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Gemini 3.1 Pro vs GPT-6.1 Sol

At a Glance

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Gemini 3.1 ProGoogle DeepMind
Intelligence, Cost, and Efficiency
IntelligenceHigher is better · MM Intelligence v4.4#9 of 5782.1 score · 3/3 sources · complete#5 of 5785.9 score · 3/3 sources · complete
CostLower is better · Published-token output estimate#18 of 27$0.161 per LiveBench case#15 of 27$0.104 per LiveBench case
EfficiencyHigher is better · MM Efficiency v1.9#8 of 2754.6 score · 3/3 sources · complete#5 of 2760.1 score · 3/3 sources · complete
Pricing and Limits
Input priceFrom · USD / 1M tokens$2.00Google AI ↗ · Aug 29, 2026$2.00Openai ↗ · Sep 29, 2026
Output priceFrom · USD / 1M tokens$12.00Google AI ↗ · Aug 29, 2026$10.00Openai ↗ · Sep 29, 2026
Context windowMaximum documented tokens1,049K1,050K
Model facts checkedAug 29, 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 →

Available Benchmarks

All benchmark results →
BenchmarkGemini 3.1 ProGPT-6.1 Sol
ARC-AGI-1verified-v1-613c385b0c93 · verified_score · leader98.0099% of row best · percent · Gemini 3.1 Pro (Preview)98.50100% of row best · percent · GPT-6.1 Sol (XHigh)
ARC-AGI-2verified-v2-be40992860f9 · verified_score · leader77.0882% of row best · percent · Gemini 3.1 Pro (Preview)94.17100% of row best · percent · GPT-6.1 Sol (Max)
LMArena Search Arenasearch-2026-10-13-a64ca3b12b6e · arena_rating · leader1,208.8198% of row best · rating · gemini-3.1-pro-grounding; 95% CI [1204.12797055, 1213.48336905]; votes 151436; rank 151,233.10100% of row best · rating · gpt-6.1-sol-max; 95% CI [1224.24145466, 1241.96324521]; votes 5555; rank 8
LMArena Vision Arenavision-2026-10-09-a64ca3b12b6e · arena_rating · statistical tie1,296.20100% of row best · rating · gemini-3.1-pro-preview; 95% CI [1291.04958388, 1301.35691905]; votes 46320; rank 221,288.1999% of row best · rating · gpt-6.1-sol-max; 95% CI [1273.83724449, 1302.54208160]; votes 1813; rank 30
LiveBench2026-06-25-90f8d44da965 · overall · leader81.6695% of row best · percent · gemini-3.1-pro-preview-high · 13,380 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 · unverified70.9986% of row best · points · Gemini 3.1 Pro (high thinking) · 10,029 output tokens / case82.44100% 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 wins4 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

FieldGemini 3.1 ProGPT-6.1 Sol
DeveloperGoogle DeepMindOpenAI
FamilyGemini 3Gpt 6
ModelGemini 3.1 ProGPT-6.1 Sol
VersionGemini 3.1 ProGPT-6.1 Sol
Lifecyclepreviewactive
ReleasedUnknown2026-09-29
Knowledge cutoffUnknown2026-04-30
Input modalitiesText, Image, Video, Audio, DocumentText, Image
Output modalitiesTextText
Context window1,049K1,050K
Total parametersUnknownUnknown
Active parametersUnknownUnknown
LicenseUnknownUnknown
Open weightsNoNo
API availableYesYes
Self-hostableNoNo
Provider accessGoogle AI (Standard), Google Gemini (Standard)Openai (Standard), Openrouter (Standard)
Capabilitieschat, generation, reasoning, toolschat, computer-use, generation, reasoning, tools
Data residencyUnknownUS, EU
Default snapshotUnknowngpt-6.1-sol
Maximum input tokensUnknown922000
Multi-agentUnknownResponses API beta
Reasoning effortUnknownlow, medium, high, xhigh, max
Regional processing premiumUnknown10% where available
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
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

Gemini 3.1 Pro Capabilities

chatgenerationreasoningtools
Serving providers2
Canonical IDgoogle-deepmind/gemini-3.1-pro-preview

GPT-6.1 Sol Capabilities

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

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Primary Evidence

Sources and Freshness

Gemini 3.1 Pro Preview | Gemini APIGoogle DeepMind · observed Aug 29, 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, 2026LMArena Vision Arena vision-2026-10-09-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

Gemini 3.1 Pro vs GPT-6.1 Sol FAQs

Is Gemini 3.1 Pro or GPT-6.1 Sol better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both Gemini 3.1 Pro and GPT-6.1 Sol, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.

Which is cheaper, Gemini 3.1 Pro or GPT-6.1 Sol?+

Gemini 3.1 Pro is $2.00 and GPT-6.1 Sol is $2.00 per million tokens, so they are tied on this metric. Gemini 3.1 Pro is $12.00 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, Gemini 3.1 Pro or GPT-6.1 Sol?+

GPT-6.1 Sol has the larger sourced context window. Gemini 3.1 Pro supports 1,048,576 tokens and GPT-6.1 Sol supports 1,050,000 tokens.

Which performs better in benchmarks, Gemini 3.1 Pro or GPT-6.1 Sol?+

GPT-6.1 Sol leads the current overall benchmark count. The result uses 5 protocol-matched benchmarks from 3 publishers; it is not a universal quality score.

Can Gemini 3.1 Pro or GPT-6.1 Sol be self-hosted?+

Both models have the same sourced self-hosting status: unsupported. Gemini 3.1 Pro is not marked open weight; GPT-6.1 Sol is not marked open weight.

Can Gemini 3.1 Pro and GPT-6.1 Sol understand images?+

Gemini 3.1 Pro 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, Gemini 3.1 Pro or GPT-6.1 Sol?+

GPT-6.1 Sol has the larger sourced maximum output. Gemini 3.1 Pro supports 65,536 tokens and GPT-6.1 Sol supports 128,000 tokens.

Do Gemini 3.1 Pro and GPT-6.1 Sol support reasoning and tool use?+

Gemini 3.1 Pro: 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, Gemini 3.1 Pro or GPT-6.1 Sol?+

Gemini 3.1 Pro has 2 sourced provider routes; GPT-6.1 Sol has 2, a tie.

Which offers better value, Gemini 3.1 Pro 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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