Alibaba (Qwen), open weights

# Qwen3.5 122B-A10B

> Qwen3.5 122B-A10B by Alibaba (Qwen), released February 2026. Ranked #119 of 354 with a Noometry Index of 42.1. API: $0.40 in / $3.20 out per M tokens. 262K context. Scores, sources and comparisons.
- Canonical page: https://noometry.com/models/qwen3-5-122b-a10b
- Last updated: 2026-10-10
- Title: Qwen3.5 122B-A10B Benchmarks, Price & Rank (October 2026)

Qwen3.5 122B-A10B by Alibaba (Qwen) ranks 119th of 354 ranked models on the Noometry Index as of October 2026, with a score of 42.1. Its strongest category is multimodal, where it ranks 57th. API pricing starts at $0.40 per million input tokens and $3.20 per million output tokens, with a 262K-token context window.

Last verified October 10, 2026

## Specifications

- **Noometry rank:** #119 of 354
- **Index score:** 42.1
- **Evidence:** Confirmed 27 results
- **Provider:** [![](/logos/alibaba.svg) Alibaba (Qwen)](https://noometry.com/providers/alibaba)
- **Released:** February 23, 2026
- **Weights:** Open weights
- **Reasoning:** Yes
- **Context window:** 262K
- **Max output:** 66K
- **Input price:** $0.40 / M
- **Output price:** $3.20 / M
- **Blended price:** $1.10 / M
- **Output speed:** Not measured
- **Value:** #124 of 219
- **Knowledge cutoff:** Unknown
- **Input:** text, image, video, audio
- **Hugging Face:** [Qwen/Qwen3.5-122B-A10B](https://huggingface.co/Qwen/Qwen3.5-122B-A10B)

## Category scores

Each category score combines every public result we have in that category.

Qwen3.5 122B-A10B category scores

1.  Coding 39.1
2.  Reasoning 27.2
3.  Math 39.1
4.  Knowledge 38.8
5.  Multimodal 39.6
6.  Multilingual 51.6
7.  Instruction Following 73.8
8.  Long Context 43.0
9.  Writing & Preference 60.0
10.  020406080

Qwen3.5 122B-A10B category ranks
| Category | Score | Rank | Results |
| --- | --- | --- | --- |
| [Coding](https://noometry.com/best/coding) | 39.1 | #162 | 3 |
| [Reasoning](https://noometry.com/best/reasoning) | 27.2 | #123 | 7 |
| [Math](https://noometry.com/best/math) | 39.1 | #112 | 1 |
| [Knowledge](https://noometry.com/best/knowledge) | 38.8 | #142 | 2 |
| [Multimodal](https://noometry.com/best/multimodal) | 39.6 | #57 | 1 |
| [Multilingual](https://noometry.com/best/multilingual) | 51.6 | #107 | 1 |
| [Instruction Following](https://noometry.com/best/instruction-following) | 73.8 | #115 | 1 |
| [Long Context](https://noometry.com/best/long-context) | 43.0 | #109 | 1 |
| [Writing & Preference](https://noometry.com/best/writing) | 60.0 | #105 | 3 |

## Strengths and weaknesses

Categories where Qwen3.5 122B-A10B places highest and lowest among the models ranked in each, with its score against that category's median.

### Strongest categories

Qwen3.5 122B-A10B: strongest categories
| Category | Score | vs median | Rank |
| --- | --- | --- | --- |
| [Writing & Preference](https://noometry.com/best/writing) | 60.0 | +6.2 | #105 of 312, top 34% |
| [Math](https://noometry.com/best/math) | 39.1 | +2.6 | #112 of 327, top 35% |
| [Reasoning](https://noometry.com/best/reasoning) | 27.2 | +3.6 | #123 of 350, top 36% |

### Weakest categories

Qwen3.5 122B-A10B: weakest categories
| Category | Score | vs median | Rank |
| --- | --- | --- | --- |
| [Coding](https://noometry.com/best/coding) | 39.1 | +0.4 | #162 of 340, top 48% |
| [Knowledge](https://noometry.com/best/knowledge) | 38.8 | +1.5 | #142 of 314, top 46% |
| [Multimodal](https://noometry.com/best/multimodal) | 39.6 | +1.1 | #57 of 128, top 45% |

## Closest competitors

The models ranked just above and below Qwen3.5 122B-A10B. When scores are this close, price and speed are often the better way to choose.

