Gemini 3.1 Pro vs Gemini 3.8 Flash

At a Glance

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Gemini 3.1 ProGoogle DeepMind
Gemini 3.8 FlashGoogle DeepMind
Intelligence, Cost, and Efficiency
IntelligenceHigher is better · MM Intelligence v4.4#9 of 5782.1 score · 3/3 sources · complete#4 of 5790.0 score · 3/3 sources · complete
CostLower is better · Published-token output estimate#18 of 27$0.161 per LiveBench case#17 of 27$0.160 per LiveBench case
EfficiencyHigher is better · MM Efficiency v1.9#8 of 2754.6 score · 3/3 sources · complete#7 of 2758.5 score · 3/3 sources · complete
Pricing and Limits
Input priceFrom · USD / 1M tokens$2.00Google AI ↗ · Aug 29, 2026$0.75Google AI ↗ · Sep 2, 2026
Output priceFrom · USD / 1M tokens$12.00Google AI ↗ · Aug 29, 2026$3.75Google AI ↗ · Sep 2, 2026
Context windowMaximum documented tokens1,049K1,049K
Model facts checkedAug 29, 2026View model evidence →Sep 2, 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 ProGemini 3.8 Flash
ARC-AGI-1verified-v1-302d8267c052 · verified_score · leader98.0099% of row best · percent · Gemini 3.1 Pro (Preview)98.50100% of row best · percent · Gemini 3.8 Flash (High)
ARC-AGI-2verified-v2-bca68e12cc9a · verified_score · leader77.0886% of row best · percent · Gemini 3.1 Pro (Preview)89.17100% of row best · percent · Gemini 3.8 Flash (High)
LMArena Agent Arenaagent-2026-10-16-a64ca3b12b6e · outcome_score · leader-4.0093% of row best · score · Gemini 3.1 Pro Preview; 95% CI [-5.35690873, -2.63856355]; sessions 87236; observations 2815597; rank 393.75100% of row best · score · Gemini 3.8 Flash (High); 95% CI [2.64957678, 4.84993702]; sessions 37692; observations 5316787; rank 15
LMArena Vision Arenavision-2026-10-09-a64ca3b12b6e · arena_rating · leader1,296.2099% of row best · rating · gemini-3.1-pro-preview; 95% CI [1291.04958388, 1301.35691905]; votes 46320; rank 221,314.08100% of row best · rating · gemini-3.8-flash-high; 95% CI [1303.54395703, 1324.61562115]; votes 3792; rank 8
LiveBench2026-06-25-90f8d44da965 · overall · leader81.66100% of row best · percent · gemini-3.1-pro-preview-high · 13,380 output tokens / case80.8599% of row best · percent · gemini-3.8-flash-high · 42,786 output tokens / case
ToneBench2026-10-17-10-task-e9c76358afb2 · overall_score · unverified70.99100% of row best · points · Gemini 3.1 Pro (high thinking) · 10,029 output tokens / case70.2299% of row best · points · Gemini 3.8 Flash (high thinking) · 20,369 output tokens / case
Overall ResultCounted from the protocol-matched rows above1 benchmark win4 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 ProGemini 3.8 Flash
DeveloperGoogle DeepMindGoogle DeepMind
FamilyGemini 3Gemini 3
ModelGemini 3.1 ProGemini 3.8 Flash
VersionGemini 3.1 ProGemini 3.8 Flash
Lifecyclepreviewactive
ReleasedUnknown2026-09-02
Knowledge cutoffUnknownUnknown
Input modalitiesText, Image, Video, Audio, DocumentText, Image, Video, Audio, Document
Output modalitiesTextText
Context window1,049K1,049K
Total parametersUnknownUnknown
Active parametersUnknownUnknown
LicenseUnknownUnknown
Open weightsNoNo
API availableYesYes
Self-hostableNoNo
Provider accessGoogle AI (Standard), Google Gemini (Standard)Google AI (Standard), Google Gemini (Standard)
Capabilitieschat, generation, reasoning, toolschat, code_execution, computer_use, generation, reasoning, structured_outputs, tools

Gemini 3.1 Pro Capabilities

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

Gemini 3.8 Flash Capabilities

chatcode executioncomputer usegenerationreasoningstructured outputstools
Serving providers2
Canonical IDgoogle-deepmind/gemini-3.8-flash

Primary Evidence

Sources and Freshness

Questions

Gemini 3.1 Pro vs Gemini 3.8 Flash FAQs

Is Gemini 3.1 Pro or Gemini 3.8 Flash better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both Gemini 3.1 Pro and Gemini 3.8 Flash, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.

Which is cheaper, Gemini 3.1 Pro or Gemini 3.8 Flash?+

Gemini 3.1 Pro is $2.00 and Gemini 3.8 Flash is $0.75 per million tokens, so Gemini 3.8 Flash is cheaper on this metric. Gemini 3.1 Pro is $12.00 and Gemini 3.8 Flash is $3.75 per million tokens, so Gemini 3.8 Flash is cheaper on this metric.

Which has a larger context window, Gemini 3.1 Pro or Gemini 3.8 Flash?+

Both models have the same sourced context window: 1,048,576 tokens each.

Which performs better in benchmarks, Gemini 3.1 Pro or Gemini 3.8 Flash?+

Gemini 3.8 Flash 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 Gemini 3.8 Flash be self-hosted?+

Both models have the same sourced self-hosting status: unsupported. Gemini 3.1 Pro is not marked open weight; Gemini 3.8 Flash is not marked open weight.

Can Gemini 3.1 Pro and Gemini 3.8 Flash understand images?+

Gemini 3.1 Pro is documented with image input; Gemini 3.8 Flash is documented with image input. This reflects supported input modalities, not vision quality.

Which can generate longer answers, Gemini 3.1 Pro or Gemini 3.8 Flash?+

Both models have the same sourced maximum output: 65,536 tokens each.

Do Gemini 3.1 Pro and Gemini 3.8 Flash support reasoning and tool use?+

Gemini 3.1 Pro: reasoning, tool calling, and image input. Gemini 3.8 Flash: 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 Gemini 3.8 Flash?+

Gemini 3.1 Pro has 2 sourced provider routes; Gemini 3.8 Flash has 2, a tie.

Which offers better value, Gemini 3.1 Pro or Gemini 3.8 Flash?+

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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