Model profile
Alibaba
New in 2026

Qwen: Qwen3.8 2.4T A95B

Qwen: Qwen3.8 2.4T A95B is a mid-range-priced text-first model from Alibaba with heavy runtime profile, large context posture, and the clearest fit around long-context research / agent workflows.

Best for: Long-context research / Agent workflowsHeavy latencyLarge contextMid-range pricing
Intelligence
57.7

Benchmark blend

Coding
71.9

Dev workflow signal

Context
1049K Tokens

Large

Input Price
$2.00

Mid-range tier

Decision snapshot
66

Qwen: Qwen3.8 2.4T A95B currently reads as a mid-range text-first option with large context and a heavy runtime profile.

Overall profile
Selective fit
Best for
Long-context research / Agent workflows
Latency tier
Heavy
Price tier
Mid-range
Source coverage
OpenRouterArtificial Analysis

Decision Strip

Decision rail before the raw tables

Core buy-side signals stay in one pass. The rest of the page expands only after intelligence, speed, context, and price are clear.

Intelligence
57.7
58

General reasoning and benchmark headroom.

Situational
Speed
47 tok/s
48

TTFT 1.71s

Situational
Context
1049K Tokens
100

How much prompt and task state can stay in view.

Above average
Price
$2.00
62

$6.00 output / 1M

Competitive

Editorial Profile

Qwen: Qwen3.8 2.4T A95B in one narrative

Positioning, tradeoffs, and fit are consolidated into one read instead of repeating the same story across separate cards.

Selective fitCoding score 72Math score N/A

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...

Identity

Alibaba text-first profile

Positioning

Long-context research / Agent workflows with large context and heavy runtime.

Cost posture

Balanced spend profile. Easier to justify in mixed production and exploration workloads.

Strengths
  • Coding indicators point to a strong developer workflow fit.

  • Large context headroom supports repo-wide prompts and long research sessions.

Tradeoffs
  • Costs look manageable, but still deserve attention in always-on agents or batch jobs.

  • Latency profile is better for deliberate runs than rapid back-and-forth chat.

  • Current metadata points to a text-first profile rather than a broad multimodal one.

Best fit
  • Code generation, refactors, test writing, and tool-assisted debugging.

  • Long-context summarization, repo analysis, and policy or document review.

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Context
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Benchmarks

Grouped by job-to-be-done

Only benchmark categories with actual signal are shown. Secondary values stay as simple definitions instead of nested micro-cards.

General intelligence

Broad reasoning, knowledge depth, and flagship benchmark posture.

Intelligence Index
57.7
GPQA
93.5%
HLE
42.4%
Coding

Software implementation, debugging quality, and coding benchmark signal.

Coding Index
71.9
SciCode
51.6%
Agent / tool use

Long-horizon execution quality and interactive benchmark evidence.

LCR
75.3%

Extra benchmark cuts are not available for this category yet.

Specs & Pricing

Technical snapshot and cost posture

Specs stay neutral, pricing gets emphasis through values rather than extra containers. Raw provider internals remain in metadata at the end.

Technical snapshot
Context Window
1049K Tokens
Vision
Text-first
Modalities
text
Tokenizer
Qwen
Max Completion
262144
Moderation
No
Supported Parameters
frequency_penaltyinclude_reasoninglogit_biaslogprobsmax_tokensmin_ppresence_penaltyreasoningreasoning_effortrepetition_penaltyresponse_formatseedstopstructured_outputstemperaturetool_choicetoolstop_ktop_logprobstop_p
Input Modalities
text
Output Modalities
text
Price architecture
Input
per 1M input tokens
$2.00
Output
per 1M output tokens
$6.00
Blended
AA 3:1 mix
$3.00

This model sits in a balanced spend range. It is easier to justify across both production and exploratory workflows.

OR Cache Read
$0.00

Metadata

Raw source tables at the end

Verification details remain available, but the page no longer forces them ahead of the editorial read.