Models ranked closest to Qwen3.5 122B-A10B
| Model | Rank | Score | Blended $/M | Speed |  |
| --- | --- | --- | --- | --- | --- |
| [DeepSeek-R1](https://noometry.com/models/deepseek-r1) | #115 | 42.3 | $0.91 | 10 | [Compare](https://noometry.com/compare/deepseek-r1-vs-qwen3-5-122b-a10b) |
| [Step 3.5 Flash](https://noometry.com/models/step-3-5-flash) | #116 | 42.3 | $0.15 | — | [Compare](https://noometry.com/compare/qwen3-5-122b-a10b-vs-step-3-5-flash) |
| [Qwen3.6 27B](https://noometry.com/models/qwen3-6-27b) | #117 | 42.2 | $1.35 | — | [Compare](https://noometry.com/compare/qwen3-5-122b-a10b-vs-qwen3-6-27b) |
| [Amazon Nova Experimental Chat 10 20](https://noometry.com/models/amazon-nova-experimental-chat-10-20) | #118 | 42.1 | — | — | [Compare](https://noometry.com/compare/amazon-nova-experimental-chat-10-20-vs-qwen3-5-122b-a10b) |
| [Longcat Flash Chat](https://noometry.com/models/longcat-flash-chat) | #120 | 42.1 | — | 69 | [Compare](https://noometry.com/compare/longcat-flash-chat-vs-qwen3-5-122b-a10b) |
| [Solar Pro4](https://noometry.com/models/solar-pro4) | #121 | 42.1 | $0.52 | — | [Compare](https://noometry.com/compare/qwen3-5-122b-a10b-vs-solar-pro4) |
| [GLM-4.5](https://noometry.com/models/glm-4-5) | #122 | 42.0 | $1 | 32 | [Compare](https://noometry.com/compare/glm-4-5-vs-qwen3-5-122b-a10b) |
| [Qwen3.5 35B-A3B](https://noometry.com/models/qwen3-5-35b-a3b) | #123 | 42.0 | $0.69 | — | [Compare](https://noometry.com/compare/qwen3-5-122b-a10b-vs-qwen3-5-35b-a3b) |

Sponsored placements are available on pages like this one. [Advertise on Noometry](https://noometry.com/advertise)

## Benchmark results

Every published result we track, with its source. Bold rows are the ones used for ranking; where several exist we prefer independent runs over self-reported numbers.

### Coding

Qwen3.5 122B-A10B Coding benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [LMArena WebDev](https://noometry.com/benchmarks/arena-webdev) | 1360 | #84 of 113, top 75% |  | [LMArena](https://lmarena.ai/leaderboard/webdev) | 2026-10-08 |
| [SciCode](https://noometry.com/benchmarks/scicode) | 35.6% | #98 of 121, top 81% | none | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [LMArena Coding](https://noometry.com/benchmarks/arena-coding) | 1436 | #104 of 294, top 36% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

### Reasoning

Qwen3.5 122B-A10B Reasoning benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [NYT Connections (extended)](https://noometry.com/benchmarks/nyt-connections) | 51.7% | #62 of 91, top 69% |  | [Lech Mazur benchmarks](https://github.com/lechmazur/nyt-connections) |  |
| [CritPt](https://noometry.com/benchmarks/critpt) | 0.9% | #84 of 134, top 63% | none | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [Thematic Generalization](https://noometry.com/benchmarks/thematic-generalization) | 51.2% | #16 of 23, top 70% |  | [Lech Mazur benchmarks](https://github.com/lechmazur/generalization) |  |
| [LMArena Hard Prompts](https://noometry.com/benchmarks/arena-hard-prompts) | 1421 | #104 of 297, top 36% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [Mystery Game Puzzles](https://noometry.com/benchmarks/mystery-game-puzzles) | 17% | #51 of 74, top 69% | none | [Epoch AI](https://epoch.ai/benchmarks) | 2026-08-27 |
| [DTBench](https://noometry.com/benchmarks/dtbench) | 84.3% | #56 of 151, top 38% | none | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [LMCA](https://noometry.com/benchmarks/lmca) | 32.2% | #69 of 125, top 56% | none | [Epoch AI](https://epoch.ai/benchmarks) |  |

