, though not all are confirmed by the company’s own pages. One confirmed step: Anthropic expanded its Cyber Verification Program to three access tiers on October 6, 2026, letting qualifying security teams apply for advanced capabilities across Claude Opus 5.5, Claude Sonnet 5.5, and a model called Claude Mythos 5.1, according to Anthropic.
Google’s equivalent expansion centers on the Fairwind Program, which started as Gemini 4 Argon’s October 1 limited release for trusted cybersecurity defenders and grew into broader access alongside Argon’s October 13 general release. OpenAI’s program expansion is more purely commercial: the October 20, 2026 introduction of the $500/month Pro 500 tier, which bundles “Ultrafast” versions of both GPT-6 Astra and GPT-6.1 Sol, alongside the reinstatement of Pro 200 for new subscribers at the same $200/month price existing subscribers already paid.
Safety, Bias, and Compliance Updates Worth Knowing
Buyers evaluating these models for regulated or public-facing use cases should know about a few compliance-adjacent changes that shipped alongside the core model releases. Anthropic reported on October 14, 2026 that Opus 5.5, Sonnet 5.5, and Haiku 5.5 all scored 99% on its internal political-evenhandedness evaluation, a metric the company uses ahead of the 2026 US midterms; that figure is Anthropic’s own evaluation claim rather than an independently audited result, so treat it with the same caution as any vendor-reported score. Anthropic also strengthened its defenses against distillation attacks on October 12, 2026, measures that apply specifically to API accounts created on or after August 31, 2026, and both Claude Fable 5.1 and Opus 5.5 introduced “preserved thinking,” which prevents those newer accounts from editing Claude’s prior reasoning context.
Separately, Anthropic confirmed that, like previous Opus models, Opus 5.5 is available with zero data retention, and that it ships with watermarking measures to comply with the EU AI Act. One operational wrinkle worth flagging for teams that build on raw model output without a chat layer: Anthropic’s documentation notes Opus 5.5 is no longer available with “thinking” mode switched off, which can change latency and token-usage patterns for integrations built against earlier Claude versions that allowed disabling it.
Real-World Use Cases: Who Should Actually Use Each Model
Specs and benchmarks only matter in context. Here’s how the differences play out in practice across common engineering and business scenarios.
- Agentic coding teams chasing iteration speed: Claude Opus 5.5’s Fast mode, now generally available at $8/$40 per million tokens, trades a token-price premium for roughly 2.5x faster responses inside Claude Code, a reasonable swap for teams where developer wait time costs more than the extra API spend.
- High-volume customer support automation: GPT-6.1 Sol’s $0.10-per-million cached-input rate is built for exactly this: repeated system prompts and knowledge-base context reused across thousands of tickets inside ChatGPT Business or Enterprise Work mode, where the bulk of each request is identical boilerplate.
- Long-document generation and codebase-wide refactors: Gemini 4 Argon’s 1-million-token output ceiling is the only one of the three built to produce extremely long single responses without chunking, making it the practical choice for generating entire reports or large-scale code changes in one pass.
- Security and cyber-defense teams: Gemini 4 Argon’s roots in Google’s Fairwind Program (its original October 1 cyber-defender-only release) and Anthropic’s three-tier Cyber Verification Program for Opus 5.5 both point toward the same trend: frontier labs are fast-tracking security-cleared users to their newest models before general release.
- Cross-app business workflow automation: Anthropic’s AutomationBench results, built in partnership with Zapier, specifically target multi-step workflows across connected apps, and Anthropic reports Opus 5.5 beating both its own predecessor and GPT-5.6 Sol at every effort level on that test.
- Budget-constrained startups scaling API usage fast: Locking in Gemini 4 Argon’s $2/$10 introductory pricing before the November 30, 2026 increase to $4/$20 is a genuine near-term cost-timing decision, not just a theoretical one, for any team planning heavy usage in Q4 2026.
The table below condenses those scenarios into a quick reference for the single most decisive factor behind each recommendation.
| If you need… | Pick | Why |
|---|---|---|
| Fastest agentic coding iteration | Claude Opus 5.5 (Fast mode) | ~2.5x speed, generally available since Opus 5.5’s September 22, 2026 launch |
| Lowest cost per high-volume task | GPT-6.1 Sol | $2/$10 standard, $0.10/M cached input |
| Longest single-response output | Gemini 4 Argon | 1,000,000-token output ceiling |
| Cross-cloud deployment flexibility | Claude Opus 5.5 | Native on AWS, Google Cloud, and Azure |
| Early access to new cyber-defense tooling | Gemini 4 Argon or Claude Opus 5.5 | Fairwind Program / Cyber Verification Program |
| Cross-app business workflow automation | Claude Opus 5.5 | Leads AutomationBench per Anthropic |
| Cheapest possible entry point to test frontier models | GPT-6.1 Sol or Gemini 4 Argon | Matching $2/$10 introductory pricing |
Migration Guide: Switching Between Claude, GPT, and Gemini APIs
If you’re currently integrated with one of these providers and evaluating a switch, the good news is that all three expose similar REST and SDK patterns. The differences that actually trip up a migration are the model identifier strings, the chat-vs-API access split (especially for GPT-6.1 Sol), and cached-token handling. For a deeper walkthrough of setting up Claude’s developer tooling specifically, see our Claude Agent SDK setup guide.
