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Model comparison

Claude Sonnet 5.5 vs GPT-6.1 Sol

Anthropic against OpenAI, compared on context, price, and attributed benchmark results.

Recorded profile verification October 1, 2026Individual provider fields may changeEvidence confidence: Medium — see receipts below

Anthropic

Claude Sonnet 5.5

Balanced

vs

OpenAI

GPT-6.1 Sol

Balanced

AI model capability comparison
SpecificationClaude Sonnet 5.5GPT-6.1 Sol
ProviderAnthropicOpenAI
TierBalancedBalanced
Context window1MWinner: 1.05M
Max output128K128K
Input / 1M tokens$2$2
Output / 1M tokens$10$10
WeightsClosedClosed
ParametersNot verifiedUnverifiedNot verifiedUnverified
Reasoning levelslow, medium, high, xhigh, maxlow, medium, high, xhigh, max
Modalitiestext, imagetext, image
API model idclaude-sonnet-5-5gpt-6.1-sol
ReleasedSeptember 28, 2026September 29, 2026
Artificial Analysis Intelligence Index [max] · source date Claude Sonnet 5.5: 2026-10-0156Not verifiedUnverified
Artificial Analysis Intelligence Index [max] · source date GPT-6.1 Sol: 2026-10-01Not verifiedUnverified52
Terminal-Bench 4.0 [max] · source date Claude Sonnet 5.5: 2026-10-0163.6Not verifiedUnverified
Terminal-Bench 4.0 · source date Claude Sonnet 5.5: 2026-10-0170.6Not verifiedUnverified
CursorBench 4.0 [max] · source date Claude Sonnet 5.5: 2026-10-0155.5Not verifiedUnverified
Humanity's Last Exam · source date Claude Sonnet 5.5: 2026-10-0164.5Not verifiedUnverified
FrontierCode 1.1 (Main) [xhigh] · source date Claude Sonnet 5.5: 2026-10-0152.1Not verifiedUnverified
OSWorld 2.1 · source date Claude Sonnet 5.5: 2026-10-0180.1Not verifiedUnverified

Dates beside benchmark scores refer to the linked source’s publication or capture date unless that source explicitly states when it measured the result. A shared URL alone does not establish comparable runs; unverified setups are marked. Prices are USD per million tokens at standard rates, excluding batch and caching discounts. Values we could not confirm from the provider are shown as “Not verified” rather than estimated.

Benchmark receipts

Where each score comes from, and how far it can be compared across models.

  • Source date2026-10-01
    Artificial Analysis (GPT-6.1 Sol (max))

    Composite index blending reasoning, knowledge, and coding evals into one 0–100 score.

    Comparable with caveatOnly same-version scores are comparable. v4.3.2 was rebaselined (the top score fell from 66 on v4.1.1 to ~58), so v4.1.1 figures must not be compared with v4.3.2 figures — check the cited source and its date.

  • Source date2026-10-01
    Anthropic (vendor-reported) (partial task set)
  • Source date2026-10-01
    Anthropic (vendor-reported)
  • Source date2026-10-01
    Anthropic (vendor-reported) (with tools)

    Frontier-knowledge ceiling: extremely hard multi-domain questions written to be near-impossible without deep expertise.

    Comparable with caveatSubset/tool configurations (text-only vs with-tools) differ between vendors and materially change scores; must match configuration to compare.

  • Source date2026-10-01
    Cursor (vendor-run coding agent)
  • Source date2026-10-01
    Artificial Analysis (independent, mini-swe-agent)

    Agentic terminal work: long multi-step tasks executed in a sandboxed shell environment.

    Comparable with caveatDo not directly compare scores across Terminal-Bench versions: 4.0 revises and prunes the 3.0 task set and changes environment resources, requiring fresh trials. Within 4.0, harness, time limit, tools, sampling and resource settings must match; maintainer-agent and Artificial Analysis runs are not interchangeable.

  • Source date2026-10-01
    Anthropic (vendor-reported)

    Agentic terminal work: long multi-step tasks executed in a sandboxed shell environment.

    Comparable with caveatDo not directly compare scores across Terminal-Bench versions: 4.0 revises and prunes the 3.0 task set and changes environment resources, requiring fresh trials. Within 4.0, harness, time limit, tools, sampling and resource settings must match; maintainer-agent and Artificial Analysis runs are not interchangeable.

  • Source date2026-10-01
    Artificial Analysis (Claude Sonnet 5.5 (max with fallback))

    Composite index blending reasoning, knowledge, and coding evals into one 0–100 score.

    Comparable with caveatOnly same-version scores are comparable. v4.3.2 was rebaselined (the top score fell from 66 on v4.1.1 to ~58), so v4.1.1 figures must not be compared with v4.3.2 figures — check the cited source and its date.

Pricing tiers

Claude Sonnet 5.5: Standard $2/$10 per MTok with no long-context surcharge; cache reads $0.20, 5-minute writes $2.50 and 1-hour writes $4. Batch $1/$5. US-only inference adds 10% where supported. The 300K output limit requires the Batch API beta header output-300k-2026-03-24; standard output stays 128K. Knowledge cutoff Jun 2026; retirement not sooner than September 28, 2027.

GPT-6.1 Sol: Standard $2/$10 per million tokens up to 272K input; cached input $0.10 and cache writes $2.50. Above 272K, the full request costs $4/$15 ($0.20 cached, $5 cache writes). Batch/Flex are half Standard; Fast is twice Standard. Regional/FedRAMP processing adds 10% where eligible; Fast is unavailable with EU data residency. No none/minimal reasoning. Use Responses for tools; Chat Completions has no tool calling.

