Claude Opus 5.5 vs GPT-6.1 Sol: Price, Benchmarks and Which to Use

Claude Opus 5.5 is Anthropic's flagship model and GPT-6.1 Sol is OpenAI's mid-tier workhorse, so this isn't a fight between two flagships: it's a check on whether OpenAI's cheaper model has closed the gap on Anthropic's best. On list price, Sol is the clear winner — $2 per million input tokens and $10 per million output tokens against Opus 5.5's $4 and $20. On Anthropic's own benchmark charts, Opus 5.5 leads on most of the tasks the company tested, though OpenAI has not published an equivalent primary benchmark report for Sol that could be checked against those claims. For general coding, long-document analysis and most day-to-day agent work, Opus 5.5 is the safer default; for high-volume, budget-capped workloads where "good enough" beats "best," Sol is the one to reach for first.

Price per million tokens: Opus 5.5 vs. GPT-6.1 Sol

Pricing is the one place both companies publish numbers directly, so it's the most reliable comparison here. Anthropic's own pricing page lists Claude Opus 5.5 at $4 per million input tokens and $20 per million output tokens, with 5-minute cache writes at $5, 1-hour cache writes at $8, and cache hits at $0.20. OpenAI's developer pricing page lists GPT-6.1 Sol at $2 per million input tokens, $0.10 for cached input, and $10 per million output tokens — exactly half of Opus 5.5 on every line.

Sources: Anthropic model pricing table and OpenAI API pricing/model docs, both fetched directly from the vendors' own pages. ¹Anthropic documents the 1-million-token context window as a feature of "Claude 4.6 and later models," which includes Opus 5.5, rather than listing a separate figure on the Opus 5.5 pricing row.

At face value, Sol is the budget pick by a wide margin — half the cost on both ends of a request, and a cheaper cache-read rate too. The math changes somewhat if a workload needs Opus 5.5's fast mode equivalent or runs past Sol's 272,000-token threshold, where OpenAI applies a 2x input/cache multiplier and a 1.5x output multiplier for the entire request. For short-context, high-volume jobs, though, Sol's price advantage holds up cleanly against Anthropic's own numbers.

What Anthropic claims for Opus 5.5

Anthropic's own announcement for Opus 5.5, published September 22, 2026, frames the model as performing "at the level of Claude Fable 5.1 on most work" while costing roughly 40% less to run than the outgoing Opus 5. The company's benchmark table compares Opus 5.5 against its own Fable 5.1 and Opus 5, and against OpenAI's flagship GPT-6 Astra and OpenAI's older GPT-5.6 Sol — not against GPT-6.1 Sol, which had not launched yet. Selected figures from that chart:

Figures as published in Anthropic's own "Introducing Claude Opus 5.5" announcement. Anthropic notes these are run at its highest "xhigh" effort setting for Terminal-Bench, that safeguard interventions may have lowered some scores on sensitive categories, and that benchmark margins are an imperfect guide to real-world performance differences.

Anthropic leads on most of the categories it chose to publish, but loses two: AutomationBench and Terminal-Bench-Science, both to GPT-6 Astra — OpenAI's pricier flagship, not Sol. That's an important asterisk: none of these figures involve GPT-6.1 Sol directly, because Anthropic's chart predates Sol's release by about a week.

What's documented for GPT-6.1 Sol

OpenAI has not published a standalone primary benchmark report for GPT-6.1 Sol that this comparison could independently verify — the company's developer docs describe the model only as offering "near-Astra performance for complex work at a lower cost," without a benchmark table. What is confirmed directly from OpenAI's own developer documentation is the model's shape: a 1,050,000-token context window (with a maximum input of 922,000 tokens to leave room for output), a 128,000-token output ceiling, and an April 30, 2026 knowledge cutoff.

DevDay coverage from outlets that attended OpenAI's September 29, 2026 event describe GPT-6.1 Sol as an upgrade to GPT-6 Sol, aimed at reaching performance close to GPT-6 Astra on coding and agentic tasks at a fraction of Astra's price. Reported benchmark figures — such as a DeepSWE v1.1 software-engineering score in the mid-70s, roughly matching Astra — come from that secondary coverage rather than from an OpenAI blog post, so treat them as reported-but-unverified rather than vendor-confirmed.

An independent data point: Artificial Analysis

Artificial Analysis, an independent model-benchmarking firm, is one of the few outside trackers running both companies' models on the same test suite. Per its published Intelligence Index, Claude Opus 5.5 reportedly reached a top score of 58 at maximum reasoning effort — described by multiple outlets citing Artificial Analysis as the highest score the index had recorded to date, roughly five points ahead of GPT-6 Astra and Claude Fable 5.1, which were tied. Artificial Analysis's own comparison pages pair Opus 5.5 against GPT-6 Sol (the model Sol replaced) rather than GPT-6.1 Sol specifically at the time of writing, so a direct, independently measured Opus 5.5-vs-Sol score was not available to verify here. Treat any specific GPT-6.1 Sol index number you see elsewhere as a secondary claim until Artificial Analysis publishes a dedicated entry for it.

Where you can actually use each one

Claude Opus 5.5 is live now across Claude.ai, the Claude apps, and the Claude API for customers on paid plans, with Anthropic's announcement noting increased usage limits on Pro, Max, Team, and seat-based Enterprise plans at launch.

