Qwen3.5-9B
Qwen · released Mar 10, 2026
Qwen3.5-9B is a multimodal foundation model from the Qwen3.5 family, designed to deliver strong reasoning, coding, and visual understanding in an efficient 9B-parameter architecture. It uses a unified vision-language design...
Specification
- Context window
- 262K
- Max output
- 262K
- Knowledge cutoff
- Not stated
- Parameters
- 9.7B
- Licence
- apache-2.0
- Serving providers
- 5
- Moderated
- No
- Uptime
- 100.0%
Intelligence
21.8
63th percentile
Coding
28.7
Coding Index
Agentic
7.0
Agentic Index
Output speed
42 t/s
Median across providers
Latency
446ms
Time to first token
Cost per task
$0.02
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)86.8%
- GPQA Diamond80.6%
- IFBench66.7%
- AA-LCR (long context)65.3%
- SciCode27.5%
- Terminal-Bench Hard24.2%
- Humanity's Last Exam14.9%
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) | 86.8% |
| GPQA Diamond | 80.6% |
| IFBench | 66.7% |
| AA-LCR (long context) | 65.3% |
| SciCode | 27.5% |
| Terminal-Bench Hard | 24.2% |
| Humanity's Last Exam | 14.9% |
Against its peers
Intelligence Index · this model highlighted, nearest peers in grey
- GLM 4.6Z.ai23.4
- GLM 4.7 FlashZ.ai23.3
- Mercury 2Inception21.9
- Qwen3.5-9BQwen21.8
- V3.1 TerminusDeepSeek21.7
- Qwen3 Coder NextQwen21.3
- R1DeepSeek20.4
- North Mini Code (free)Cohere20.2
Peers are the models sitting closest on the Intelligence Index — the set you would realistically choose between.
View as table
| Model | Intelligence |
|---|---|
| GLM 4.6 | 23.4 |
| GLM 4.7 Flash | 23.3 |
| Mercury 2 | 21.9 |
| Qwen3.5-9B | 21.8 |
| V3.1 Terminus | 21.7 |
| Qwen3 Coder Next | 21.3 |
| R1 | 20.4 |
| North Mini Code (free) | 20.2 |
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
- $0.1
- Output / 1M tokens
- $0.15
- Cached input / 1M
- Not offered
- Blended 3:1
- $0.113
One task, estimated
$0.02
- 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.