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Qwen3.8 27B vs Gemini 3.1 Pro

Market Position

LiveBench Quality Versus Estimated Output Cost

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Efficiency FrontierLiveBench overall · output estimate
Upper-left is better
xAIDeepSeekZ.aiMiniMaxOpenAIQwenGoogle 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$0.020$0.050$0.100$0.200$0.5006873788287Grok Build 0.1GLM 5.3 FlashGPT-5.6 Luna (max)DeepSeek V4 Flash Vision ExpGPT-5.6 Sol (max)Score-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.

This current-market view appears only when both compared models are reviewed current models with publisher-reported LiveBench token accounting and current sourced USD output rates.

Model Markets Rankings

Intelligence, Cost, and Efficiency

All rankings →
RankingQwen3.8-27BGemini 3.1 Pro
CostLower is better · Published-token output estimate#16 of 36$0.086 per LiveBench case#22 of 36$0.161 per LiveBench case

Ranks come from the current complete eligible cohorts. Green highlights appear only when both models are ranked in the same metric. Missing required inputs remain unranked, and the three dimensions are not collapsed into an overall winner.

Benchmark Performance

Available Benchmarks

All benchmark results →
BenchmarkQwen3.8-27BGemini 3.1 Pro
LMArena Text Arenatext-2026-09-01-011508720696 · arena_rating · leader1,437.3597% of row best · rating · qwen3.8-27b; 95% CI [1429.71618499, 1444.98971204]; votes 6626; rank 691,480.10100% of row best · rating · gemini-3.1-pro-preview; 95% CI [1476.89767236, 1483.30025658]; votes 102763; rank 11
LMArena Vision Arenavision-2026-08-27-011508720696 · arena_rating · statistical tie1,279.3299% of row best · rating · qwen3.8-27b; 95% CI [1267.46655532, 1291.16933290]; votes 2954; rank 281,295.39100% of row best · rating · gemini-3.1-pro-preview; 95% CI [1289.75236576, 1301.03738662]; votes 39412; rank 17
LiveBench2026-06-25 · overall · leader78.0296% of row best · percent · qwen3.8-27b · 28,740 output tokens / case81.66100% of row best · percent · gemini-3.1-pro-preview-high · 13,380 output tokens / case
Overall ResultCounted from the protocol-matched rows above · 1 tie0 benchmark wins2 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.

FieldAt a Glance
Qwen · activeQwen3.8 27BVerified Aug 28, 2026
Google DeepMind · previewGemini 3.1 ProVerified Aug 29, 2026

Technical Differences

Side-by-Side Facts

Indexable
FieldQwen3.8-27BGemini 3.1 Pro
DeveloperQwenGoogle DeepMind
FamilyQwen3 8 27bGemini 3
ModelQwen3.8-27BGemini 3.1 Pro
VersionQwen3.8-27BGemini 3.1 Pro
Lifecycleactivepreview
ReleasedUnknownUnknown
Knowledge cutoffUnknownUnknown
Input modalitiesText, ImageText, Image, Video, Audio, Document
Output modalitiesTextText
Context window262K1,049K
Total parameters27.8BUnknown
Active parametersUnknownUnknown
Licenseapache-2.0Unknown
Open weightsYesNo
API availableYesYes
Self-hostableYesNo
Provider accessDeepinfra (Standard), Hugging Face (Standard), Openrouter (Standard)Google AI (Standard), Google Gemini (Standard)
Capabilitieschat, generation, reasoning, toolschat, generation, reasoning, tools

13 comparable fields · 10 material differences · Pair passes the primary-source comparison gate

Qwen3.8 27B Capabilities

chatgenerationreasoningtools
Input price$0.40
Output price$3.00
Serving providers3
Canonical IDQwen/Qwen3.8-27B

Gemini 3.1 Pro Capabilities

chatgenerationreasoningtools
Input price$2.00
Output price$12.00
Serving providers2
Canonical IDgoogle-deepmind/gemini-3.1-pro-preview

Internal Comparison Graph

Related Comparisons

All text comparisons →
APairBContext
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Primary Evidence

Sources and Freshness

Qwen/Qwen3.8-27B developer model repositoryQwen · observed Aug 28, 2026Gemini 3.1 Pro Preview | Gemini APIGoogle DeepMind · observed Aug 29, 2026LMArena Text Arena text-2026-09-01-011508720696 score tableLMArena · observed Sep 3, 2026LMArena Vision Arena vision-2026-08-27-011508720696 score tableLMArena · observed Sep 3, 2026LiveBench 2026-06-25 score tableLiveBench · observed Sep 3, 2026LiveBench 2026-06-25 token accountingLiveBench · observed Sep 3, 2026

Questions

Qwen3.8 27B vs Gemini 3.1 Pro FAQs

Is Qwen3.8 27B or Gemini 3.1 Pro better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both Qwen3.8 27B and Gemini 3.1 Pro, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.

Which is cheaper, Qwen3.8 27B or Gemini 3.1 Pro?+

Qwen3.8 27B is $0.40 and Gemini 3.1 Pro is $2.00 per million tokens, so Qwen3.8 27B is cheaper on this metric. Qwen3.8 27B is $3.00 and Gemini 3.1 Pro is $12.00 per million tokens, so Qwen3.8 27B is cheaper on this metric.

Which has a larger context window, Qwen3.8 27B or Gemini 3.1 Pro?+

Gemini 3.1 Pro has the larger sourced context window. Qwen3.8 27B supports 262K and Gemini 3.1 Pro supports 1,049K.

Which performs better in benchmarks, Qwen3.8 27B or Gemini 3.1 Pro?+

Gemini 3.1 Pro leads the current overall benchmark count. The result uses 3 protocol-matched benchmarks from 2 publishers; it is not a universal quality score.

Can Qwen3.8 27B or Gemini 3.1 Pro be self-hosted?+

Qwen3.8 27B is the only model in this pair currently marked as self-hostable. Qwen3.8 27B is open weight; Gemini 3.1 Pro is not marked open weight.

Can Qwen3.8 27B and Gemini 3.1 Pro understand images?+

Qwen3.8 27B is documented with image input; Gemini 3.1 Pro is documented with image input. This reflects supported input modalities, not vision quality.

Which can generate longer answers, Qwen3.8 27B or Gemini 3.1 Pro?+

Qwen3.8 27B has the larger sourced maximum output: Qwen3.8 27B supports 131K and Gemini 3.1 Pro supports 66K output tokens.

Do Qwen3.8 27B and Gemini 3.1 Pro support reasoning and tool use?+

Qwen3.8 27B: reasoning, tool calling, and image input. Gemini 3.1 Pro: reasoning, tool calling, and image input. Feature support does not establish relative quality.

Which is available from more inference providers, Qwen3.8 27B or Gemini 3.1 Pro?+

Qwen3.8 27B has 3 sourced provider routes; Gemini 3.1 Pro has 2, so Qwen3.8 27B has broader tracked availability.

Which offers better value, Qwen3.8 27B or Gemini 3.1 Pro?+

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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