Qwen3.5-27B
Qwen · released Feb 25, 2026
The Qwen3.5 27B native vision-language Dense model incorporates a linear attention mechanism, delivering fast response times while balancing inference speed and performance. Its overall capabilities are comparable to those of...
Specification
- Context window
- 262K
- Max output
- 66K
- Knowledge cutoff
- Not stated
- Parameters
- 27.8B
- Licence
- apache-2.0
- Serving providers
- 6
- Moderated
- No
- Uptime
- 100.0%
Intelligence
34.6
81th percentile
Coding
—
Coding Index
Agentic
—
Agentic Index
Output speed
44 t/s
Median across providers
Latency
560ms
Time to first token
Cost per task
$0.13
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)93.9%
- GPQA Diamond85.8%
- IFBench75.6%
- AA-LCR (long context)72.3%
- SciCode39.5%
- Terminal-Bench Hard32.6%
- Humanity's Last Exam23.9%
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) | 93.9% |
| GPQA Diamond | 85.8% |
| IFBench | 75.6% |
| AA-LCR (long context) | 72.3% |
| SciCode | 39.5% |
| Terminal-Bench Hard | 32.6% |
| Humanity's Last Exam | 23.9% |
Against its peers
Intelligence Index · this model highlighted, nearest peers in grey
- GLM 5V TurboZ.ai35.3
- GPT-5OpenAI35.3
- Qwen3.5-27BQwen34.6
- M2.5MiniMax34.5
- GLM 4.7Z.ai34.5
- Hy3 previewTencent34.4
- 34.3
- LongCat 2.0Meituan33.9
Peers are the models sitting closest on the Intelligence Index — the set you would realistically choose between.
View as table
| Model | Intelligence |
|---|---|
| GLM 5V Turbo | 35.3 |
| GPT-5 | 35.3 |
| Qwen3.5-27B | 34.6 |
| M2.5 | 34.5 |
| GLM 4.7 | 34.5 |
| Hy3 preview | 34.4 |
| Qwen3.5 397B A17B | 34.3 |
| LongCat 2.0 | 33.9 |
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
- $0.195
- Output / 1M tokens
- $1.56
- Cached input / 1M
- Not offered
- Blended 3:1
- $0.536
One task, estimated
$0.13
- 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.