Alibaba Cloud / Qwenopen-weight
Released: 2026-02-24Qwen: Qwen3.5-27B
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...
Intelligence Index
85.0/ 100
Calibrated multi-domain compositeThroughput Speed
85tok/sec
Output streaming throughputTime To First Token
280ms
Initial chunk server latencyLiveBench Contam-Free
74.8%
September 2026 suite scoreLiveBench Multi-Domain Evaluation Breakdown
Monthly refreshed contamination-free test setsLogical Reasoning78.2%
Coding & Repo Repair76.5%
Mathematics (AIME)75.7%
Data Analysis & Tables72.3%
Language & Comprehension74.0%
Instruction Following74.8%
Sourced Benchmark Evaluations (60)
Verified performance across authoritative benchmarks with provenance tracking.| Benchmark | Status | Score | Trust | Date | Source Type | Provenance |
|---|---|---|---|---|---|---|
| ARC-AGI-3 | Active | 53.6% | 93 | 2026-03-31 | independent | Source ↗ |
| ARC-AGI-2 | Nearing Saturation | 64.4% | 75 | 2026-03-24 | independent | Source ↗ |
| FrontierMath | Active | 22.1% | 98 | 2026-03-21 | independent | Source ↗ |
| PutnamBench | Active | 41.1% | 90 | 2026-03-20 | independent | Source ↗ |
| Omni-MATH | Deprecated | 58.5% | 10 | 2026-03-18 | independent | Source ↗ |
| SWE-Lancer | Deprecated | 54.9% | 20 | 2026-03-18 | independent | Source ↗ |
| FrontierCode | Active | 46.9% | 98 | 2026-03-16 | independent | Source ↗ |
| Soohak | Active | 60.1% | 98 | 2026-03-16 | independent | Source ↗ |
| StructFlowBench | Nearing Saturation | 63.6% | 75 | 2026-03-14 | independent | Source ↗ |
| Humanity's Last Exam | Active | 36.3% | 93 | 2026-03-14 | independent | Source ↗ |
| AIME | Nearing Saturation | 75.1% | 75 | 2026-03-14 | independent | Source ↗ |
| OlympiadBench | Active | 64.9% | 80 | 2026-03-13 | independent | Source ↗ |
| Terminal-Bench | Active | 56.6% | 80 | 2026-03-12 | independent | Source ↗ |
| FireBench | Active | 62.8% | 95 | 2026-03-12 | independent | Source ↗ |
| MathArena | Active | 63.3% | 99 | 2026-03-12 | independent | Source ↗ |
| SimpleQA | Active | 44.2% | 90 | 2026-03-11 | independent | Source ↗ |
| OpenAI-MRCR | Active | 71.4% | 80 | 2026-03-11 | independent | Source ↗ |
| CodeContests | Deprecated | 52.5% | 10 | 2026-03-11 | independent | Source ↗ |
| SWE-bench Pro | Active | 50.1% | 90 | 2026-03-10 | independent | Source ↗ |
| ComplexBench | Nearing Saturation | 61.3% | 80 | 2026-03-10 | independent | Source ↗ |
| LongBench-Pro | Active | 69.7% | 80 | 2026-03-10 | independent | Source ↗ |
| MultiPL-E | Deprecated | 74.3% | 10 | 2026-03-09 | independent | Source ↗ |
| ZeroSCROLLS | Nearing Saturation | 68% | 78 | 2026-03-09 | independent | Source ↗ |
| InfiniteBench | Nearing Saturation | 72.3% | 65 | 2026-03-08 | independent | Source ↗ |
| LiveCodeBench | Saturated | 66.3% | 39 | 2026-03-08 | independent | Source ↗ |
| AgentIF | Nearing Saturation | 50.9% | 80 | 2026-03-08 | independent | Source ↗ |
| MATH | Saturated | 77.5% | 25 | 2026-03-08 | independent | Source ↗ |
| SCROLLS | Nearing Saturation | 68% | 65 | 2026-03-07 | independent | Source ↗ |
| Mercury | Deprecated | 71.1% | 10 | 2026-03-07 | independent | Source ↗ |
| MMLU-Pro | Nearing Saturation | 78.2% | 75 | 2026-03-07 | independent | Source ↗ |
