Alibaba (Qwen), open weights

# Qwen3.5 35B-A3B

> Qwen3.5 35B-A3B by Alibaba (Qwen), released February 2026. Ranked #123 of 354 with a Noometry Index of 42.0. API: $0.25 in / $2 out per M tokens. 262K context. Scores, sources and comparisons.
- Canonical page: https://noometry.com/models/qwen3-5-35b-a3b
- Last updated: 2026-10-10
- Title: Qwen3.5 35B-A3B Benchmarks, Price & Rank (October 2026)

Qwen3.5 35B-A3B by Alibaba (Qwen) ranks 123rd of 354 ranked models on the Noometry Index as of October 2026, with a score of 42.0. Its strongest category is knowledge, where it ranks 79th. API pricing starts at $0.25 per million input tokens and $2 per million output tokens, with a 262K-token context window.

Last verified October 10, 2026

## Specifications

- **Noometry rank:** #123 of 354
- **Index score:** 42.0
- **Evidence:** Confirmed 28 results
- **Provider:** [![](/logos/alibaba.svg) Alibaba (Qwen)](https://noometry.com/providers/alibaba)
- **Released:** February 1, 2026
- **Weights:** Open weights
- **Reasoning:** Yes
- **Context window:** 262K
- **Max output:** 66K
- **Input price:** $0.25 / M
- **Output price:** $2 / M
- **Blended price:** $0.69 / M
- **Output speed:** Not measured
- **Value:** #89 of 219
- **Knowledge cutoff:** January 2025
- **Input:** text, image, video, audio
- **Hugging Face:** [Qwen/Qwen3.5-35B-A3B](https://huggingface.co/Qwen/Qwen3.5-35B-A3B)

## Category scores

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

Qwen3.5 35B-A3B category scores

1.  Coding 33.8
2.  Reasoning 24.6
3.  Math 39.9
4.  Knowledge 47.8
5.  Multilingual 50.0
6.  Instruction Following 72.8
7.  Long Context 42.4
8.  Writing & Preference 57.9
9.  020406080

Qwen3.5 35B-A3B category ranks
| Category | Score | Rank | Results |
| --- | --- | --- | --- |
| [Coding](https://noometry.com/best/coding) | 33.8 | #251 | 3 |
| [Reasoning](https://noometry.com/best/reasoning) | 24.6 | #161 | 5 |
| [Math](https://noometry.com/best/math) | 39.9 | #97 | 3 |
| [Knowledge](https://noometry.com/best/knowledge) | 47.8 | #79 | 3 |
| [Multilingual](https://noometry.com/best/multilingual) | 50.0 | #127 | 1 |
| [Instruction Following](https://noometry.com/best/instruction-following) | 72.8 | #128 | 1 |
| [Long Context](https://noometry.com/best/long-context) | 42.4 | #127 | 1 |
| [Writing & Preference](https://noometry.com/best/writing) | 57.9 | #124 | 3 |

## Strengths and weaknesses

Categories where Qwen3.5 35B-A3B places highest and lowest among the models ranked in each, with its score against that category's median.

### Strongest categories

Qwen3.5 35B-A3B: strongest categories
| Category | Score | vs median | Rank |
| --- | --- | --- | --- |
| [Knowledge](https://noometry.com/best/knowledge) | 47.8 | +10.5 | #79 of 314, top 26% |
| [Math](https://noometry.com/best/math) | 39.9 | +3.3 | #97 of 327, top 30% |
| [Writing & Preference](https://noometry.com/best/writing) | 57.9 | +4.1 | #124 of 312, top 40% |

### Weakest categories

Qwen3.5 35B-A3B: weakest categories
| Category | Score | vs median | Rank |
| --- | --- | --- | --- |
| [Coding](https://noometry.com/best/coding) | 33.8 | −4.9 | #251 of 340, top 74% |
| [Reasoning](https://noometry.com/best/reasoning) | 24.6 | +1.0 | #161 of 350, top 46% |
| [Long Context](https://noometry.com/best/long-context) | 42.4 | +1.4 | #127 of 296, top 43% |

## Closest competitors

The models ranked just above and below Qwen3.5 35B-A3B. When scores are this close, price and speed are often the better way to choose.

