Qwen3.8 2.4T A95B vs Gemma 4 31B

At a Glance

Compare
Gemma 4 31BGoogle DeepMind
Pricing and Limits
Input priceFrom · USD / 1M tokens$2.00Deepinfra · Sep 21, 2026$0.090Openrouter · Sep 22, 2026
Output priceFrom · USD / 1M tokens$6.00Deepinfra · Sep 21, 2026$0.34Openrouter · Sep 22, 2026
Context windowMaximum documented tokens262K262K
Model facts checkedAug 28, 2026View model evidence →Sep 3, 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 →
No Protocol-Matched Benchmark Yet.Results appear here only when both models share the same benchmark version, metric, evaluation protocol, and evidence class.

Side-by-Side Facts

FieldQwen3.8-2.4T-A95BGemma 4 31B
DeveloperQwenGoogle DeepMind
FamilyQwen3 8 2 4t A95bGemma 4
ModelQwen3.8-2.4T-A95BGemma 4 31B
VersionQwen3.8-2.4T-A95BGemma 4 31B
Lifecycleactiveactive
ReleasedUnknown2026-03-11
Knowledge cutoffUnknownUnknown
Input modalitiesTextText, Image
Output modalitiesTextText
Context window262K262K
Total parameters2.4T31B
Active parameters95BUnknown
Licenseotherapache-2.0
Open weightsYesYes
API availableYesYes
Self-hostableYesYes
Provider accessDeepinfra (Standard), Fireworks Ai (Standard), Hugging Face (Standard), Openrouter (Standard), Together Ai (Standard)Cerebras (Standard), Deepinfra (Standard), Google Gemini (Standard), Openrouter (Standard), Together Ai (Standard)
Capabilitieschat, generation, reasoning, toolschat, generation, reasoning, structured_outputs, tools

Qwen3.8 2.4T A95B Capabilities

chatgenerationreasoningtools
Serving providers5
Canonical IDQwen/Qwen3.8-2.4T-A95B

Gemma 4 31B Capabilities

chatgenerationreasoningstructured outputstools
Serving providers5
Canonical IDgoogle/gemma-4-31B-it

Primary Evidence

Sources and Freshness

Questions

Qwen3.8 2.4T A95B vs Gemma 4 31B FAQs

Is Qwen3.8 2.4T A95B or Gemma 4 31B better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both Qwen3.8 2.4T A95B and Gemma 4 31B, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.

Which is cheaper, Qwen3.8 2.4T A95B or Gemma 4 31B?+

Qwen3.8 2.4T A95B is $2.00 and Gemma 4 31B is $0.090 per million tokens, so Gemma 4 31B is cheaper on this metric. Qwen3.8 2.4T A95B is $6.00 and Gemma 4 31B is $0.34 per million tokens, so Gemma 4 31B is cheaper on this metric.

Which has a larger context window, Qwen3.8 2.4T A95B or Gemma 4 31B?+

Neither model has a larger sourced context window in this comparison. Qwen3.8 2.4T A95B is 262K and Gemma 4 31B is 262K.

Which performs better in benchmarks, Qwen3.8 2.4T A95B or Gemma 4 31B?+

There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.

Can Qwen3.8 2.4T A95B or Gemma 4 31B be self-hosted?+

Both models have the same recorded self-hosting status: supported. Qwen3.8 2.4T A95B is open weight; Gemma 4 31B is open weight.

Can Qwen3.8 2.4T A95B and Gemma 4 31B understand images?+

Qwen3.8 2.4T A95B is not documented with image input; Gemma 4 31B is documented with image input. This reflects supported input modalities, not vision quality.

Which can generate longer answers, Qwen3.8 2.4T A95B or Gemma 4 31B?+

Neither has a larger sourced maximum output. Qwen3.8 2.4T A95B is — and Gemma 4 31B is —.

Do Qwen3.8 2.4T A95B and Gemma 4 31B support reasoning and tool use?+

Qwen3.8 2.4T A95B: reasoning and tool calling. Gemma 4 31B: reasoning, tool calling, and image input. Feature support does not establish relative quality.

Which is available from more inference providers, Qwen3.8 2.4T A95B or Gemma 4 31B?+

Qwen3.8 2.4T A95B has 5 sourced provider routes; Gemma 4 31B has 5, a tie.

Which offers better value, Qwen3.8 2.4T A95B or Gemma 4 31B?+

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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