Qwen: Qwen3.5-122B-A10B API Pricing
Qwen: Qwen3.5-122B-A10B costs $0.260 per 1M input tokens and $2.08 per 1M output tokens. Context window: 262K. Prices verified 2026-10-21 · source
Alternatives to consider
96% cheaper with nearly identical quality (20.1 vs 17.7)
+27.1 quality points for 17% 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.
Higher effort = deeper thinking = more reasoning tokens billed as output.
What would Qwen: Qwen3.5-122B-A10B cost you per month?
| Workload | Requests/mo | Avg tokens (in/out) | Est. monthly cost |
|---|---|---|---|
| Light chatbot | 10,000 | 800 / 400 | $10.40 |
| Coding agent | 5,000 | 8,000 / 2,000 | $31.20 |
| RAG pipeline | 30,000 | 4,000 / 500 | $62.40 |
| Doc summarizer | 2,000 | 20,000 / 1,000 | $14.56 |
Estimates use list prices without prompt caching. Caching can cut input cost by up to 90% on repeated context.
About Qwen: Qwen3.5-122B-A10B
The Qwen3.5 122B-A10B native vision-language model is built on a hybrid architecture that integrates a linear attention mechanism with a sparse mixture-of-experts model, achieving higher inference efficiency. In terms of...
Compare Qwen: Qwen3.5-122B-A10B with
- Qwen: Qwen3.5-122B-A10B vs OpenAI: GPT-5.6 Terra Pro
- Qwen: Qwen3.5-122B-A10B vs Anthropic: Claude Fable 5
- Qwen: Qwen3.5-122B-A10B vs Anthropic: Claude Opus 5
- Qwen: Qwen3.5-122B-A10B vs OpenAI: GPT-5.6 Sol
Popular head-to-heads — see all on the comparisons index.
Frequently asked questions
How much does Qwen: Qwen3.5-122B-A10B cost?
Qwen: Qwen3.5-122B-A10B costs $0.260 per 1M input tokens and $2.08 per 1M output tokens. Verified 2026-10-21 — provider source.
What is the context window?
262K tokens, with up to 66K output tokens per response. That's roughly 328 pages of text in a single request.
Does it support prompt caching?
Prompt-caching pricing is not published for this model via OpenRouter.
What's a cheaper alternative?
ScaleDown: Summarize saves about 96% on a typical workload with comparable quality.
Official resources
- Qwen: Qwen3.5-122B-A10B on OpenRouter — live endpoint, pricing source of record.
- Artificial Analysis leaderboard → — independent intelligence and performance rankings.
- Qwen GitHub → — official model repositories and release notes.
- Shred your current bill — paste a CSV and see if switching saves money.