Alibaba Cloud / Qwen Team model product
Qwen3.5 27B
5-27B is a multimodal dense foundation model with 27 billion parameters.
Updated Aug 12, 2026. Default version: Qwen3.5-27B
LLMBoard score57.2Qwen3.5-27B
Coverage100%81 benchmark families
Context window262.1KTokens
Official input price$0.30Alibaba API
Qwen3.5 27B Specifications
Technical details for the model's default version.
- Version
- Qwen3.5-27B
- Released
- Feb 24, 2026
- Knowledge cutoff
- Unknown
- Parameters
- 27B
- Context window
- 262.1K
- Max output
- 65.5K
- Inputs
- audio, image, text, video
- Outputs
- text
- Open weights
- Yes
- License
- Apache 2.0
Qwen3.5 27B Capability Profile
This profile uses the model's current scored version. Arena ratings and prices are shown separately.
Qwen3.5 27B Benchmark Results
Benchmark scores for Qwen3.5-27B.
| CountBench | 1.0 | 1 | 6 | 100.0% | C | |
| Hallusion Bench | 0.7 | 1 | 16 | 100.0% | C | |
| IFEval | 0.9 | 1 | 65 | 100.0% | C | |
| DynaMath | 0.9 | 2 | 7 | 83.3% | C | |
| EmbSpatialBench | 0.8 | 2 | 8 | 85.7% | C | |
| FullStackBench en | 0.6 | 2 | 3 | 50.0% | C | |
| FullStackBench zh | 0.6 | 2 | 3 | 50.0% | C | |
| Hypersim | 0.1 | 2 | 4 | 66.7% | C | |
| LingoQA | 0.8 | 2 | 4 | 66.7% | C | |
| MathVista-Mini | 0.9 | 2 | 23 | 95.5% | C | |
| MMLongBench-Doc | 0.6 | 2 | 5 | 75.0% | C | |
| Nuscene | 0.2 | 2 | 3 | 50.0% | C | |
| PMC-VQA | 0.6 | 2 | 3 | 50.0% | C | |
| SlakeVQA | 0.8 | 2 | 4 | 66.7% | C | |
| SUNRGBD | 0.4 | 2 | 4 | 66.7% | C | |
| TIR-Bench | 0.6 | 2 | 4 | 66.7% | C | |
| VideoMME w/o sub. | 0.8 | 2 | 10 | 88.9% | C | |
| ZEROBench-Sub | 0.4 | 2 | 5 | 75.0% | C | |
| AndroidWorld_SR | 0.6 | 3 | 8 | 71.4% | C | |
| MedXpertQA | 0.6 | 3 | 12 | 81.8% | C | |
| MMBench-V1.1 | 0.9 | 3 | 18 | 88.2% | C | |
| MMVU | 0.7 | 3 | 4 | 33.3% | C | |
| OJBench | 0.4 | 3 | 9 | 75.0% | C | |
| Seal-0 | 0.5 | 3 | 6 | 60.0% | C | |
| VLMsAreBlind | 1.0 | 3 | 4 | 33.3% | C | |
| MVBench | 0.7 | 4 | 17 | 81.3% | C | |
| RefSpatialBench | 0.7 | 4 | 6 | 40.0% | C | |
| V* | 0.9 | 4 | 7 | 50.0% | C | |
| VideoMME w sub. | 0.9 | 4 | 10 | 66.7% | C | |
| BFCL-V4 | 0.7 | 5 | 13 | 66.7% | C | |
| MAXIFE | 0.9 | 5 | 11 | 60.0% | C | |
| MMStar | 0.8 | 5 | 22 | 81.0% | C | |
| NOVA-63 | 0.6 | 5 | 11 | 60.0% | C | |
| PolyMATH | 0.7 | 5 | 23 | 81.8% | C | |
| VITA-Bench | 0.4 | 5 | 10 | 55.6% | C | |
| MLVU | 0.9 | 6 | 10 | 44.4% | C | |
| RefCOCO-avg | 0.9 | 6 | 7 | 16.7% | C | |
| WideSearch | 0.6 | 6 | 9 | 37.5% | C | |
| ZEROBench | 0.1 | 6 | 9 | 37.5% | C | |
| AI2D | 0.9 | 7 | 32 | 80.7% | C | |
| BabyVision | 0.4 | 7 | 9 | 25.0% | C | |
| CC-OCR | 0.8 | 7 | 18 | 64.7% | C | |
| C-Eval | 0.9 | 7 | 18 | 64.7% | C | |
| CodeForces | 0.8 | 7 | 16 | 60.0% | C | |
| DeepPlanning | 0.2 | 7 | 9 | 25.0% | C | |
| HMMT25 | 0.9 | 7 | 25 | 75.0% | C | |
| Include | 0.8 | 7 | 31 | 80.0% | C | |
| LVBench | 0.7 | 7 | 24 | 73.9% | C | |
| MMLU-ProX | 0.8 | 7 | 32 | 80.7% | C | |
| AA-LCR | 0.7 | 8 | 16 | 53.3% | C | |
| Global PIQA | 0.9 | 8 | 13 | 41.7% | C | |
| IFBench | 0.8 | 8 | 29 | 75.0% | C | |
| MathVision | 0.9 | 8 | 32 | 77.4% | C | |
| OCRBench | 0.9 | 8 | 22 | 66.7% | C | |
| OmniDocBench 1.5 | 0.9 | 8 | 17 | 56.3% | C | |
| BrowseComp-zh | 0.6 | 9 | 13 | 33.3% | C | |
| MMMU | 0.8 | 9 | 63 | 87.1% | C | |
| Multi-Challenge | 0.6 | 9 | 29 | 71.4% | C | |
| ScreenSpot Pro | 0.7 | 9 | 25 | 66.7% | C | |
| SuperGPQA | 0.7 | 9 | 34 | 75.8% | C | |
| LongBench v2 | 0.6 | 10 | 17 | 43.8% | C | |
| RealWorldQA | 0.8 | 10 | 26 | 64.0% | C | |
| WMT24++ | 0.8 | 10 | 23 | 59.1% | C | |
| ERQA | 0.6 | 12 | 23 | 50.0% | C | |
| MMLU-Pro | 0.9 | 13 | 129 | 90.6% | C | |
| MMLU-Redux | 0.9 | 13 | 48 | 74.5% | C | |
| SimpleVQA | 0.6 | 13 | 13 | 0.0% | C | |
| HMMT 2025 | 0.9 | 14 | 33 | 59.4% | C | |
| ODinW | 0.4 | 14 | 16 | 13.3% | C | |
