Qwen: Qwen3.5-122B-A10B
Analysis Summary
Qwen3.5-122B-A10B is a 122-billion parameter mixture-of-experts model from Alibaba's Qwen team, activating 10B parameters per forward pass. Its intelligence index of 32.3 and coding index of 45.7 place it in the strong mid-tier, and its agentic index of 62.3 confirms reliable multi-step task execution. Vision, tool use, and function calling are all supported, and instruction following (aa_ifbench 0.76) is consistent with the 27B sibling.
For businesses, the coding index makes it a credible option for software engineering assistance, code review, and technical content generation. The 262K context window supports long-document analysis, and the agentic score means it can handle structured automation pipelines. Its main limitation is that it sits well below frontier coding models like GPT-5.4 or Claude Opus 4.7.
At $0.26 input and $2.08 output per million tokens, it is exceptionally affordable for a model with confirmed coding and agentic capability. Teams needing a cost-effective coding and agentic workhorse for mid-complexity tasks will find it a strong value proposition.
Assessed June 30, 2026
Editorial notes
Qwen3.5-122B-A10B is a large MoE model with a coding index of 45.7, strong agentic performance, vision, tool use, and a 262K context at very low cost for its capability level.
Rankings consider pricing, capabilities, benchmarks, and real-world applicability and are refreshed as new models launch. Feedback?
Performance Profile
How Qwen: Qwen3.5-122B-A10B compares
Qwen: Qwen3.5-122B-A10B ranks #70 of 385 AI models we track for overall intelligence, #38 of 129 for coding, #54 of 293 for agentic tasks. Its 262K-token context window is larger than 81% of the models we list. At $0.26 per million input tokens it is cheaper than 46% of comparable models.
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..
Capabilities
Performance Indices
Source: Artificial Analysis
Benchmark Scores
Intelligence
Technical
Content
Benchmark data from Artificial Analysis and Hugging Face
How does Qwen: Qwen3.5-122B-A10B stack up?
Compare side-by-side with other professional models.
Model Information
| OpenRouter ID |
qwen/qwen3.5-122b-a10b
|
| Provider | qwen |
| Release Date | February 25, 2026 |
| Context Length | 262,144 tokens |
| Max Completion | 262,144 tokens |
| Status | Active |
Pricing
| Token Type | Cost per 1M tokens | Cost per 1K tokens |
|---|---|---|
| Input | $0.26 | $0.000260 |
| Output | $2.08 | $0.002080 |
Live Performance
Live endpoint metrics, refreshed every 30 minutes.
Leaderboard Categories
External Resources
Frequently asked questions about Qwen: Qwen3.5-122B-A10B
How much does Qwen: Qwen3.5-122B-A10B cost?
Qwen: Qwen3.5-122B-A10B costs $0.26 per million input tokens and $2.08 per million output tokens.
What is the context window of Qwen: Qwen3.5-122B-A10B?
Qwen: Qwen3.5-122B-A10B has a context window of 262,144 tokens (262K).
Is Qwen: Qwen3.5-122B-A10B good for coding?
On our coding benchmark index, Qwen: Qwen3.5-122B-A10B ranks #38 of 129 models, placing it in the broader range of the field for code generation and debugging.
What can Qwen: Qwen3.5-122B-A10B do?
Qwen: Qwen3.5-122B-A10B supports image/vision input, tool use, and function calling.
Who created Qwen: Qwen3.5-122B-A10B?
Qwen: Qwen3.5-122B-A10B is developed by Qwen and was released on February 25, 2026.
