Qwen3.5-27B
Qwen vision-language model for visual reasoning, documents, and agent tasks
- Context
- 262K
- Released
- 7mo ago
- Parameters
- 27B
- Input / 1M tokens
- $0.26
- Output / 1M tokens
- $2.60
Sources:models.devOpenRouter
Benchmarks
DeepSWE is the primary coding benchmark where an exact model evaluation exists. Other sourced evaluations appear below; missing scores are not zero.
Not evaluated in DeepSWE 1.1 as of 2026-09-22. Results are only shown for exact model versions in the official dataset. Official leaderboard.
No benchmark results have been matched to this model yet.
Specifications
- Developer
- Qwen
- Model family
- Qwen
- Type
- Language model
- Predecessor
- —
- Successor
- —
- Released
- February 23, 2026
- Model ID
qwen/qwen3.5-27b- Openness
- Open weights
- License
- —
- Parameters
- 27B
- Input modalities
- text, image, video
- Output modalities
- text
- Modality
- text+image+video->text
- Native context
- 256K
- Tokenizer
- Qwen3
- Max output tokens
- 82K
- Hugging Face
- Qwen/Qwen3.5-27B
- Source freshness
- Metadata synced Oct 8, 2026, 10:17 PM UTC
Additional source evidence
- Source model
- alibaba/qwen3.5-27b
- Source family
- qwen
- Last updated
- 2026-02-23
- Model context
- 262K
- Model output limit
- 66K
- Open weights
- Yes
- File attachments
- Yes
- Reasoning
- Yes
- Tool calling
- Yes
- Structured output
- Yes
- Temperature control
- Yes
Downloadable weights
Published benchmarks
| Benchmark | Score | Evaluation details | Evidence |
|---|---|---|---|
| SWE-Bench Verified | 72.4 · resolved | — | Source |
Complete source record (JSON)
{
"id": "alibaba/qwen3.5-27b",
"name": "Qwen3.5 27B",
"description": "Qwen vision-language model for visual reasoning, documents, and agent tasks",
"family": "qwen",
"last_updated": "2026-02-23",
"attachment": true,
"reasoning": true,
"tool_call": true,
"structured_output": true,
"temperature": true,
"modalities": {
"input": [
"text",
"image",
"video",
"audio"
],
"output": [
"text"
]
},
"limit": {
"context": 262144,
"output": 65536
},
"benchmarks": [
{
"name": "SWE-Bench Verified",
"score": 72.4,
"source": "https://huggingface.co/Qwen/Qwen3.5-27B",
"metric": "resolved"
}
],
"release_date": "2026-02-23",
"open_weights": true,
"weights": [
{
"label": "Hugging Face",
"url": "https://huggingface.co/Qwen/Qwen3.5-27B"
}
]
}Infrastructure
Provider availability
| Provider | Endpoint | Context | Input /M tokens | Output /M tokens | Cached input /M tokens | Cache write /M tokens | Uptime 1d | Data handling |
|---|---|---|---|---|---|---|---|---|
| alibaba | 262K | $0.20 | $1.56 | — | — | 96.64% | ZDR: NoTraining: Unknown Prompt logging: Unknown Retention: Unknown Checked 2026-10-15 | |
| siliconflow/fp8 | 262K | $0.25 | $2.00 | — | — | 89.13% | ZDR: YesTraining: Unknown Prompt logging: Unknown Retention: Unknown Checked 2026-10-15 | |
| deepinfra/fp8 | 262K | $0.26 | $2.60 | — | — | 100.00% | ZDR: YesTraining: Unknown Prompt logging: Unknown Retention: Unknown Checked 2026-10-15 | |
| reka | 33K | $0.26 | $2.60 | $0.03 | — | 100.00% | ZDR: YesTraining: Unknown Prompt logging: Unknown Retention: Unknown Checked 2026-10-15 | |
| atlas-cloud/fp8 | 262K | $0.27 | $2.16 | $0.27 | — | 99.71% | ZDR: NoTraining: Unknown Prompt logging: Unknown Retention: Unknown Checked 2026-10-15 | |
| novita/bf16 | 262K | $0.30 | $2.40 | — | — | 100.00% | ZDR: YesTraining: Unknown Prompt logging: Unknown Retention: Unknown Checked 2026-10-15 | |
| phala | 262K | $0.30 | $2.40 | $0.03 | — | 97.79% | ZDR: YesTraining: Unknown Prompt logging: Unknown Retention: Unknown Checked 2026-10-15 |
Provider data:OpenRouter
Deployment graph
Can I run this?
Vertical Tabs only shows compatibility when it has structured evidence tying this exact model to hardware, runtime, quantization, memory use, and observed performance.