Qwen3.6 35B A3B
Qwen · released Apr 27, 2026
Qwen3.6-35B-A3B is an open-weight multimodal model from Alibaba Cloud with 35 billion total parameters and 3 billion active parameters per token. It uses a hybrid sparse mixture-of-experts architecture combining Gated...
Specification
- Context window
- 262K
- Max output
- 262K
- Knowledge cutoff
- Not stated
- Parameters
- 36B
- Licence
- apache-2.0
- Serving providers
- 9
- Moderated
- No
- Uptime
- 100.0%
Intelligence
32.1
77th percentile
Coding
41.9
Coding Index
Agentic
21.6
Agentic Index
Output speed
177 t/s
Median across providers
Latency
254ms
Time to first token
Cost per task
$0.09
Estimated
Benchmarks
Where the score comes from
The Intelligence Index is a composite. These are the underlying evaluations this model was actually measured on.
Evaluation scores
Percentage correct · higher is better
- τ²-bench (Telecom)95.3%
- GPQA Diamond84.1%
- AA-LCR (long context)66.7%
- IFBench64.4%
- SciCode35.8%
- Terminal-Bench Hard34.8%
- Humanity's Last Exam22.2%
An evaluation missing from this list was not run for this model — it is not a zero.
View as table
| Evaluation | Score |
|---|---|
| τ²-bench (Telecom) | 95.3% |
| GPQA Diamond | 84.1% |
| AA-LCR (long context) | 66.7% |
| IFBench | 64.4% |
| SciCode | 35.8% |
| Terminal-Bench Hard | 34.8% |
| Humanity's Last Exam | 22.2% |
Against its peers
Intelligence Index · this model highlighted, nearest peers in grey
- o3 ProOpenAI33.3
- 32.8
- 32.5
- Qwen3.6 35B A3BQwen32.1
- M2.1MiniMax32.1
- GPT-5.1-Codex-MiniOpenAI31.3
- Ring-2.6-1TInclusionAI31.1
- o3OpenAI31.1
Peers are the models sitting closest on the Intelligence Index — the set you would realistically choose between.
View as table
| Model | Intelligence |
|---|---|
| o3 Pro | 33.3 |
| Qwen3.5-122B-A10B | 32.8 |
| Qwen3 Max Thinking | 32.5 |
| Qwen3.6 35B A3B | 32.1 |
| M2.1 | 32.1 |
| GPT-5.1-Codex-Mini | 31.3 |
| Ring-2.6-1T | 31.1 |
| o3 | 31.1 |
Percentile among all indexed models
Pricing
What it costs to run
List prices per million tokens, plus what one representative task works out to.
List price
- Input / 1M tokens
- $0.14
- Output / 1M tokens
- $1
- Cached input / 1M
- $0.05
- Blended 3:1
- $0.355
One task, estimated
$0.09
- Input tokens
- 50,000
- Output tokens
- 80,000
- Profile
- Reasoning
Estimated from list pricing: 50K input tokens plus 80K output tokens for reasoning models (25K for non-reasoning).
Serving providers
Speed and latency figures are medians across these providers, so a widely-served model reports a blend rather than any single endpoint.