GPT-6.1 Sol's rollout looks more staged, based on DevDay coverage: multiple outlets reporting from OpenAI's September 29, 2026 event describe it as available to Plus, Pro, Business, Enterprise, and Edu users inside ChatGPT Work and Codex, plus API access under the model ID gpt-6.1-sol — but not yet inside the regular ChatGPT chat surface. A faster "Ultrafast" serving tier was reported as rolling out separately, tied to a new higher-priced Pro plan. None of this availability detail could be confirmed against an OpenAI primary announcement page during this review, so it should be read as reported by DevDay attendees rather than vendor-confirmed. If you're deciding whether Sol is reachable from your plan today, check OpenAI's own release notes before assuming either way — our comparison of GPT-6.1 Sol against GPT-6 Astra covers the access question in more depth.

Safety framing: what each company says about guardrails

Both companies tie this release to safety messaging, which is worth noting even though neither side's self-reported safety testing is independently audited in the way a benchmark table might be. Anthropic's Opus 5.5 announcement claims the model attempted to work around explicit boundaries in testing roughly 85% less often than Opus 5 or Claude's Mythos 5.1 model, and describes Opus 5.5 as the strongest model the company has tested on its internal automated behavioral audit, with external evaluators including METR reportedly involved pre-launch. DevDay coverage of GPT-6.1 Sol reports a comparable kind of claim from OpenAI — lower rates of attempting to bypass access restrictions than GPT-6 Sol — but again, this figure comes from third-party DevDay reporting rather than a primary OpenAI safety card this review could fetch directly. Both sets of numbers are the vendor marking its own homework; useful as a directional signal, not as independent verification.

Cost in practice: a few worked numbers

Anthropic's own announcement includes some concrete workload comparisons worth repeating because they come from the vendor rather than a reviewer's lab: a 200,000-line codebase audit and fix that reportedly took under three hours on Opus 5.5 versus more than 20 hours on Opus 5, and a C-to-Rust translation task on the HAProxy codebase that Opus 5.5 completed in 9.5 hours at 51% lower cost than Fable 5.1's 12-hour run. Anthropic also cites third-party enterprise pilots — Deloitte and Hebbia are named — reporting higher bug-catch rates and finance-rubric coverage respectively at lower effort settings than Opus 5.

No equivalent vendor-published workload table exists yet for GPT-6.1 Sol in what this review could access directly. Given that Sol's list price is half of Opus 5.5's on both input and output tokens, the practical question for most teams is less "which model scores higher" and more "does Sol's output quality hold up closely enough on your specific task to justify running at half the per-token cost" — a question raw benchmark percentages from either vendor's own chart can't fully answer, because neither company ran its chart against the other's newest model.

Which to use

For complex, multi-step coding work, long-document or codebase analysis, and agentic tasks that run for hours unattended, Opus 5.5 is the more conservative choice — it's the one with a published, favorable (if vendor-selected) benchmark comparison against a flagship-tier competitor, and it carries Anthropic's largest published usage-limit increase at launch. Teams already standardized on Claude Code or the Claude API, or comparing it against Anthropic's own smaller models, may also want to read how it stacks up against Claude Sonnet 5.5 on price and benchmarks before committing budget to the top tier.

For high-volume, cost-sensitive workloads — bulk classification, first-pass drafting, customer-support triage, anything run millions of times a month — GPT-6.1 Sol's half-price input and output tokens make it worth testing first, provided your own evaluation on your own data confirms the quality holds up; OpenAI's own "near-Astra" framing is a vendor claim about its relationship to GPT-6 Astra, not an audited claim against Opus 5.5. Teams evaluating OpenAI's lineup broadly may also want the fuller picture in our look at Gemini 4 Argon, GPT-6 Astra, and Claude Opus 5.5 side by side.

If your workload is mixed, a common pattern among teams that have made this kind of call before is to route the bulk of simple requests to the cheaper model and escalate only the harder cases to the pricier one — which is exactly the kind of tiering both companies' own pricing pages are built to support, between cache discounts on one side and a lower base rate on the other.

What's next

Anthropic has said Claude Sonnet 5.5 and Claude Haiku 5.5 are coming "in the coming weeks" after Opus 5.5, which would round out a full mid-tier comparison against Sol on Anthropic's side. On OpenAI's side, DevDay coverage points to a GPT-6.1 Sol "Ultrafast" serving tier arriving separately, plus a more capable (and reportedly safety-delayed) GPT-6.1 Astra that multiple outlets say was held back from the same launch window. Until OpenAI publishes its own primary benchmark report for GPT-6.1 Sol — and until Artificial Analysis or a similar independent tracker runs Sol and Opus 5.5 head-to-head on the same test suite — any claim that one model "beats" the other on raw capability should be treated as provisional. The price gap, by contrast, is confirmed directly from both companies' own pricing pages and isn't likely to move until either side's next release.

Written byTheo Park

Theo Park runs the AI desk at Pandromeda. He follows model launches from the frontier labs and the open-weight community, tracks the assistants and developer tools built on them, and explains what each release changes on pricing, capability and safety. His reporting leans on primary sources: model cards, technical reports, API documentation and the companies' own announcements.

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