Step-by-step migration checklist
- Confirm which API identifier you need:
claude-opus-5-5,gpt-6.1-sol, orgemini-4-argon. Model names are case-sensitive and provider-specific. - Check access tier eligibility before writing code. GPT-6.1 Sol requires a plan that includes Work/Codex access; it will not respond through endpoints scoped to regular ChatGPT Chat.
- Re-map your prompt-caching strategy. Anthropic charges $0.20/M for cache reads on Opus 5.5; OpenAI charges $0.10/M for cached input on GPT-6.1 Sol; Google discounts cached input 95% off Argon’s standard rate. These are not interchangeable discount structures.
- Budget for Gemini 4 Argon’s scheduled price increase. Any cost projection built before November 30, 2026 needs a second column for the post-increase $4/$20 rate.
- Test output-length assumptions separately for Gemini 4 Argon. Code that assumes a ~64K-token ceiling (true of the previous Gemini generation) may behave differently against Argon’s 1-million-token ceiling, especially around truncation-handling logic.
- If you depend on Claude Opus 5.5 Fast mode, note that it has been generally available in Claude Code and on the Claude Platform, priced at $8 per million input tokens and $40 per million output tokens.
- Re-run your evaluation suite rather than trusting a single leaderboard. Given how much BenchLeader, LiveBench, and TensorFeed disagree with each other, in-house testing against your actual workload is the only reliable tiebreaker.
A minimal request against each provider looks like this once you’ve swapped identifiers:
# Claude Opus 5.5 (Anthropic API)
curl https://api.anthropic.com/v1/messages \
-H "x-api-key: $ANTHROPIC_API_KEY" \
-H "anthropic-version: 2023-06-01" \
-H "content-type: application/json" \
-d '{
"model": "claude-opus-5-5",
"max_tokens": 1024,
"messages": [{"role": "user", "content": "Summarize this migration plan."}]
}'# GPT-6.1 Sol (OpenAI API, Work/Codex-scoped key required)
curl https://api.openai.com/v1/chat/completions \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "gpt-6.1-sol",
"messages": [{"role": "user", "content": "Summarize this migration plan."}]
}'# Gemini 4 Argon (Google Gemini API)
curl "https://generativelanguage.googleapis.com/v1/models/gemini-4-argon:generateContent?key=$GEMINI_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"contents": [{"parts": [{"text": "Summarize this migration plan."}]}]
}'Pros and Cons of Each Model
Claude Opus 5.5
- Pros: Leads BenchLeader’s overall October 21 ranking; 40% cheaper to run than its predecessor per Anthropic; now generally available Fast mode; widest cloud-platform reach across AWS, Google Cloud, and Azure.
- Cons: Highest standard per-token price of the three ($4/$20); OpenAI’s own cost comparison claims GPT-6.1 Sol completes equivalent tasks for roughly a quarter of the price; no published standalone max-output-token figure to compare against Argon’s 1 million.
GPT-6.1 Sol
- Pros: Standard token pricing of $2/$10, matched for now by Gemini 4 Argon’s introductory rate, and a cached-input rate of $0.10/M that Argon’s discounted rate also reaches; strong LiveBench coding (92.6) and browser-use (96.0) sub-scores; tied with Opus 5.5 under BenchLM’s confidence-interval methodology.
- Cons: Not available in ordinary ChatGPT Chat, only Work and Codex; not OpenAI’s flagship model, so some capability is deliberately traded for price; narrower access tier list than the other two.
Gemini 4 Argon
- Pros: Largest output ceiling by far at 1 million tokens; introductory pricing matches GPT-6.1 Sol’s $2/$10 rate; deepest integration across Google’s own ecosystem (Search, Android Studio, Antigravity, Android Auto); Google claims a #1 Vals Index ranking across finance, coding, legal, and tax tasks.
- Cons: Price doubles to $4/$20 on December 1, 2026, a scheduled increase that’s easy to overlook while budgeting; Google AI Ultra pricing for full Antigravity access isn’t published in current materials; started as a restricted cyber-defender-only release, so some documentation still reflects that narrower original scope.
The Verdict: No Single Leaderboard Wins, But the Data Points Somewhere
Anyone hoping this llm leaderboard comparison would crown one undisputed champion is going to be disappointed, and that’s the honest, data-backed conclusion rather than a dodge. BenchLeader puts Claude Opus 5.5 first by 1.7 points over Gemini 4 Argon. BenchLM calls Opus 5.5 and GPT-6.1 Sol a statistical tie. LiveBench’s overall leader isn’t even one of these three models. Google’s self-reported Vals Index favors Argon. That spread of outcomes across four different methodologies is itself the finding: at this point in the release cycle, the three models are close enough in raw capability that benchmark choice, not model choice, decides who “wins.”
