Qwen3.8 2.4T A95B model profile
Evidence snapshot:
Qwen3.8 2.4T A95B is a Alibaba Qwen model profile with a 1,048,576-token context window. The dated catalog snapshot records text modalities and interfaces for prompt caching, reasoning controls, structured output, text generation, tool calling.
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...
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.
Qwen3.8 2.4T A95B is an independent knowledge profile. It does not claim that Kendr hosts the model, quote a Kendr customer price, promise API availability, or advertise a Kendr routing receipt.
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.
The dated reference snapshot lists $2 input and $6 output per million tokens. Cached input is $0.2 per million tokens.
The 2026-09-06 snapshot includes 3 Artificial Analysis indexes. Publisher-reported launch results are labeled and are not presented as Kendr measurements; scores from different suites are not treated as interchangeable.
No comparable popularity rank or traffic share is present in the 2026-09-06 snapshot. No comparable routing rank or traffic-share observation is attached to this dated profile; missing adoption evidence is not estimated.
Profile data was reviewed for the 2026-09-06 snapshot. Claims retain their source dates, and unavailable fields are shown as unavailable instead of estimated.
Profile facts
- Profile type
- Model research profile
- Provider or publisher
- Alibaba Qwen
- Context window
- 1,048,576 tokens
- Snapshot date
- 2026-09-06
- 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 2026-09-06 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 163 models publishing a limit here, so long documents can go in whole rather than chunked.
- 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
- 262,144 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...
- 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 $0.2 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
- 2026-09-06
- Input
- $2 per 1M tokens
- Cached input
- $0.2 per 1M tokens
- Output
- $6 per 1M tokens
Provider routes, performance, and uptime
The snapshot retains 7 provider endpoints. Provider prices, context limits, p50 performance, and uptime can differ by route and are not Kendr guarantees.
- Active provider endpoints
- 7
- Best p50 latency
- No recent metric
- Best p50 throughput
- No recent metric
- Availability with routing
- No recent metric
- Availability without routing
- No recent metric
- Performance date
- 2026-09-06
| Provider | Quantization | Input / 1M | Output / 1M | Cache read / 1M | Context | p50 latency | p50 throughput | Uptime (1d) |
|---|---|---|---|---|---|---|---|---|
| Novita | unknown | $2 / 1M | $6 / 1M | $0.25 / 1M | 1,000,000 tokens | No recent p50 | No recent p50 | 99.99% |
| Alibaba | unknown | $2 / 1M | $6 / 1M | $0.25 / 1M | 1,000,000 tokens | No recent p50 | No recent p50 | 99.98% |
| SiliconFlow | fp8 | $2 / 1M | $6 / 1M | $0.25 / 1M | 1,048,576 tokens | No recent p50 | No recent p50 | 99.97% |
| Modal | unknown | $2 / 1M | $6 / 1M | $0.25 / 1M | 1,000,000 tokens | No recent p50 | No recent p50 | 99.96% |
| DeepInfra | fp4 | $2 / 1M | $6 / 1M | $0.2 / 1M | 262,144 tokens | No recent p50 | No recent p50 | 98.35% |
| Together | unknown | $2 / 1M | $6 / 1M | $0.25 / 1M | 1,010,000 tokens | No recent p50 | No recent p50 | 99.94% |
| Venice | unknown | $2.5 / 1M | $7.5 / 1M | $0.3125 / 1M | 262,144 tokens | No recent p50 | No recent p50 | 99.99% |
Benchmark evidence and limitations
The 2026-09-06 snapshot includes 3 Artificial Analysis indexes. 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
- 46.7
- Coding Index
- 71.9
- Agentic Index
- 50.7
Popularity and market context
No comparable popularity rank or traffic share is present in the 2026-09-06 snapshot. No comparable routing rank or traffic-share observation is attached to this dated profile; missing adoption evidence is not estimated.
- Third-party catalog rank
- No verified rank
- Global market share
- Not inferred
- Observation date
- 2026-09-06
Frequently asked questions
When should I use 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. 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 163 models publishing a limit here, so long documents can go in whole rather than chunked. 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.
What is Qwen3.8 2.4T A95B?
Qwen3.8 2.4T A95B is a Alibaba Qwen model profile with a 1,048,576-token context window. The dated catalog snapshot records text modalities and interfaces for prompt caching, reasoning controls, structured output, text generation, tool calling.
What context window does Qwen3.8 2.4T A95B have?
The dated profile lists 1,048,576 tokens of context and up to 262,144 output tokens. Provider routes, variants, and runtime configuration can impose lower effective limits.
What benchmark evidence is available for Qwen3.8 2.4T A95B?
The 2026-09-06 snapshot includes 3 Artificial Analysis indexes. 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.
Is Qwen3.8 2.4T A95B available through Kendr?
This is an independent knowledge profile, not a Kendr-hosted availability claim. Check Kendr's live public model API for currently enabled Kendr aliases.
Does the popularity rank represent Qwen3.8 2.4T A95B's global market share?
No comparable popularity rank or traffic share is present in the 2026-09-06 snapshot. No comparable routing rank or traffic-share observation is attached to this dated profile; missing adoption evidence is not estimated. No global market-share percentage is inferred when the source does not publish one.
Sources and evidence dates
- Qwen3.8 2.4T A95B third-party catalog record (catalog, checked 2026-09-06)
- Third-party model catalog methodology (methodology, checked 2026-09-06)
- Alibaba Qwen official model documentation (primary, checked 2026-09-06)
- Artificial Analysis capability indices methodology (benchmark, checked 2026-09-06)