Qwen3.8 2.4T A95B model profile

Profile facts

Profile type

Model research profile

Provider or publisher

Alibaba Qwen

Context window

1,048,576 tokens

Snapshot date

2026-10-13

Knowledge cutoff

Not disclosed

Reference catalog ID

qwen/qwen3.8-2.4t-a95b

When to pick Qwen3.8 2.4T A95B

Qwen3.8 2.4T A95B is a reference profile: Alibaba Qwen publishes it, Kendr documents it for comparison, and it carries no Kendr alias to call.

Each condition below is derived from this model's own values in the 2026-10-13 snapshot, compared only against models publishing the same field.

• Reach for it when a whole corpus has to fit in one prompt. The 1.05M-token context window is in the top quarter of the 167 models publishing a limit here, so long documents can go in whole rather than chunked.
• Reach for it when answer quality matters more than unit cost. It scores 39.9 on the Artificial Analysis intelligence index, above three quarters of the 119 models carrying that field in the 2026-10-13 snapshot.
• Reach for it when the model has to call tools. Tool calling is recorded in the snapshot, so this route can drive an agent loop rather than only answer in prose.
• Look elsewhere when you need to call it through Kendr today. This is a research reference profile with no Kendr alias. The facts and evidence here are published for comparison; the model is not routable on Kendr.
• Look elsewhere when the request is trivial and latency-sensitive. Reasoning is mandatory on this route and cannot be turned off, so short factual requests still pay reasoning tokens and reasoning latency.

Context, modalities, and identity

Qwen3.8 2.4T A95B accepts text and returns text. The snapshot records prompt caching, reasoning controls, structured output, text generation, and tool calling as capabilities or interfaces.

Provider or publisher

Alibaba Qwen

Context window

1,048,576 tokens

Maximum output

131,072 tokens

Input modalities

text

Output modalities

text

Knowledge cutoff

Not disclosed

Model overview

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, with 95 billion active parameters out of 2.4 trillion total. It is suited for coding, research, complex reasoning, and agentic workflows.

Reference model ID

qwen/qwen3.8-2.4t-a95b

Canonical version

qwen/qwen3.8-2.4t-a95b-20260812

Hugging Face ID

Qwen/Qwen3.8-2.4T-A95B

Capabilities and supported controls

Capabilities and parameters are reported from the dated catalog and source records; their presence does not guarantee identical behavior across every provider route.

Supported parameters

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

• prompt caching
• reasoning controls
• structured output
• text generation
• tool calling

Dated pricing snapshot

The dated reference snapshot lists $2 input and $6 output per million tokens. Cached input is $0.25 per million tokens.

These are dated third-party reference prices, not Kendr prices or an availability offer. Routes, tiers, caching, region, and provider policy can change the landed price.

Price date

2026-10-13

Input

$2 per 1M tokens

Cached input

$0.25 per 1M tokens

Output

$6 per 1M tokens

Provider routes, performance, and uptime

The snapshot retains 6 provider endpoints. Provider prices, context limits, p50 performance, and uptime can differ by route and are not Kendr guarantees.

Active provider endpoints

6

Best p50 latency

0.77 s

Best p50 throughput

113 tok/s

Availability with routing

99.92% over the sampled window

Availability without routing

97.68% over the sampled window

Performance date

2026-10-13

Benchmark evidence and limitations

The 2026-10-13 snapshot includes 3 Artificial Analysis indexes and AutoExacto results for 8 provider observations. Publisher-reported launch results are labeled and are not presented as Kendr measurements; scores from different suites are not treated as interchangeable.

Third-party catalog fields normalized from the cited model dataset; benchmark methodology and coverage differ by source.

Intelligence Index

39.9

Coding Index

71.9

Agentic Index

50.1

AutoExacto coverage

8 provider observations over 32 days

AutoExacto provider benchmarks

Rolling provider observations from the cited third-party benchmark view. The lookback is 32 days; GPQA Diamond and TAU-Bench Airline measure different abilities and should not be blended into one score.

Popularity and market context

Qwen3.8 2.4T A95B ranked #100 in the cited trailing-7-day third-party catalog usage dataset as of 2026-10-13. Observed within the cited trailing-7-day third-party catalog usage dataset; this is not global AI market share.

Third-party catalog rank

#100

Global market share

Not inferred

Observation date

2026-10-13

Frequently asked questions

Sources and evidence dates

1. Qwen3.8 2.4T A95B third-party catalog record (catalog, checked 2026-10-13)
2. Third-party model catalog methodology (methodology, checked 2026-10-13)
3. Alibaba Qwen official model documentation (primary, checked 2026-10-13)
4. Artificial Analysis capability indices methodology (benchmark, checked 2026-10-13)
5. Qwen3.8 2.4T A95B third-party catalog record (benchmark, checked 2026-10-13)