### Math

Qwen3.5 122B-A10B Math benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [LMArena Math](https://noometry.com/benchmarks/arena-math) | 1432 | #82 of 285, top 29% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

### Knowledge

Qwen3.5 122B-A10B Knowledge benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [Vectara Hallucination Rate](https://noometry.com/benchmarks/vectara-hallucination) (lower is better) | 11.2% | #67 of 96, top 70% |  | [Vectara Hallucination Leaderboard](https://github.com/vectara/hallucination-leaderboard) |  |
| [LMArena Expert](https://noometry.com/benchmarks/arena-expert) | 1432 | #94 of 273, top 35% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

### Multimodal

Qwen3.5 122B-A10B Multimodal benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [LMArena Vision](https://noometry.com/benchmarks/arena-vision) | 1245 | #61 of 122, top 50% |  | [LMArena](https://lmarena.ai/leaderboard/vision) | 2026-10-09 |

### Multilingual

Qwen3.5 122B-A10B Multilingual benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [LMArena Non-English](https://noometry.com/benchmarks/arena-non-english) | 1400 | #106 of 297, top 36% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Chinese](https://noometry.com/benchmarks/arena-chinese) | 1462 | #88 of 285, top 31% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena French](https://noometry.com/benchmarks/arena-french) | 1442 | #82 of 223, top 37% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena German](https://noometry.com/benchmarks/arena-german) | 1426 | #71 of 231, top 31% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Japanese](https://noometry.com/benchmarks/arena-japanese) | 1367 | #89 of 211, top 43% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Korean](https://noometry.com/benchmarks/arena-korean) | 1352 | #103 of 213, top 49% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Russian](https://noometry.com/benchmarks/arena-russian) | 1400 | #104 of 283, top 37% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Spanish](https://noometry.com/benchmarks/arena-spanish) | 1424 | #87 of 226, top 39% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

### Instruction Following

Qwen3.5 122B-A10B Instruction Following benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [LMArena Instruction Following](https://noometry.com/benchmarks/arena-instruction-following) | 1399 | #108 of 298, top 37% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

### Long Context

Qwen3.5 122B-A10B Long Context benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [LMArena Longer Query](https://noometry.com/benchmarks/arena-longer-query) | 1410 | #106 of 291, top 37% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

### Writing & Preference

Qwen3.5 122B-A10B Writing & Preference benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [LMArena Text](https://noometry.com/benchmarks/arena-text) | 1417 | #100 of 297, top 34% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Creative Writing](https://noometry.com/benchmarks/arena-creative-writing) | 1368 | #112 of 295, top 38% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Multi-Turn](https://noometry.com/benchmarks/arena-multi-turn) | 1416 | #100 of 295, top 34% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

## API pricing by provider

Qwen3.5 122B-A10B API prices
| Route | Input $/M | Output $/M | Cached input $/M | Checked |
| --- | --- | --- | --- | --- |
| [alibaba](https://www.alibabacloud.com/help/en/model-studio/models) | $0.40 | $3.20 | — | 2026-10-10 |
| [deepinfra](https://deepinfra.com/models) | $0.29 | $2.40 | — | 2026-10-10 |
| [openrouter](https://openrouter.ai/qwen/qwen3.5-122b-a10b) | $0.26 | $2.08 | — | 2026-10-10 |

[All Alibaba (Qwen) API prices →](https://noometry.com/llm-pricing/alibaba) [Estimate your cost →](https://noometry.com/tools/cost-calculator)