Models ranked closest to Qwen3.5 35B-A3B
| Model | Rank | Score | Blended $/M | Speed |  |
| --- | --- | --- | --- | --- | --- |
| [Qwen3.5 122B-A10B](https://noometry.com/models/qwen3-5-122b-a10b) | #119 | 42.1 | $1.10 | — | [Compare](https://noometry.com/compare/qwen3-5-122b-a10b-vs-qwen3-5-35b-a3b) |
| [Longcat Flash Chat](https://noometry.com/models/longcat-flash-chat) | #120 | 42.1 | — | 69 | [Compare](https://noometry.com/compare/longcat-flash-chat-vs-qwen3-5-35b-a3b) |
| [Solar Pro4](https://noometry.com/models/solar-pro4) | #121 | 42.1 | $0.52 | — | [Compare](https://noometry.com/compare/qwen3-5-35b-a3b-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-qwen3-5-35b-a3b) |
| [GLM-4.7](https://noometry.com/models/glm-4-7) | #124 | 42.0 | $1 | — | [Compare](https://noometry.com/compare/glm-4-7-vs-qwen3-5-35b-a3b) |
| [GPT-5.4 nano](https://noometry.com/models/gpt-5-4-nano) | #125 | 41.9 | $0.46 | 19 | [Compare](https://noometry.com/compare/gpt-5-4-nano-vs-qwen3-5-35b-a3b) |
| [Amazon Nova Experimental Chat 10 09](https://noometry.com/models/amazon-nova-experimental-chat-10-09) | #126 | 41.9 | — | — | [Compare](https://noometry.com/compare/amazon-nova-experimental-chat-10-09-vs-qwen3-5-35b-a3b) |
| [Qwen3.5 27B](https://noometry.com/models/qwen3-5-27b) | #127 | 41.9 | $0.82 | — | [Compare](https://noometry.com/compare/qwen3-5-27b-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 35B-A3B Coding benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [LMArena WebDev](https://noometry.com/benchmarks/arena-webdev) | 1254 | #101 of 113, top 90% |  | [LMArena](https://lmarena.ai/leaderboard/webdev) | 2026-10-08 |
| [SciCode](https://noometry.com/benchmarks/scicode) | 29.3% | #106 of 121, top 88% | none | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [LMArena Coding](https://noometry.com/benchmarks/arena-coding) | 1410 | #129 of 294, top 44% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

### Reasoning

Qwen3.5 35B-A3B Reasoning benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [CritPt](https://noometry.com/benchmarks/critpt) | 0.6% | #90 of 134, top 68% | none | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [Chess Puzzles](https://noometry.com/benchmarks/chess-puzzles) | 1% |  |  | [Epoch AI](https://epoch.ai/benchmarks) | 2026-08-28 |
| [Chess Puzzles](https://noometry.com/benchmarks/chess-puzzles) | 10% | #83 of 129, top 65% | none | [Epoch AI](https://epoch.ai/benchmarks) | 2026-08-30 |
| [LMArena Hard Prompts](https://noometry.com/benchmarks/arena-hard-prompts) | 1400 | #125 of 297, top 43% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [DTBench](https://noometry.com/benchmarks/dtbench) | 80% | #77 of 151, top 51% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [LMCA](https://noometry.com/benchmarks/lmca) | 29.5% | #75 of 125, top 60% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [Epoch Capabilities Index](https://noometry.com/benchmarks/epoch-capabilities-index) | 142.52 | #97 of 213, top 46% |  | [Epoch AI](https://epoch.ai/eci) | 2026-02-24 |

