Qwen3.8 2.4T A95B vs Gemini 2.5 Pro

At a Glance

Compare
Gemini 2.5 ProGoogle DeepMind
Pricing and Limits
Input priceFrom · USD / 1M tokens$2.00Deepinfra · Sep 22, 2026$1.25Google AI · Aug 29, 2026
Output priceFrom · USD / 1M tokens$6.00Deepinfra · Sep 22, 2026$10.00Google AI · Aug 29, 2026
Context windowMaximum documented tokens262K1,049K
Model facts checkedAug 28, 2026View model evidence →Aug 29, 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-A95BGemini 2.5 Pro
DeveloperQwenGoogle DeepMind
FamilyQwen3 8 2 4t A95bGemini 2 5
ModelQwen3.8-2.4T-A95BGemini 2.5 Pro
VersionQwen3.8-2.4T-A95BGemini 2.5 Pro
Lifecycleactiveactive
ReleasedUnknownUnknown
Knowledge cutoffUnknown2025-01-01
Input modalitiesTextText, Image, Video, Audio, Document
Output modalitiesTextText
Context window262K1,049K
Total parameters2.4TUnknown
Active parameters95BUnknown
LicenseotherUnknown
Open weightsYesNo
API availableYesYes
Self-hostableYesNo
Provider accessDeepinfra (Standard), Fireworks Ai (Standard), Hugging Face (Standard), Openrouter (Standard), Together Ai (Standard)Google AI (Standard), Google Gemini (Standard)
Capabilitieschat, generation, reasoning, toolschat, generation, reasoning, tools

Qwen3.8 2.4T A95B Capabilities

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

Gemini 2.5 Pro Capabilities

chatgenerationreasoningtools
Serving providers2
Canonical IDgoogle-deepmind/gemini-2.5-pro

Primary Evidence

Sources and Freshness

Questions

Qwen3.8 2.4T A95B vs Gemini 2.5 Pro FAQs

Is Qwen3.8 2.4T A95B or Gemini 2.5 Pro better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both Qwen3.8 2.4T A95B and Gemini 2.5 Pro, 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 Gemini 2.5 Pro?+

Qwen3.8 2.4T A95B is $2.00 and Gemini 2.5 Pro is $1.25 per million tokens, so Gemini 2.5 Pro is cheaper on this metric. Qwen3.8 2.4T A95B is $6.00 and Gemini 2.5 Pro is $10.00 per million tokens, so Qwen3.8 2.4T A95B is cheaper on this metric.

Which has a larger context window, Qwen3.8 2.4T A95B or Gemini 2.5 Pro?+

Gemini 2.5 Pro has the larger sourced context window. Qwen3.8 2.4T A95B supports 262K and Gemini 2.5 Pro supports 1,049K.

Which performs better in benchmarks, Qwen3.8 2.4T A95B or Gemini 2.5 Pro?+

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 Gemini 2.5 Pro be self-hosted?+

Qwen3.8 2.4T A95B is the only model in this pair currently marked as self-hostable. Qwen3.8 2.4T A95B is open weight; Gemini 2.5 Pro is not marked open weight.

Can Qwen3.8 2.4T A95B and Gemini 2.5 Pro understand images?+

Qwen3.8 2.4T A95B is not documented with image input; Gemini 2.5 Pro is documented with image input. This reflects supported input modalities, not vision quality.

Which can generate longer answers, Qwen3.8 2.4T A95B or Gemini 2.5 Pro?+

Neither has a larger sourced maximum output. Qwen3.8 2.4T A95B is — and Gemini 2.5 Pro is 66K.

Do Qwen3.8 2.4T A95B and Gemini 2.5 Pro support reasoning and tool use?+

Qwen3.8 2.4T A95B: reasoning and tool calling. Gemini 2.5 Pro: 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 Gemini 2.5 Pro?+

Qwen3.8 2.4T A95B has 5 sourced provider routes; Gemini 2.5 Pro has 2, so Qwen3.8 2.4T A95B has broader tracked availability.

Which offers better value, Qwen3.8 2.4T A95B or Gemini 2.5 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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