## Compare Qwen3.5 122B-A10B

-   [Qwen3.5 122B-A10B vs Qwen3.5 397B-A17B](https://noometry.com/compare/qwen3-5-122b-a10b-vs-qwen3-5-397b-a17b)
-   [Qwen3.5 122B-A10B vs Amazon Nova Experimental Chat 10 20](https://noometry.com/compare/amazon-nova-experimental-chat-10-20-vs-qwen3-5-122b-a10b)
-   [Qwen3.5 122B-A10B vs Longcat Flash Chat](https://noometry.com/compare/longcat-flash-chat-vs-qwen3-5-122b-a10b)
-   [Qwen3.5 122B-A10B vs Qwen3.6 27B](https://noometry.com/compare/qwen3-5-122b-a10b-vs-qwen3-6-27b)
-   [Qwen3.5 122B-A10B vs Solar Pro4](https://noometry.com/compare/qwen3-5-122b-a10b-vs-solar-pro4)
-   [Qwen3.5 122B-A10B vs Step 3.5 Flash](https://noometry.com/compare/qwen3-5-122b-a10b-vs-step-3-5-flash)
-   [Qwen3.5 122B-A10B vs GLM-4.5](https://noometry.com/compare/glm-4-5-vs-qwen3-5-122b-a10b)
-   [Qwen3.5 122B-A10B vs GPT-6 Astra](https://noometry.com/compare/gpt-6-astra-vs-qwen3-5-122b-a10b)
-   [Qwen3.5 122B-A10B vs Claude Fable 5.1](https://noometry.com/compare/claude-fable-5-1-vs-qwen3-5-122b-a10b)
-   [Qwen3.5 122B-A10B vs Gemini 3.8 Flash](https://noometry.com/compare/gemini-3-8-flash-vs-qwen3-5-122b-a10b)
-   [Qwen3.5 122B-A10B vs Kimi K3](https://noometry.com/compare/kimi-k3-vs-qwen3-5-122b-a10b)
-   [Qwen3.5 122B-A10B vs Grok 4.6](https://noometry.com/compare/grok-4-6-vs-qwen3-5-122b-a10b)
-   [Qwen3.5 122B-A10B vs GLM-5.3](https://noometry.com/compare/glm-5-3-vs-qwen3-5-122b-a10b)
-   [Qwen3.5 122B-A10B vs Muse Spark 1.3](https://noometry.com/compare/muse-spark-1-3-vs-qwen3-5-122b-a10b)

## Other Alibaba (Qwen) models

-   [Qwen3.8 Max](https://noometry.com/models/qwen3-8-max)56.8
-   [Qwen3.7 Max](https://noometry.com/models/qwen3-7-max)51.5
-   [Qwen3.6 Max Preview](https://noometry.com/models/qwen3-6-max-preview)51.5
-   [Qwen3.6 Plus](https://noometry.com/models/qwen3-6-plus)47.5
-   [Qwen3.5 397B-A17B](https://noometry.com/models/qwen3-5-397b-a17b)46.0
-   [Qwen3.8 27B](https://noometry.com/models/qwen3-8-27b)46.0
-   [Qwen3.5 Max Preview](https://noometry.com/models/qwen3-5-max-preview)45.3
-   [Qwen3.7 Plus](https://noometry.com/models/qwen3-7-plus)45.3

## Frequently asked questions

### How good is Qwen3.5 122B-A10B?

Qwen3.5 122B-A10B by Alibaba (Qwen) ranks 119th of 354 ranked models on the Noometry Index as of October 2026, with a score of 42.1. Its strongest category is multimodal, where it ranks 57th. API pricing starts at $0.40 per million input tokens and $3.20 per million output tokens, with a 262K-token context window.

### How much does Qwen3.5 122B-A10B cost?

Qwen3.5 122B-A10B costs $0.40 per million input tokens and $3.20 per million output tokens on Alibaba (Qwen)'s own API.

### What is Qwen3.5 122B-A10B's context window?

Qwen3.5 122B-A10B accepts up to 262K tokens of input and can write up to 66K tokens in one response.

### Is Qwen3.5 122B-A10B open source?

Yes. Qwen3.5 122B-A10B's weights are downloadable from Hugging Face (Qwen/Qwen3.5-122B-A10B); check the license for commercial terms.

### What are Qwen3.5 122B-A10B's strengths and weaknesses?

Relative to other ranked models, Qwen3.5 122B-A10B places best in writing & preference, math, reasoning and lowest in coding, knowledge, multimodal.

### What is Qwen3.5 122B-A10B best at?

Its best category is multimodal, where it ranks 57th on Noometry.

### Cite this page

Noometry. (2026). Qwen3.5 122B-A10B benchmarks and pricing. Retrieved October 10, 2026, from https://noometry.com/models/qwen3-5-122b-a10b

Quote Noometry with a link back to this page. It is also available in [Markdown](https://noometry.com/md/models/qwen3-5-122b-a10b.md).