Qwen3.8 2.4T A95B vs Olmo 3 32B Think

At a Glance

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Pricing and Limits
Input priceFrom · USD / 1M tokens$2.00Deepinfra · Sep 23, 2026$0.15Openrouter · Aug 28, 2026
Output priceFrom · USD / 1M tokens$6.00Deepinfra · Sep 23, 2026$0.50Openrouter · Aug 28, 2026
Context windowMaximum documented tokens262K66K
Model facts checkedAug 28, 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 →
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-A95BOlmo-3-32B-Think
DeveloperQwenAi2
FamilyQwen3 8 2 4t A95bOlmo 3 32b Think
ModelQwen3.8-2.4T-A95BOlmo-3-32B-Think
VersionQwen3.8-2.4T-A95BOlmo-3-32B-Think
Lifecycleactiveactive
ReleasedUnknownUnknown
Knowledge cutoffUnknownUnknown
Input modalitiesTextText
Output modalitiesTextText
Context window262K66K
Total parameters2.4T32.2B
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)Openrouter (Standard)
Capabilitieschat, generation, reasoning, toolschat, generation, reasoning

Qwen3.8 2.4T A95B Capabilities

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

Olmo 3 32B Think Capabilities

chatgenerationreasoning
Serving providers1
Canonical IDallenai/Olmo-3-32B-Think

Primary Evidence

Sources and Freshness

Questions

Qwen3.8 2.4T A95B vs Olmo 3 32B Think FAQs

Is Qwen3.8 2.4T A95B or Olmo 3 32B Think better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both Qwen3.8 2.4T A95B and Olmo 3 32B Think, 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 Olmo 3 32B Think?+

Qwen3.8 2.4T A95B is $2.00 and Olmo 3 32B Think is $0.15 per million tokens, so Olmo 3 32B Think is cheaper on this metric. Qwen3.8 2.4T A95B is $6.00 and Olmo 3 32B Think is $0.50 per million tokens, so Olmo 3 32B Think is cheaper on this metric.

Which has a larger context window, Qwen3.8 2.4T A95B or Olmo 3 32B Think?+

Qwen3.8 2.4T A95B has the larger sourced context window. Qwen3.8 2.4T A95B supports 262K and Olmo 3 32B Think supports 66K.

Which performs better in benchmarks, Qwen3.8 2.4T A95B or Olmo 3 32B Think?+

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 Olmo 3 32B Think be self-hosted?+

Both models have the same recorded self-hosting status: supported. Qwen3.8 2.4T A95B is open weight; Olmo 3 32B Think is open weight.

Can Qwen3.8 2.4T A95B and Olmo 3 32B Think understand images?+

Qwen3.8 2.4T A95B is not documented with image input; Olmo 3 32B Think is not documented with image input. This reflects supported input modalities, not vision quality.

Which can generate longer answers, Qwen3.8 2.4T A95B or Olmo 3 32B Think?+

Neither has a larger sourced maximum output. Qwen3.8 2.4T A95B is — and Olmo 3 32B Think is 33K.

Do Qwen3.8 2.4T A95B and Olmo 3 32B Think support reasoning and tool use?+

Qwen3.8 2.4T A95B: reasoning and tool calling. Olmo 3 32B Think: reasoning. Feature support does not establish relative quality.

Which is available from more inference providers, Qwen3.8 2.4T A95B or Olmo 3 32B Think?+

Qwen3.8 2.4T A95B has 5 sourced provider routes; Olmo 3 32B Think has 1, so Qwen3.8 2.4T A95B has broader tracked availability.

Which offers better value, Qwen3.8 2.4T A95B or Olmo 3 32B Think?+

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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