MODEL PROOF
Qwen3.8 2.4T A95B
NOT INDEPENDENTLY RATED
No independent LMArena score is published for this model.
Serving precision differs between offers.
- Independent LMArena score
- Not independently rated
- Context window
- 1.05M
- Maximum output
- 131.07K
- Input modalities
- text
- Output modalities
- text
- Published input price
- $2.00 / 1M tokens
- Published output price
- $6.00 / 1M tokens
- Pricing kind
- fixed
Inspect complete billing conditions and endpoint terms below.
Price from Alibaba: the cheapest offer that is serving, at standard delivery and at the maker’s precision or better, at its standard rate.
Every price dimension · USD per million tokens
| Input | $2.00/M |
|---|---|
| Output | $6.00/M |
| Cached input | $0.250/M |
| Cache write | $2.50/M |
| Cache write 1h | Unknown/M |
| Reasoning | Unknown/M |
Who sells it
The same weights, different shops. Cheapest is not like-for-like when serving precision differs.
Headline cheapest is a lower precision. Like-for-like at the best declared precision is $2.00/M from SiliconFlow.
7 provider offers · rates, limits and conditions
Rates are USD per million tokens. Endpoint terms can differ even when the quoted price and precision match. A listed parameter is a provider declaration, not a task-success test.
| Seller | Input | Output | Precision | Uptime (1d) |
|---|---|---|---|---|
| SiliconFlowsiliconflow/fp8 Endpoint terms
| $2.00 | $6.00 | fp8 | 99.53% |
| DeepInfradeepinfra/fp4 Endpoint terms
| $2.00 | $6.00 | fp4 | 99.81% |
| Novitanovita Endpoint terms
| $2.00 | $6.00 | undeclared | 99.90% |
| Alibabaalibaba Endpoint terms
| $2.00 | $6.00 | undeclared | 99.90% |
| Venicevenice Endpoint terms
| $2.00 | $6.00 | undeclared | 99.77% |
| Modalmodal Endpoint terms
| $2.00 | $6.00 | undeclared | 98.91% |
| Togethertogether Endpoint terms
| $2.00 | $6.00 | undeclared | 99.96% |
Independent scores
No independent benchmark has measured this model. Unrated is not a score of zero.
Capability
| Context window | 1M |
|---|---|
| Max output | 131K |
| Input modes | text |
| Tool use | yes |
| Reasoning | always on |
| Open weights | yes |
Provenance
| Price source | openrouter.ai |
|---|---|
| Fetched | 2026-10-06 |
| Quality data | unrated |
| Cross-checked | vendor page |
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...
Questions this page answers
What does Qwen3.8 2.4T A95B cost?
$2.00/M in, $6.00/M out in this catalogue, as of the fetch date on this page. That is the API row, not a subscription.
Does Qwen3.8 2.4T A95B have an independent quality score?
Qwen3.8 2.4T A95B has no independent quality score in this catalogue. Unrated is not a score of zero.
What beats Qwen3.8 2.4T A95B?
Qwen3.8 2.4T A95B has no independent quality score. Unrated is not a score of zero.
Does this page use Artificial Analysis scores for Qwen3.8 2.4T A95B?
No. Artificial Analysis figures are not published here. Quality on this page is LMArena Elo where a score exists; otherwise the row is unrated.
Does a missing score mean Qwen3.8 2.4T A95B scored zero?
Unrated is not a score of zero.
Is the cheapest Qwen3.8 2.4T A95B endpoint the same product?
Headline cheapest is a lower precision. Like-for-like at the best declared precision is $2.00/M from SiliconFlow.
MODEL MONUMENT
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The verdict as one SVG, for a README or a docs page. It states this model's dominance status at the balanced workload on the LMArena lens, with the date it was computed, and it is rebuilt with the catalogue — so it changes when the verdict changes, including to one you would rather it did not.
[](https://undominated.ai/models/qwen__qwen3.8-2.4t-a95b/)<a href="https://undominated.ai/models/qwen__qwen3.8-2.4t-a95b/"><img src="https://undominated.ai/badge/qwen__qwen3.8-2.4t-a95b.svg" alt="Qwen3.8 2.4T A95B — Undominated.ai dominance verdict" height="36"></a>Direct file: https://undominated.ai/badge/qwen__qwen3.8-2.4t-a95b.svg — a static SVG, written by scripts/build-badges.mjs on every build, so the copy you embed is never
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