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Claude Opus 5.5 vs GPT-6.1 Sol

At a Glance

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Intelligence, Cost, and Efficiency
IntelligenceHigher is better · MM Intelligence v4.4#1 of 57100.0 score · 2/3 sources · provisional · missing LMArena Text · full-core range 66.7–100.0#5 of 5785.9 score · 3/3 sources · complete
CostLower is better · Published-token output estimate#25 of 27$0.512 per LiveBench case#15 of 27$0.104 per LiveBench case
EfficiencyHigher is better · MM Efficiency v1.9#9 of 2753.9 score · 2/3 sources · provisional · missing LMArena Text · full-core range 37.3–53.9#5 of 2760.1 score · 3/3 sources · complete
Pricing and Limits
Input priceFrom · USD / 1M tokens$4.00Anthropic ↗ · Sep 22, 2026$2.00Openai ↗ · Sep 29, 2026
Output priceFrom · USD / 1M tokens$20.00Anthropic ↗ · Sep 22, 2026$10.00Openai ↗ · Sep 29, 2026
Context windowMaximum documented tokens1,000K1,050K
Model facts checkedSep 22, 2026View model evidence →Sep 29, 2026View model evidence →

Token prices are the lowest available sourced USD rates; input and output may use different providers. Cost ranking estimates output spend on LiveBench, not a full request bill. Ranking methodology →

Decision Notes

Workload evidence
ARC-AGI-1 (verified-v1-613c385b0c93): Claude Opus 5.5 98.5, GPT-6.1 Sol 98.5 percent; higher is better. The row is a statistical tie. ARC-AGI-2 (verified-v2-be40992860f9): Claude Opus 5.5 93.3333, GPT-6.1 Sol 94.1667 percent; higher is better. GPT-6.1 Sol leads this matched row. These results describe the published evaluation workloads, not a universal model winner or an independent Model Markets measurement. View evidence →
Reference request
A reference-request price comparison is unavailable: both models need current uncached input and output rates on the same provider, protocol, tier, region scope and quantization. The lowest prices above can use different routes and cannot establish a matched request bill. View evidence →
Deployment requirements
Claude Opus 5.5 is documented as not self-hostable; GPT-6.1 Sol is documented as not self-hostable. Recorded licenses: Claude Opus 5.5, not reported; GPT-6.1 Sol, not reported. If you need local deployment, verify the license and hardware requirements; an unknown field does not establish permission or lack of support. View evidence →

Available Benchmarks

All benchmark results →
BenchmarkClaude Opus 5.5GPT-6.1 Sol
ARC-AGI-1verified-v1-613c385b0c93 · verified_score · statistical tie98.50100% of row best · percent · Claude Opus 5.5 (High)98.50100% of row best · percent · GPT-6.1 Sol (XHigh)
ARC-AGI-2verified-v2-be40992860f9 · verified_score · leader93.3399% of row best · percent · Claude Opus 5.5 (High)94.17100% of row best · percent · GPT-6.1 Sol (Max)
LMArena Search Arenasearch-2026-10-13-a64ca3b12b6e · arena_rating · leader1,212.7598% of row best · rating · claude-opus-5.5-medium; 95% CI [1205.66309681, 1219.84195206]; votes 10842; rank 141,233.10100% of row best · rating · gpt-6.1-sol-max; 95% CI [1224.24145466, 1241.96324521]; votes 5555; rank 8
LiveBench2026-06-25-90f8d44da965 · overall · leader85.94100% of row best · percent · claude-opus-5-5-max-effort · 25,610 output tokens / case86.14100% of row best · percent · gpt-6.1-sol-max · 10,375 output tokens / case
ToneBench2026-10-17-10-task-e9c76358afb2 · overall_score · unverified85.93100% of row best · points · Claude Opus 5.5 (max effort) · 126,485 output tokens / case82.4496% of row best · points · GPT-6.1 Sol (max) · 21,221 output tokens / case
Overall ResultCounted from the protocol-matched rows above · 1 tie0 benchmark wins3 benchmark winsOverall lead

Third-party benchmark Only like-for-like primary-publisher results are shown; raw scores, relative scores, configuration, and token spend remain visible.

Quality Versus Estimated Output Cost

Full ranking →
Efficiency FrontierLiveBench overall · output estimate
Upper-left is better
xAIZ.aiOpenAIMiniMaxDeepSeekMistral AIQwenGoogle DeepMindMoonshot AIAnthropic
LiveBench quality versus score-adjusted output costEach dot is a reviewed major-model configuration and is colored by developer. Higher means a better LiveBench overall score. Farther left means lower estimated output cost after adjusting by the score. A dotted line connects the non-dominated frontier observations. When models are selected, their sourced families remain prominent, unrelated observations retain their developer colors at lower opacity, and an orange ring identifies each selected model.$0.0050$0.010$0.050$0.100$0.500$1.006873798489Grok Build 0.1GLM 5.3 FlashGPT-6 Luna (max)DeepSeek V4.1 Flash (max)GPT-6.1 Sol (max)GPT-6 Astra (max)Claude Fable 5.1Score-adjusted output cost per LiveBench case (log) →LiveBench overall →
The dotted frontier connects measured, non-dominated major-model observations. With a selection, sourced families stay prominent, unrelated observations retain their developer colors at lower opacity, and orange rings mark the selected model or models. Family lines connect models only when their sourced family and generation match. Cost is estimated from published output tokens and the lowest current USD output rate; it excludes input, caching, batch discounts, and provider-specific benchmark execution details.

