Qwen3.8 27B
Intelligence benchmarks
Artificial Analysis indexes - compared with the best open and proprietary models
Intelligence
52.0
AA Index
Agentic
50.9
AA Index
Intelligence Index - Qwen3.8 27B vs. the field
Best open-weight models (you can run locally) and leading proprietary models for context.
Agentic Index comparison
Benchmark data from Artificial Analysis · updated 2026-08-22.
Standard benchmarks
Performance across standard evaluations
| Benchmark | Score |
|---|---|
| GPQA | 90.5 |
Will it run on your hardware?
Pick your GPU memory - see which quantizations fit, and the cheapest card for the rest
Need an exact figure for your context length? Use the VRAM calculator.
Run it locally
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Deep dive
Notes, sources, and the full write-up
Qwen3.8 27B is a 27.8B-parameter apache-2.0 model from Alibaba. It scores 52 on the Artificial Analysis Intelligence Index. At Q4_K_M it needs roughly 16 GB of VRAM, placing it in the 12–24 GB GPU hardware tier.
Benchmarks
Artificial Analysis Intelligence Index - Qwen3.8 27B vs. leading closed models:
| Model | Intelligence | Coding | GPQA |
|---|---|---|---|
| Qwen3.8 27B | 52 | - | 90.5 |
| Claude Opus 5 (max) | 63.1 | - | 93.2 |
| Claude Fable 5 (with fallback) | 62.1 | - | 92.6 |
| GPT-5.6 Sol (max) | 60.9 | - | 94.1 |
| Grok 4.6 (high) | 60.9 | - | 94.9 |
| GLM-5.3 (max) | 59.5 | - | 91.7 |
Source: Artificial Analysis (2026-08-20).
Popularity
Qwen3.8 27B has 1,063,646 downloads in the last month on HuggingFace and 600 likes.
Frequently asked
Quick answers to common questions
How much VRAM does Qwen3.8 27B need?
Qwen3.8 27B with 27.8B parameters needs approximately 16 GB at Q4_K_M quantization. Use our VRAM calculator for an exact estimate.
Is Qwen3.8 27B better than other Qwen models?
Qwen3.8 27B has 27.8B parameters with 262,144 context - a strong choice for general use.
What license is Qwen3.8 27B under?
Qwen3.8 27B is released under the apache-2.0 license, making it suitable for most commercial and personal projects.
What hardware runs Qwen3.8 27B well?
With 27.8B parameters, Qwen3.8 27B requires adequate VRAM. High-end GPUs like the RTX 4090 (24GB), RTX 5090 (32GB), or Mac Studio with unified memory are good options. Check our hardware directory for specific recommendations.
What is the best quantization for Qwen3.8 27B?
Q4_K_M is the recommended sweet spot - ~98% of FP16 quality at ~27% of the size. Q5_K_M (~20 GB) is an option if you have spare VRAM. Use our VRAM calculator to compare.
How long can Qwen3.8 27B's context window handle?
Qwen3.8 27B supports a 262,144-token context window - enough for very long documents, codebases, or multi-turn conversations. Real-world usable context may vary by implementation.
What models compete with Qwen3.8 27B?
Qwen3.8 27B competes with other models in its class. Browse our model directory for comparisons, benchmarks, and community reviews to find the best fit.
Nearby options
Similar models and compatible hardware by spec
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