Gemini 3.1 Pro vs GPT-5.6 Luna

At a Glance

Compare
Gemini 3.1 ProGoogle DeepMind
Intelligence, Cost, and Efficiency
IntelligenceHigher is better · MM Intelligence v2.5#9 of 4679.7 score · 3/3 sources · complete#31 of 4652.7 score · 3/3 sources · complete
CostLower is better · Published-token output estimate#27 of 44$0.161 per LiveBench case#6 of 44$0.026 per LiveBench case
EfficiencyHigher is better · MM Efficiency v1.5#9 of 3859.2 score · 3/3 sources · complete#4 of 3864.8 score · 3/3 sources · complete
Pricing and Limits
Input priceFrom · USD / 1M tokens$2.00Google AI · Aug 29, 2026$0.20Openai · Sep 3, 2026
Output priceFrom · USD / 1M tokens$12.00Google AI · Aug 29, 2026$1.20Openai · Sep 3, 2026
Context windowMaximum documented tokens1,049K1,050K
Model facts checkedAug 29, 2026View model evidence →Aug 28, 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-5.6 Luna
ARC-AGI-1verified-v1-ba05d69f6453 · verified_score · leader98.00100% of row best · percent · Gemini 3.1 Pro (Preview)90.6793% of row best · percent · GPT-5.6 Luna 2026-07-30 (Max)
ARC-AGI-2verified-v2-6c676fa3e9af · verified_score · leader77.08100% of row best · percent · Gemini 3.1 Pro (Preview)59.5877% of row best · percent · GPT-5.6 Luna 2026-07-30 (Max)
LMArena Agent Arenaagent-2026-09-15-d25aabda0010 · outcome_score · leader-5.8195% of row best · score · Gemini 3.1 Pro Preview; 95% CI [-6.60162758, -5.00976712]; sessions 86017; observations 2915267; rank 38-0.44100% of row best · score · GPT 5.6 Luna (xHigh); 95% CI [-1.27310649, 0.39719069]; sessions 29186; observations 2307801; rank 27
LMArena Document Arenadocument-2026-09-13-d25aabda0010 · arena_rating · statistical tie1,443.9299% of row best · rating · gemini-3.1-pro-preview; 95% CI [1438.69417039, 1449.14324048]; votes 49457; rank 311,456.92100% of row best · rating · gpt-5.6-luna-xhigh; 95% CI [1448.72029252, 1465.11301394]; votes 5766; rank 23
LMArena Text Arenatext-2026-09-13-d25aabda0010 · arena_rating · leader1,480.08100% of row best · rating · gemini-3.1-pro-preview; 95% CI [1476.92899018, 1483.22190450]; votes 106951; rank 161,429.8997% of row best · rating · gpt-5.6-luna-xhigh; 95% CI [1425.11549148, 1434.66063238]; votes 28547; rank 86
LMArena Vision Arenavision-2026-09-13-d25aabda0010 · arena_rating · leader1,295.61100% of row best · rating · gemini-3.1-pro-preview; 95% CI [1290.13797622, 1301.07924121]; votes 40691; rank 191,258.5397% of row best · rating · gpt-5.6-luna-xhigh; 95% CI [1250.17799393, 1266.87249678]; votes 7793; rank 48
LiveBench2026-06-25 · overall · leader81.66100% of row best · percent · gemini-3.1-pro-preview-high · 13,380 output tokens / case77.0594% of row best · percent · gpt-5.6-luna-max · 21,799 output tokens / case
ToneBench2026-09-11-10-task-4ef099199c9c · overall_score · unverified79.8995% of row best · points · Gemini 3.1 Pro (high thinking) · 10,009 output tokens / case84.47100% of row best · points · GPT-5.6 Luna (ultra) · 17,605 output tokens / case
Overall ResultCounted from the protocol-matched rows above · 1 tie5 benchmark winsOverall lead1 benchmark win

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.aiMiniMaxDeepSeekOpenAIQwenGoogle 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 FlashDeepSeek V4.1 Flash (max)GPT-5.6 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-5.6 Luna
DeveloperGoogle DeepMindOpenAI
FamilyGemini 3Gpt 5 6
ModelGemini 3.1 ProGPT-5.6 Luna
VersionGemini 3.1 ProGPT-5.6 Luna
Lifecyclepreviewactive
ReleasedUnknownUnknown
Knowledge cutoffUnknown2026-02-16
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, generation, reasoning, tools

Gemini 3.1 Pro Capabilities

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

GPT-5.6 Luna Capabilities

chatgenerationreasoningtools
Serving providers2
Canonical IDopenai/gpt-5.6-luna

Primary Evidence

Sources and Freshness

Questions

Gemini 3.1 Pro vs GPT-5.6 Luna FAQs

Is Gemini 3.1 Pro or GPT-5.6 Luna better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both Gemini 3.1 Pro and GPT-5.6 Luna, 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-5.6 Luna?+

Gemini 3.1 Pro is $2.00 and GPT-5.6 Luna is $0.20 per million tokens, so GPT-5.6 Luna is cheaper on this metric. Gemini 3.1 Pro is $12.00 and GPT-5.6 Luna is $1.20 per million tokens, so GPT-5.6 Luna is cheaper on this metric.

Which has a larger context window, Gemini 3.1 Pro or GPT-5.6 Luna?+

GPT-5.6 Luna has the larger sourced context window. Gemini 3.1 Pro supports 1,049K and GPT-5.6 Luna supports 1,050K.

Which performs better in benchmarks, Gemini 3.1 Pro or GPT-5.6 Luna?+

Gemini 3.1 Pro leads the current overall benchmark count. The result uses 7 protocol-matched benchmarks from 3 publishers; it is not a universal quality score.

Can Gemini 3.1 Pro or GPT-5.6 Luna be self-hosted?+

Both models have the same recorded self-hosting status: unsupported. Gemini 3.1 Pro is not marked open weight; GPT-5.6 Luna is not marked open weight.

Can Gemini 3.1 Pro and GPT-5.6 Luna understand images?+

Gemini 3.1 Pro is documented with image input; GPT-5.6 Luna is documented with image input. This reflects supported input modalities, not vision quality.

Which can generate longer answers, Gemini 3.1 Pro or GPT-5.6 Luna?+

GPT-5.6 Luna has the larger sourced maximum output: Gemini 3.1 Pro supports 66K and GPT-5.6 Luna supports 128K output tokens.

Do Gemini 3.1 Pro and GPT-5.6 Luna support reasoning and tool use?+

Gemini 3.1 Pro: reasoning, tool calling, and image input. GPT-5.6 Luna: 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-5.6 Luna?+

Gemini 3.1 Pro has 2 sourced provider routes; GPT-5.6 Luna has 2, a tie.

Which offers better value, Gemini 3.1 Pro or GPT-5.6 Luna?+

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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