Side-by-Side Facts

FieldClaude Opus 5.5GPT-6.1 Sol
DeveloperAnthropicOpenAI
FamilyClaude 5 5Gpt 6
ModelClaude Opus 5.5GPT-6.1 Sol
VersionClaude Opus 5.5GPT-6.1 Sol
Lifecycleactiveactive
Released2026-09-222026-09-29
Knowledge cutoff2026-06-012026-04-30
Input modalitiesText, ImageText, Image
Output modalitiesTextText
Context window1,000K1,050K
Total parametersUnknownUnknown
Active parametersUnknownUnknown
LicenseUnknownUnknown
Open weightsNoNo
API availableYesYes
Self-hostableNoNo
Provider accessAnthropic (Standard), Deepinfra (Standard)Openai (Standard), Openrouter (Standard)
Capabilitieschat, generation, reasoning, toolschat, computer-use, generation, reasoning, tools
Message Batches max output (beta)300000 tokensUnknown
Data residencyUnknownUS, EU
Default effortmediumUnknown
Default snapshotUnknowngpt-6.1-sol
Maximum input tokensUnknown922000
Multi-agentUnknownResponses API beta
Reasoning effortUnknownlow, medium, high, xhigh, max
Regional processing premiumUnknown10% where available
Retirement commitmentNot sooner than September 22, 2027Unknown
Supported API routesUnknownv1/responses, v1/chat/completions, v1/batch
Supported toolsUnknownweb_search, file_search, image_generation, code_interpreter, hosted_shell, apply_patch, skills, computer_use, mcp, tool_search
ThinkingAdaptive (always on)Unknown
Tier 1 rate limitsUnknown500 RPM; 500,000 TPM
Tier 2 rate limitsUnknown5,000 RPM; 1,000,000 TPM
Tier 3 rate limitsUnknown5,000 RPM; 2,000,000 TPM
Tier 4 rate limitsUnknown10,000 RPM; 4,000,000 TPM
Tier 5 rate limitsUnknown15,000 RPM; 40,000,000 TPM
Tool calling routeUnknownResponses API only

Claude Opus 5.5 Capabilities

chatgenerationreasoningtools
Serving providers2
Canonical IDanthropic/claude-opus-5-5

GPT-6.1 Sol Capabilities

chatcomputer-usegenerationreasoningtools
Serving providers2
Canonical IDopenai/gpt-6.1-sol

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Primary Evidence

Sources and Freshness

Claude Opus 5.5 | Claude Platform DocsAnthropic · observed Sep 22, 2026GPT-6.1 Sol Model | OpenAI APIOpenAI · observed Sep 29, 2026ARC-AGI-1 verified-v1-613c385b0c93 score tableARC Prize Foundation · observed Oct 15, 2026ARC-AGI-2 verified-v2-be40992860f9 score tableARC Prize Foundation · observed Oct 15, 2026LMArena Search Arena search-2026-10-13-a64ca3b12b6e score tableLMArena · observed Oct 19, 2026LiveBench 2026-06-25-90f8d44da965 score tableLiveBench · observed Oct 15, 2026LiveBench 2026-06-25-90f8d44da965 token accountingLiveBench · observed Oct 15, 2026ToneBench 2026-10-17-10-task-e9c76358afb2 score tableTowards AI · observed Oct 17, 2026

Questions

Claude Opus 5.5 vs GPT-6.1 Sol FAQs

Is Claude Opus 5.5 or GPT-6.1 Sol better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both Claude Opus 5.5 and GPT-6.1 Sol, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.

Which is cheaper, Claude Opus 5.5 or GPT-6.1 Sol?+

Claude Opus 5.5 is $4.00 and GPT-6.1 Sol is $2.00 per million tokens, so GPT-6.1 Sol is cheaper on this metric. Claude Opus 5.5 is $20.00 and GPT-6.1 Sol is $10.00 per million tokens, so GPT-6.1 Sol is cheaper on this metric.

Which has a larger context window, Claude Opus 5.5 or GPT-6.1 Sol?+

GPT-6.1 Sol has the larger sourced context window. Claude Opus 5.5 supports 1,000,000 tokens and GPT-6.1 Sol supports 1,050,000 tokens.

Which performs better in benchmarks, Claude Opus 5.5 or GPT-6.1 Sol?+

GPT-6.1 Sol leads the current overall benchmark count. The result uses 4 protocol-matched benchmarks from 3 publishers; it is not a universal quality score.

Can Claude Opus 5.5 or GPT-6.1 Sol be self-hosted?+

Both models have the same sourced self-hosting status: unsupported. Claude Opus 5.5 is not marked open weight; GPT-6.1 Sol is not marked open weight.

Can Claude Opus 5.5 and GPT-6.1 Sol understand images?+

Claude Opus 5.5 is documented with image input; GPT-6.1 Sol is documented with image input. This reflects supported input modalities, not vision quality.

Which can generate longer answers, Claude Opus 5.5 or GPT-6.1 Sol?+

Both models have the same sourced maximum output: 128,000 tokens each.

Do Claude Opus 5.5 and GPT-6.1 Sol support reasoning and tool use?+

Claude Opus 5.5: reasoning, tool calling, and image input. GPT-6.1 Sol: reasoning, tool calling, and image input. Feature support does not establish relative quality.

Which is available from more inference providers, Claude Opus 5.5 or GPT-6.1 Sol?+

Claude Opus 5.5 has 2 sourced provider routes; GPT-6.1 Sol has 2, a tie.

Which offers better value, Claude Opus 5.5 or GPT-6.1 Sol?+

There is no universal value winner. Compare the input and output prices above with the matched benchmark result for your workload: cheaper tokens can be offset by different quality, token usage, latency, or provider availability.

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