Qwen: Qwen3.8 2.4T A95B API Pricing
Qwen: Qwen3.8 2.4T A95B costs $2.00 per 1M input tokens and $6.00 per 1M output tokens (cache reads: $0.250). Context window: 1.0M. Prices verified 2026-10-21 · source
Alternatives to consider
86% cheaper with nearly identical quality (60 vs 58)
+2 quality points for 5% more
Rebuilt daily from our snapshot archive — the chart appears once a model has 5+ snapshots of history.
High adoption means battle-tested weights, more fine-tunes/quants, and faster bug fixes. View on HuggingFace →
From our own daily snapshot archive — independent of provider announcements.
Intelligence measures reasoning/knowledge/coding benchmarks. A high score with a low blended price = value pick; check the value chart to see where this model lands.
Token economics
| Token type | Price | vs base input |
|---|---|---|
| Standard input | $2.00 | — |
| Cache read | $0.250 | −88% |
| Output | $6.00 | — |
Prompt caching stores repeated context server-side: reads cost far less, but writes carry a one-time premium.
Higher effort = deeper thinking = more reasoning tokens billed as output.
What would Qwen: Qwen3.8 2.4T A95B cost you per month?
| Workload | Requests/mo | Avg tokens (in/out) | Est. monthly cost |
|---|---|---|---|
| Light chatbot | 10,000 | 800 / 400 | $40.00 |
| Coding agent | 5,000 | 8,000 / 2,000 | $140.00 |
| RAG pipeline | 30,000 | 4,000 / 500 | $330.00 |
| Doc summarizer | 2,000 | 20,000 / 1,000 | $92.00 |
Estimates use list prices without prompt caching. Caching can cut input cost by up to 90% on repeated context.
About Qwen: Qwen3.8 2.4T A95B
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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Frequently asked questions
How much does Qwen: Qwen3.8 2.4T A95B cost?
Qwen: Qwen3.8 2.4T A95B costs $2.00 per 1M input tokens and $6.00 per 1M output tokens; cached input tokens cost $0.250 per 1M. Verified 2026-10-21 — provider source.
What is the context window?
1.0M tokens, with up to 909K output tokens per response. That's roughly 1311 pages of text in a single request.
Does it support prompt caching?
Yes — cached input is $0.250/1M, about 88% cheaper than standard input. Agents and RAG workloads with repeated context benefit most.
What's a cheaper alternative?
ScaleDown: Summarize saves about 99% on a typical workload with comparable quality.
Official resources
- Qwen: Qwen3.8 2.4T A95B on OpenRouter — live endpoint, pricing source of record.
- Artificial Analysis benchmarks → — independent intelligence and performance analysis.
- Qwen GitHub → — official model repositories and release notes.
- Shred your current bill — paste a CSV and see if switching saves money.