| TabMWP | Saturated | 72.8% | 25 | 2026-03-06 | independent | Source ↗ |
| CyberSecEval | Deprecated | 72.7% | 10 | 2026-03-06 | independent | Source ↗ |
| RULER | Nearing Saturation | 78.2% | 84 | 2026-03-06 | independent | Source ↗ |
| SWE-bench Verified | Saturated | 63% | 25 | 2026-03-05 | independent | Source ↗ |
| QuALITY | Nearing Saturation | 74.8% | 78 | 2026-03-05 | independent | Source ↗ |
| MMLU-Redux | Saturated | 83.3% | 25 | 2026-03-05 | independent | Source ↗ |
| SWE-bench | Deprecated | 54.9% | 10 | 2026-03-04 | independent | Source ↗ |
| MGSM | Nearing Saturation | 75.1% | 65 | 2026-03-04 | independent | Source ↗ |
| LongBench | Nearing Saturation | 73.1% | 65 | 2026-03-04 | independent | Source ↗ |
| QASPER | Nearing Saturation | 70.6% | 65 | 2026-03-03 | independent | Source ↗ |
| TruthfulQA | Saturated | 74.8% | 25 | 2026-03-03 | independent | Source ↗ |
| AGIEval | Saturated | 71% | 25 | 2026-03-03 | independent | Source ↗ |
| SuperGLUE | Saturated | 84.2% | 25 | 2026-03-02 | independent | Source ↗ |
| GSM-Hard | Deprecated | 75.9% | 10 | 2026-03-02 | independent | Source ↗ |
| MT-Bench | Nearing Saturation | 7.7% | 75 | 2026-03-01 | independent | Source ↗ |
| BIG-Bench Hard | Saturated | 80.9% | 25 | 2026-03-01 | independent | Source ↗ |
| CodeXGLUE | Deprecated | 76% | 23 | 2026-03-01 | independent | Source ↗ |
| WinoGrande | Saturated | 85.8% | 28 | 2026-02-28 | independent | Source ↗ |
| MBPP+ | Nearing Saturation | 82.4% | 65 | 2026-02-28 | independent | Source ↗ |
| IFEval | Deprecated | 73.3% | 25 | 2026-02-28 | independent | Source ↗ |
| GPQA | Nearing Saturation | 74.8% | 78 | 2026-02-28 | independent | Source ↗ |
| HumanEval+ | Saturated | 87.3% | 25 | 2026-02-27 | independent | Source ↗ |
| Needle-in-a-Haystack | Saturated | 97% | 44 | 2026-02-27 | independent | Source ↗ |
| CommonsenseQA | Saturated | 86.6% | 28 | 2026-02-27 | independent | Source ↗ |
| GSM8K | Saturated | 85.4% | 25 | 2026-02-26 | independent | Source ↗ |
| GLUE | Saturated | 89.1% | 28 | 2026-02-26 | independent | Source ↗ |
| MBPP | Saturated | 85.6% | 25 | 2026-02-26 | independent | Source ↗ |
| HumanEval | Saturated | 92.1% | 25 | 2026-02-25 | independent | Source ↗ |
| MMLU | Saturated | 86.7% | 25 | 2026-02-25 | independent | Source ↗ |
| ARC-AGI | Saturated | 77.6% | 25 | 2026-02-25 | independent | Source ↗ |
Local Hardware Execution (Ollama)Hardware Compatible
# 1. Pull and execute model locally with Ollama
ollama run qwen-qwen3-5-27b
# 2. Or invoke via local OpenAI-compatible endpoint
curl http://localhost:11434/v1/chat/completions \
-H "Content-Type: application/json" \
-d '{
"model": "qwen-qwen3-5-27b",
"messages": [{"role": "user", "content": "Analyze reasoning chains on AIME 2026"}]
}'Evaluation & Sourcing Notes
Scores listed for Qwen: Qwen3.5-27B represent verified evaluations extracted from official research papers, independent evaluation suites (HELM, LMSYS, OpenCompass, LiveBench), and verified audit reports.
All benchmarks marked as saturated or deprecated reflect historical performance where the benchmark no longer provides active discriminative power.