Where the data is unambiguous is cost and structure. GPT-6.1 Sol and Gemini 4 Argon are priced the same for now, at $2 per million input tokens and $10 per million output tokens, and both also offer a cached-input rate near $0.10 per million, so neither is alone at the bottom of the pricing table. Argon’s rate is introductory and rises to $4 per million input tokens and $20 per million output tokens after November 30, 2026; Argon is also reportedly the leader on raw output capacity. Claude Opus 5.5 costs the most per token, at $4 per million input tokens and $20 per million output tokens, but backs that premium with the widest cloud-platform reach and a Fast mode available in Claude Code and the Claude Platform for teams that value speed over per-token economy. If your decision has to be data-driven rather than vibes-driven, pick based on the one variable each model actually wins clearly, output capacity, pricing structure, or platform reach, rather than waiting for a leaderboard consensus that, as of October 21, 2026, simply doesn’t exist.
How This Compares to the Previous Generation
It’s worth remembering how fast this field moves: our earlier look at ChatGPT vs Claude vs Gemini covered the generation these three models just replaced, and the gap between leaders there was reported at 5.8 points, more than three times the 1.7-point spread BenchLeader now reports between Opus 5.5 and Gemini 4 Argon. That tightening gap is itself a signal that the three labs are converging on similar capability levels even as they diverge sharply on pricing strategy, access structure, and which specific benchmark each chooses to publicize.
Frequently Asked Questions
Is Claude Opus 5.5 better than GPT-6.1 Sol?
It depends which leaderboard you trust. BenchLeader’s October 21, 2026 ranking puts Claude Opus 5.5 ahead overall, while BenchLM’s confidence-interval methodology calls the two models statistically tied. GPT-6.1 Sol costs roughly a quarter as much per task according to OpenAI’s own reported figures, so “better” depends heavily on whether you’re optimizing for accuracy or cost.
What is Gemini 4 Argon’s pricing after the introductory period ends?
Google has confirmed that after November 30, 2026, Gemini 4 Argon’s standard API price rises from $2 to $4 per million input tokens and from $10 to $20 per million output tokens, matching Claude Opus 5.5’s current standard rate.
Is GPT-6.1 Sol available in regular ChatGPT Chat?
No. As of October 21, 2026, OpenAI’s Help Center documentation lists GPT-6.1 Sol as a model option exclusively for ChatGPT Work and Codex, available to Plus, Pro, Business, Enterprise, and Edu users in those contexts, but separate from the models offered in ordinary Chat.
How much does Claude Opus 5.5 Fast mode cost?
Fast mode costs $8 per million input tokens and $40 per million output tokens, roughly double Opus 5.5’s standard $4/$20 rate, in exchange for approximately 2.5x faster response speed. It has been available since Opus 5.5 launched on September 22, 2026.
What is the Vals Index, and why does Google cite it for Gemini 4 Argon?
The Vals Index is a benchmark that evaluates models across finance, coding, legal work, and tax tasks. Google says Gemini 4 Argon ranks first on this index, a claim that comes directly from Google rather than an independent third party, which is worth keeping in mind when weighing it against other rankings.
Can I use Gemini 4 Argon for free?
Consumer access to Gemini 4 Argon in the Gemini app and AI Mode in Search requires a Google AI Pro or Google AI Ultra subscription; Google’s official pages do not list current subscription prices for those plans, and it is not part of Google’s free tier based on currently published access terms.
Which model has the largest output window?
Gemini 4 Argon, by a wide margin. Google increased its maximum output from 64,000 tokens on the previous generation to 1 million tokens, a ceiling neither Claude Opus 5.5 nor GPT-6.1 Sol has published an equivalent figure for.
Do any of these benchmarks agree on a single winner?
No, and that’s the central finding of this comparison. BenchLeader favors Claude Opus 5.5, BenchLM calls Opus 5.5 and GPT-6.1 Sol a tie, LiveBench’s top overall score belongs to a different Anthropic model entirely (Claude Fable 5.1), and Google’s self-reported Vals Index favors Gemini 4 Argon. Running your own evaluation against your actual workload remains the most reliable way to choose between them.
What is the Claude Frontier Academy, and does it affect this comparison?
The Claude Frontier Academy is a $100 million Anthropic program announced October 2, 2026, aimed at training 10,000 “Frontier Deployed Engineers” by the end of 2027. It doesn’t change Opus 5.5’s benchmark scores, but it’s a relevant data point for enterprises comparing not just model capability but each vendor’s investment in helping customers actually deploy that capability.
Does GPT-6.1 Sol replace GPT-6 Astra?
No. GPT-6 Astra remains OpenAI’s flagship model as of October 21, 2026. GPT-6.1 Sol is a separate, lower-cost release positioned as delivering near-Astra capability for agentic coding, computer use, and professional work at roughly one-fifth of Astra’s standard token price, not a replacement for it.
