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Qwen3.8 2.4T A95B

Qwen

Qwen3.8 2.4T A95B is an open-weight sparse mixture-of-experts model from Qwen and the open-weight variant of [Qwen3.8 Max](/qwen/qwen3.8-max), with 95 billion active parameters out of 2.4 trillion total. It is...

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data quality56

Updated 9 h ago · first seen 11 Sept 2026

model_01M294WVRHZ940DGTKHNEEH0P7

Overview

Identity

Identity block not returned by the API for this entity.

Openness

Openness not classified yet — no sourced evidence to place this model in the ontology.

Key facts

Release date

Source:OpenRouter public model & pricing listingT2observed 12 h agomedium

Openrouter id

Source:OpenRouter public model & pricing listingT2observed 12 h agomedium

Architecture

Tokenizer

Source:OpenRouter public model & pricing listingT2observed 12 h agomedium

Hugging Face repo

Source:OpenRouter public model & pricing listingT2observed 12 h agomedium

Capabilities

Modalities

Modalities
text
Input
text
Output
text

Capabilities

  • Tool calling

    Yes

    OpenRouter public model & pricing listing · T2

  • Structured output

    Yes

    OpenRouter public model & pricing listing · T2

  • Reasoning

    Yes

    OpenRouter public model & pricing listing · T2

  • Vision

    Unavailable

  • Audio

    Unavailable

  • Fine-tuning available

    Unavailable

Context window

Source:OpenRouter public model & pricing listingT2observed 9 h agomedium

Max output

Source:OpenRouter public model & pricing listingT2observed 12 h agomedium

Tokenizer

Source:OpenRouter public model & pricing listingT2observed 12 h agomedium

Benchmarks6

Compare with another model →

Comparable same task and conditions · Partially comparable same task, conditions differ (effort, temperature, judge) · Not comparable different variant or metric

No benchmark results recorded

Results appear when a tier 1–3 source publishes them; we never copy scores without a source.

Providers & Pricing3

All offers in the price terminal →
Current prices per 1M tokens
ProviderInput / 1MOutput / 1MCached inBatch in / outContextObservedSource
OpenRouterqwen/qwen3.8-2.4t-a95b$2$6$0.25—1M8 h agoopenrouter.aiT2
OpenRouterqwen/qwen3.8-2.4t-a95b:batch$2$6$0.25—1.01M8 h agoopenrouter.aiT2
Together AIqwen3-8-max$2$6$0.25$2 / $6—10 h agotogether.aiT1

USD per 1M tokens as published by each provider (USD). Rows are append-only: every change is kept in the history below.

Price history

Step lines per provider; amber markers are recorded changes. Click a marker or a row for the evidence behind that price.

Output price · USD / 1M tokens 2 providers

Output price history of Qwen3.8 2.4T A95B$0$2$4$6$8Sept 26Sept 26Sept 26Sept 26OpenRouter: first observed → $6 · 11 Sept 2026Together AI: first observed → $6 · 11 Sept 2026
  • OpenRouter
  • Together AI
  • Together AIfirst observed $611 Sept 2026
  • OpenRouterfirst observed $611 Sept 2026

Input price · USD / 1M tokens 2 providers

Input price history of Qwen3.8 2.4T A95B$0$0.50$1$1.5$2$2.5Sept 26Sept 26Sept 26Sept 26OpenRouter: first observed → $2 · 11 Sept 2026Together AI: first observed → $2 · 11 Sept 2026
  • OpenRouter
  • Together AI
  • Together AIfirst observed $211 Sept 2026
  • OpenRouterfirst observed $211 Sept 2026

Timeline12

Full timeline →

Change history18

Temporal, append-only claims: a new observation closes the previous claim instead of overwriting it. Rewind the record with the as-of picker.

Viewing AI Atlas as of 12 Aug 2026 — attributes exactly as the atlas knew them on that day; later corrections are not shown.

Back to today →

Qwen3.8 2.4T A95B was not yet in AI Atlas on 12 Aug 2026

First seen 11 Sept 2026. Nothing is inferred backwards: no attribute is shown for dates before the first observation.
18 claims · 16 properties

Release daterelease_date1

Claim history for Release date
ValueValid from → toStatusSourceConfidenceExtractor
12 Aug 2026 → currentcurrentOpenRouter public model & pricing listingT2mediumdeterministic

Opennessopenness1

Claim history for Openness
ValueValid from → toStatusSourceConfidenceExtractor
open-weights → currentcurrentArtificial AnalysisT2mediumdeterministic