### Math

Qwen3.5 35B-A3B Math benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [MathArena Final-Answer Competitions](https://noometry.com/benchmarks/matharena) | 56% | #26 of 29, top 90% |  | [MathArena](https://matharena.ai/) |  |
| [OTIS Mock AIME 2024-2025](https://noometry.com/benchmarks/otis-mock-aime) | 54.4% |  |  | [Epoch AI](https://epoch.ai/benchmarks) | 2026-08-30 |
| [OTIS Mock AIME 2024-2025](https://noometry.com/benchmarks/otis-mock-aime) | 70% | #93 of 173, top 54% | none | [Epoch AI](https://epoch.ai/benchmarks) | 2026-08-30 |
| [LMArena Math](https://noometry.com/benchmarks/arena-math) | 1404 | #121 of 285, top 43% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

### Knowledge

Qwen3.5 35B-A3B Knowledge benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [GPQA Diamond](https://noometry.com/benchmarks/gpqa-diamond) | 83.5% | #68 of 186, top 37% |  | [Epoch AI](https://epoch.ai/benchmarks) | 2026-08-28 |
| [GPQA Diamond](https://noometry.com/benchmarks/gpqa-diamond) | 81.2% |  | none | [Epoch AI](https://epoch.ai/benchmarks) | 2026-08-28 |
| [Vectara Hallucination Rate](https://noometry.com/benchmarks/vectara-hallucination) (lower is better) | 10.5% | #59 of 96, top 62% |  | [Vectara Hallucination Leaderboard](https://github.com/vectara/hallucination-leaderboard) |  |
| [LMArena Expert](https://noometry.com/benchmarks/arena-expert) | 1408 | #116 of 273, top 43% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

### Multilingual

Qwen3.5 35B-A3B Multilingual benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [LMArena Non-English](https://noometry.com/benchmarks/arena-non-english) | 1378 | #127 of 297, top 43% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Chinese](https://noometry.com/benchmarks/arena-chinese) | 1457 | #95 of 285, top 34% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena French](https://noometry.com/benchmarks/arena-french) | 1412 | #110 of 223, top 50% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena German](https://noometry.com/benchmarks/arena-german) | 1367 | #119 of 231, top 52% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Japanese](https://noometry.com/benchmarks/arena-japanese) | 1325 | #112 of 211, top 54% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Korean](https://noometry.com/benchmarks/arena-korean) | 1356 | #101 of 213, top 48% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Russian](https://noometry.com/benchmarks/arena-russian) | 1376 | #131 of 283, top 47% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Spanish](https://noometry.com/benchmarks/arena-spanish) | 1392 | #118 of 226, top 53% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

### Instruction Following

Qwen3.5 35B-A3B Instruction Following benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [LMArena Instruction Following](https://noometry.com/benchmarks/arena-instruction-following) | 1379 | #122 of 298, top 41% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

### Long Context

Qwen3.5 35B-A3B Long Context benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [LMArena Longer Query](https://noometry.com/benchmarks/arena-longer-query) | 1389 | #128 of 291, top 44% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

### Writing & Preference

Qwen3.5 35B-A3B Writing & Preference benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [LMArena Text](https://noometry.com/benchmarks/arena-text) | 1395 | #125 of 297, top 43% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Creative Writing](https://noometry.com/benchmarks/arena-creative-writing) | 1346 | #132 of 295, top 45% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Multi-Turn](https://noometry.com/benchmarks/arena-multi-turn) | 1390 | #128 of 295, top 44% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

## API pricing by provider

Qwen3.5 35B-A3B API prices
| Route | Input $/M | Output $/M | Cached input $/M | Checked |
| --- | --- | --- | --- | --- |
| [alibaba](https://www.alibabacloud.com/help/en/model-studio/models) | $0.25 | $2 | — | 2026-10-10 |
| [deepinfra](https://deepinfra.com/models) | $0.14 | $1 | $0.05 | 2026-10-10 |
| [openrouter](https://openrouter.ai/qwen/qwen3.5-35b-a3b) | $0.08 | $0.75 | $0.04 | 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 35B-A3B