BalancedRecord checked October 1, 2026

Claude Sonnet 5.5

Anthropic’s newer Sonnet model for everyday coding and knowledge work at the same $2/$10 token rates as Sonnet 5.

Best for

  • Everyday coding
  • Document and slide creation
  • Fast iteration

Watch out

Vendor scores use Anthropic's evaluation setup. between_tools turns off up-front thinking only at high effort or below. Forced tool use and non-default temperature/top_p/top_k error; older computer_20251124 and some advisors are rejected. Thinking blocks are model/conversation-bound; progress text needs a display setting that returns it. Haiku 5.5 is announced, not released as of October 1.

BalancedRecord checked October 1, 2026

GPT-6.1 Sol

OpenAI’s newer Sol model for coding, computer use and professional work, with the same base token price as GPT-6 Sol and lower cached-input pricing.

Best for

  • Agentic coding
  • Computer use
  • Professional work

Watch out

Compare quality on your own tasks. Reasoning starts at low; none and minimal are unsupported. Long prompts above 272K increase the rate for the whole request.

When the cheaper one wins

Both charge $10 per million output tokens at standard rates, so output price is not the split. Prefer the row whose “best for” line matches the job, then confirm the live vendor rate.

Run the model picker

Evidence confidence: Medium

How strong and complete the evidence behind this comparison is — not a prediction of which model is better.

  • Pricing verified on both sides — Input and output rates are verified for both models.
  • 4/5 core specs verified on both sides — Not published for at least one side: parameter count.
  • No directly aligned benchmark setup — No benchmark has matching cited sources, source dates, units, effort and recorded run details on both models.
  • Verified within the last 90 days — Older of the two catalog checks was 25 days ago.
  • Both models carry source citations — Each side has at least two catalog sources on record.

Source receipts

Each catalog figure was checked against the provider or an independent second source on the date shown.

Related comparisons

Diving deeper on one model? Claude Sonnet 5.5 · GPT-6.1 Sol

Common questions

Claude Sonnet 5.5 vs GPT-6.1 Sol

Answered from the verified figures on this page rather than general guidance.

Is Claude Sonnet 5.5 or GPT-6.1 Sol cheaper for input?
Both list a base rate of $2 per million input tokens. Actual cost can differ with context tiers, caching, tools and other charges. Claude Sonnet 5.5: Standard $2/$10 per MTok with no long-context surcharge; cache reads $0.20, 5-minute writes $2.50 and 1-hour writes $4. Batch $1/$5. US-only inference adds 10% where supported. The 300K output limit requires the Batch API beta header output-300k-2026-03-24; standard output stays 128K. Knowledge cutoff Jun 2026; retirement not sooner than September 28, 2027. GPT-6.1 Sol: Standard $2/$10 per million tokens up to 272K input; cached input $0.10 and cache writes $2.50. Above 272K, the full request costs $4/$15 ($0.20 cached, $5 cache writes). Batch/Flex are half Standard; Fast is twice Standard. Regional/FedRAMP processing adds 10% where eligible; Fast is unavailable with EU data residency. No none/minimal reasoning. Use Responses for tools; Chat Completions has no tool calling.
Is Claude Sonnet 5.5 or GPT-6.1 Sol cheaper for output?
Both list a base rate of $10 per million output tokens. Actual cost can differ with context tiers, caching, tools and other charges. Claude Sonnet 5.5: Standard $2/$10 per MTok with no long-context surcharge; cache reads $0.20, 5-minute writes $2.50 and 1-hour writes $4. Batch $1/$5. US-only inference adds 10% where supported. The 300K output limit requires the Batch API beta header output-300k-2026-03-24; standard output stays 128K. Knowledge cutoff Jun 2026; retirement not sooner than September 28, 2027. GPT-6.1 Sol: Standard $2/$10 per million tokens up to 272K input; cached input $0.10 and cache writes $2.50. Above 272K, the full request costs $4/$15 ($0.20 cached, $5 cache writes). Batch/Flex are half Standard; Fast is twice Standard. Regional/FedRAMP processing adds 10% where eligible; Fast is unavailable with EU data residency. No none/minimal reasoning. Use Responses for tools; Chat Completions has no tool calling.
Which has the larger context window, Claude Sonnet 5.5 or GPT-6.1 Sol?
GPT-6.1 Sol accepts 1.05M tokens against 1M for Claude Sonnet 5.5. This only matters if you routinely send very long documents or large codebases.
Do Claude Sonnet 5.5 and GPT-6.1 Sol support the same reasoning levels?
Both expose these named effort settings: "low", "medium", "high", "xhigh", "max". The same labels do not guarantee equal compute budgets or behavior across providers. Compare quality, latency and cost on your own tasks.
Should I use Claude Sonnet 5.5 or GPT-6.1 Sol?
Both are classified in our balanced tier; this editorial grouping does not imply equal capability. Claude Sonnet 5.5 is a candidate for everyday coding; GPT-6.1 Sol is a candidate for agentic coding. Compare accuracy, tool reliability, latency and cost on representative tasks.

Next step

Choosing between them

The verified figures that separate this pair, computed from the catalog rather than restated boilerplate.

  • Context: GPT-6.1 Sol takes 1.05M against 1M for Claude Sonnet 5.5 — only decisive if your prompts approach the smaller window.
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