Context windowcontext_length3

Claim history for Context window
ValueValid from → toStatusSourceConfidenceExtractor
1.05M tokens → currentcurrentOpenRouter public model & pricing listingT2mediumdeterministic
983.6K tokens → supersededArtificial AnalysisT2mediumdeterministic
1.05M tokens → supersededOpenRouter public model & pricing listingT2mediumdeterministic

Max outputmax_output_tokens1

Claim history for Max output
ValueValid from → toStatusSourceConfidenceExtractor
131.1K tokens → currentcurrentOpenRouter public model & pricing listingT2mediumdeterministic

Modalitiesmodalities1

Claim history for Modalities
ValueValid from → toStatusSourceConfidenceExtractor
text → currentcurrentOpenRouter public model & pricing listingT2mediumdeterministic

Input modalitiesmodalities_input1

Claim history for Input modalities
ValueValid from → toStatusSourceConfidenceExtractor
text → currentcurrentOpenRouter public model & pricing listingT2mediumdeterministic

Output modalitiesmodalities_output1

Claim history for Output modalities
ValueValid from → toStatusSourceConfidenceExtractor
text → currentcurrentOpenRouter public model & pricing listingT2mediumdeterministic

Tokenizertokenizer1

Claim history for Tokenizer
ValueValid from → toStatusSourceConfidenceExtractor
Qwen → currentcurrentOpenRouter public model & pricing listingT2mediumdeterministic

Hugging Face repohf_repo1

Claim history for Hugging Face repo
ValueValid from → toStatusSourceConfidenceExtractor
Qwen/Qwen3.8-2.4T-A95B → currentcurrentOpenRouter public model & pricing listingT2mediumdeterministic

Descriptiondescription1

Claim history for Description
ValueValid from → toStatusSourceConfidenceExtractor
Qwen3.8 2.4T A95B is an open-weight sparse mixture-of-experts model from Qwen and the open-weight variant of [Qwen3.8 Max](/qwen/qwen3.8-max), with 95 billion active parameters out of 2.4 trillion total. It is... → currentcurrentOpenRouter public model & pricing listingT2mediumdeterministic

Aa median output tokens per secondmetric.aa_median_output_tokens_per_second1

Claim history for Aa median output tokens per second
ValueValid from → toStatusSourceConfidenceExtractor
38.3 → currentcurrentArtificial AnalysisT2mediumdeterministic

Openrouter idopenrouter_id1

Claim history for Openrouter id
ValueValid from → toStatusSourceConfidenceExtractor
qwen/qwen3.8-2.4t-a95b → currentcurrentOpenRouter public model & pricing listingT2mediumdeterministic

Reasoningreasoning1

Claim history for Reasoning
ValueValid from → toStatusSourceConfidenceExtractor
Yes → currentcurrentOpenRouter public model & pricing listingT2mediumdeterministic

Structured outputstructured_output1

Claim history for Structured output
ValueValid from → toStatusSourceConfidenceExtractor
Yes → currentcurrentOpenRouter public model & pricing listingT2mediumdeterministic

Supported parameterssupported_parameters1

Claim history for Supported parameters
ValueValid from → toStatusSourceConfidenceExtractor
frequency_penalty, include_reasoning, logit_bias, logprobs, max_tokens, min_p, presence_penalty, reasoning, reasoning_effort, repetition_penalty, response_format, seed, stop, structured_outputs, temperature, tool_choice, tools, top_k, top_logprobs, top_p → currentcurrentOpenRouter public model & pricing listingT2mediumdeterministic

Tool callingtool_calling1

Claim history for Tool calling
ValueValid from → toStatusSourceConfidenceExtractor
Yes → currentcurrentOpenRouter public model & pricing listingT2mediumdeterministic

Claims are temporal and append-only: a new observation closes the previous claim (valid_to) instead of overwriting it. Conflicting claims from different sources are kept side by side and flagged — never averaged. Methodology →

Provenance

Attributed facts

16

Source tiers

T216

Freshest observation

9 h ago

Conflicts

None

Source documents 3

Source documents
SourceDocumentTypeTierLast observedSnapshots
Together AI — pricingtogether.ai/pricing pricingT1· Official10 h ago1
OpenRouter public model & pricing listingopenrouter.ai/api/v1/models catalogueT2· Quality secondary8 h ago4
Artificial Analysisartificialanalysis.ai/leaderboards/models leaderboardT2· Quality secondary10 h ago1

Tier 1 = official/primary, 2 = quality secondary, 3 = community, 4 = unverified. Every snapshot is archived; see all sources and the methodology.

Data quality (56/100) measures how well AI Atlas knows this entity — completeness, primary-source ratio, freshness, conflicts — never how good the model is. Methodology →