-   [Qwen3.5 35B-A3B vs Qwen3-4B](https://noometry.com/compare/qwen3-4b-vs-qwen3-5-35b-a3b)
-   [Qwen3.5 35B-A3B vs GLM-4.5](https://noometry.com/compare/glm-4-5-vs-qwen3-5-35b-a3b)
-   [Qwen3.5 35B-A3B vs GLM-4.7](https://noometry.com/compare/glm-4-7-vs-qwen3-5-35b-a3b)
-   [Qwen3.5 35B-A3B vs Solar Pro4](https://noometry.com/compare/qwen3-5-35b-a3b-vs-solar-pro4)
-   [Qwen3.5 35B-A3B vs GPT-5.4 nano](https://noometry.com/compare/gpt-5-4-nano-vs-qwen3-5-35b-a3b)
-   [Qwen3.5 35B-A3B vs Longcat Flash Chat](https://noometry.com/compare/longcat-flash-chat-vs-qwen3-5-35b-a3b)
-   [Qwen3.5 35B-A3B vs Amazon Nova Experimental Chat 10 09](https://noometry.com/compare/amazon-nova-experimental-chat-10-09-vs-qwen3-5-35b-a3b)
-   [Qwen3.5 35B-A3B vs GPT-6 Astra](https://noometry.com/compare/gpt-6-astra-vs-qwen3-5-35b-a3b)
-   [Qwen3.5 35B-A3B vs Claude Fable 5.1](https://noometry.com/compare/claude-fable-5-1-vs-qwen3-5-35b-a3b)
-   [Qwen3.5 35B-A3B vs Gemini 3.8 Flash](https://noometry.com/compare/gemini-3-8-flash-vs-qwen3-5-35b-a3b)
-   [Qwen3.5 35B-A3B vs Kimi K3](https://noometry.com/compare/kimi-k3-vs-qwen3-5-35b-a3b)
-   [Qwen3.5 35B-A3B vs Grok 4.6](https://noometry.com/compare/grok-4-6-vs-qwen3-5-35b-a3b)
-   [Qwen3.5 35B-A3B vs GLM-5.3](https://noometry.com/compare/glm-5-3-vs-qwen3-5-35b-a3b)
-   [Qwen3.5 35B-A3B vs Muse Spark 1.3](https://noometry.com/compare/muse-spark-1-3-vs-qwen3-5-35b-a3b)

## 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 35B-A3B?

Qwen3.5 35B-A3B by Alibaba (Qwen) ranks 123rd of 354 ranked models on the Noometry Index as of October 2026, with a score of 42.0. Its strongest category is knowledge, where it ranks 79th. API pricing starts at $0.25 per million input tokens and $2 per million output tokens, with a 262K-token context window.

### How much does Qwen3.5 35B-A3B cost?

Qwen3.5 35B-A3B costs $0.25 per million input tokens and $2 per million output tokens on Alibaba (Qwen)'s own API.

### What is Qwen3.5 35B-A3B's context window?

Qwen3.5 35B-A3B accepts up to 262K tokens of input and can write up to 66K tokens in one response.

### Is Qwen3.5 35B-A3B open source?

Yes. Qwen3.5 35B-A3B's weights are downloadable from Hugging Face (Qwen/Qwen3.5-35B-A3B); check the license for commercial terms.

### What are Qwen3.5 35B-A3B's strengths and weaknesses?

Relative to other ranked models, Qwen3.5 35B-A3B places best in knowledge, math, writing & preference and lowest in coding, reasoning, long context.

### What is Qwen3.5 35B-A3B best at?

Its best category is knowledge, where it ranks 79th on Noometry.

### Cite this page

Noometry. (2026). Qwen3.5 35B-A3B benchmarks and pricing. Retrieved October 10, 2026, from https://noometry.com/models/qwen3-5-35b-a3b

Quote Noometry with a link back to this page. It is also available in [Markdown](https://noometry.com/md/models/qwen3-5-35b-a3b.md).