| VideoMMMU | 0.8 | 14 | 26 | 48.0% | C | |
| t2-bench | 0.8 | 15 | 23 | 36.4% | C | |
| LiveCodeBench v6 | 0.8 | 18 | 53 | 67.3% | C | |
| CharXiv-R | 0.8 | 21 | 48 | 57.5% | C | |
| OSWorld-Verified | 0.6 | 21 | 23 | 9.1% | C | |
| Humanity's Last Exam | 0.5 | 22 | 93 | 77.2% | C | |
| MMMLU | 0.9 | 26 | 49 | 47.9% | C | |
| BrowseComp | 0.6 | 34 | 58 | 42.1% | C | |
| MMMU-Pro | 0.8 | 34 | 66 | 49.2% | C | |
| Terminal-Bench 2.0 | 0.4 | 43 | 49 | 12.5% | C | |
| GPQA | 0.9 | 52 | 234 | 78.1% | C | |
| SWE-Bench Verified | 0.7 | 52 | 105 | 51.0% | C |
Qwen3.5 27B Arena Results
Preference and agent-evaluation results for the default version.
| vision | overall | 55 | 1240.9 | 21,450 | N/A | |
| vision style control | overall | 59 | 1218.7 | 21,450 | N/A | |
| webdev | overall | 78 | 1357.2 | 7,428 | N/A | |
| text factuality | overall | 109 | 1418.9 | 27,160 | N/A | |
| text | overall | 122 | 1407.9 | 27,339 | N/A | |
| text style control | overall | 130 | 1408.0 | 27,339 | N/A |
Qwen3.5 27B Pricing
Official vendor API pricing appears first, followed by individual provider offers.
- Official API
- $0.30 input, $2.4 output per 1M
- Official provider
- Alibaba
- Lowest third-party
- From $0.086 input, $0.688 output per 1M via EmpirioLabs AI
- Tracked offerings
- 13
| EmpirioLabs AI | qwen3-5-27b | global | $0.086 | $0.688 | 256K | |
| OrcaRouter | qwen/qwen3.5-27b | global | $0.086 | $0.688 | 262.1K | |
| Merge Gateway | qwen/qwen3.5-27b | global | $0.086 | $0.688 | 256K | |
| Kilo Gateway | qwen/qwen3.5-27b | global | $0.195 | $1.56 | 262.1K | |
| OpenRouter | qwen/qwen3.5-27b | global | $0.195 | $1.56 | 262.1K | |
| SiliconFlow | Qwen/Qwen3.5-27B | global | $0.25 | $2 | 262.1K | |
| Deep Infra | Qwen/Qwen3.5-27B | global | $0.26 | $2.6 | 262.1K | |
| NanoGPT | qwen3.5-27b | global | $0.27 | $2.16 | 260.1K | |
| Ofox | bailian/qwen3.5-27b | global | $0.29 | $2.05 | 262.1K | |
| Mixlayer | qwen/qwen3.5-27b | global | $0.30 | $2.4 | 262.1K | |
| Alibaba | qwen3.5-27b | global | $0.30 | $2.4 | 262.1K | |
| NovitaAI | qwen/qwen3.5-27b | global | $0.30 | $2.4 | 262.1K | |
| Hugging Face | Qwen/Qwen3.5-27B | global | $0.30 | $2.4 | 262.1K |
Official prices use only the vendor's configured official Provider and positive standard USD PAYG rates. Third-party offers remain explicitly labeled.
Qwen3.5 27B Versions
Available versions of this model. The score column identifies the version used in the overall ranking.
| Qwen3.5-27B | 57.2 | 27B | 262.1K | 65.5K | Yes | Apache 2.0 |
What is Qwen3.5 27B?
Key information about Qwen3.5 27B and its available data.
5-27B is a multimodal dense foundation model with 27 billion parameters. It combines strong reasoning, coding, multilingual, long-context, and visual understanding performance in a production-friendly open-weight package with a native 262K context window.
Data as of 2026-08-11.
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FAQ
Common questions about Qwen3.5 27B.
When was Qwen3.5 27B released?
Qwen3.5 27B's default version was released on Feb 24, 2026.
How much does Qwen3.5 27B cost?
Qwen3.5 27B's official API price is $0.30 per million input tokens and $2.4 per million output tokens via Alibaba. The lowest tracked third-party offer starts at $0.086 input and $0.688 output via EmpirioLabs AI.
Who created Qwen3.5 27B?
Qwen3.5 27B was created by Alibaba Cloud / Qwen Team.
What is the context window for Qwen3.5 27B?
The default version has a 262.1K token context window.
Is Qwen3.5 27B open weight?
Yes. The default version is marked as open weight under Apache 2.0.
How many API providers offer Qwen3.5 27B?
13 provider offerings are linked to the default version.
What models should I compare Qwen3.5 27B with?
Nearby ranked alternatives include Muse Glimmer 30B, MiniMax M2.7, DeepSeek-V3.2.