Alibaba
Qwen 3.6 27B
Frontera
5.0MDescargas1.5KMe gustaApr 2026Publicado262K tokensContextoApache 2.0Licencia99 ExcepcionalCalidad
Qwen 3.6 27B (27B parameters) requires approximately 18.9 GB of VRAM with Q4_K_M quantization. For the best balance of quality and speed, we recommend hardware with at least 22 GB of VRAM.
Comenzar
— copia y pega para ejecutar en localCopy-paste commands to run Qwen 3.6 27B on your machine.
Run
lms load Qwen3.6-27B && lms server startQuick specs
Parameters27B
Architecturedense
Context262K tokens
Modalitytext+vision
Min RAM10.5 GB
Rec. RAM16.5 GB (Q4_K_M)
LicenseApache 2.0
FamilyQwen
✓ Vision✓ Tool Use✓ Thinking✓ Code✓ Chat✓ Reasoning
About this model
- •Dense 27B beats Qwen 3.5 397B-A17B MoE on SWE-bench Verified (77.2%)
- •Fits on RTX 4080/4090/3090 (16-24 GB) at Q4_K_M (~16.8 GB)
- •Multimodal: vision encoder for images, OCR, and hour-scale video
- •262K native context, extensible to ~1M tokens via YaRN
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Selecciones rápidas
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Ejecutar este modelo
Opciones de cuantización
Estimaciones de VRAM por nivel de cuantización
No hardware detected — fit column shows raw VRAM estimates
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 10.5 GB | Low | — |
Q3_K_S | 3 | 13.2 GB | Low | — |
NVFP4 | 4 | 15.1 GB | Medium | — |
Q4_K_M | 4 | 16.5 GB | Medium | — |
Q5_K_M | 5 | 19.4 GB | High | — |
Q6_K | 6 | 22.1 GB | High | — |
Q8_0 | 8 | 28.9 GB | Very High | — |
F16 | 16 | 55.4 GB | Maximum | — |
Quality benchmarks
Qwen 3.6 27B benchmark scores
Coding
SWE-bench Verified77.2%
HumanEval+—
Aider Polyglot—
LiveCodeBench83.9%
Reasoning
MMLU-Pro86.2%
GPQA Diamond87.8%
MATH-500—
ARC Challenge—
Source: official · 2026-04-22
Compatibilidad de hardware
Estimaciones de encaje en todo el hardware
Computing compatibility...
Desglose de memoria
Reference: RTX 2060 6GB
Weights16.5 GB
KV Cache1.0 GB
Runtime0.9 GB
Headroom0.6 GB
Preguntas frecuentes
FAQ — Qwen 3.6 27B
Ver también