qwen
27B parameters
Commercial OK
Multimodal
Reviewed October 2026

Qwen3.8 27B

Dense 27B Qwen model with a vision encoder, published on Hugging Face in August 2026 under Apache 2.0. The model card lists 64 layers and a native context of 262,144 tokens, extensible to 1,000,000. GGUF builds exist (Q4_K_M is 16.5 GB in unsloth/Qwen3.8-27B-GGUF, plus a 0.9 GB vision projector) and Ollama carries qwen3.8:27b and qwen3.8:27b-mlx. We have not benchmarked it yet; the VRAM figures here are planning estimates from file size, not measurements.

License: Apache 2.0·Context: 262,144 tokens

Overview

Dense 27B Qwen model with a vision encoder, published on Hugging Face in August 2026 under Apache 2.0. The model card lists 64 layers and a native context of 262,144 tokens, extensible to 1,000,000. GGUF builds exist (Q4_K_M is 16.5 GB in unsloth/Qwen3.8-27B-GGUF, plus a 0.9 GB vision projector) and Ollama carries qwen3.8:27b and qwen3.8:27b-mlx. We have not benchmarked it yet; the VRAM figures here are planning estimates from file size, not measurements.

Strengths

  • Apache 2.0
  • Vision input
  • Fits a 24GB card at Q4_K_M
  • 262K native context

Weaknesses

  • No first-party benchmark yet
  • Does not fit 16GB cards fully at Q4

Quantization variants

Each quantization trades model quality for file size and VRAM. Q4_K_M is the most popular starting point.

QuantizationFile sizeVRAM required
Q4_K_M16.5 GB20 GB
Q5_K_M19.8 GB24 GB
Q6_K22.0 GB26 GB
Q8_029.0 GB34 GB

Get the model

Ollama

One-line install

ollama run qwen3.8:27bRead our Ollama review →

HuggingFace

Original weights

huggingface.co/Qwen/Qwen3.8-27B

Source repository — direct quantization required.

Hardware that runs this

Cards with enough VRAM for at least one quantization of Qwen3.8 27B.

AMD Radeon RX 7900 XT
20GB · amd · fits by VRAM, no benchmark yet
NVIDIA RTX 2080 Ti 22GB (China-mod)
22GB · nvidia · fits by VRAM, no benchmark yet
NVIDIA GeForce RTX 3090 Ti
24GB · nvidia · fits by VRAM, no benchmark yet
NVIDIA GeForce RTX 5090 Mobile
24GB · nvidia · fits by VRAM, no benchmark yet
NVIDIA L4
24GB · nvidia · fits by VRAM, no benchmark yet
ASUS ROG Strix Scar 18 (RTX 5090 Mobile)
24GB · nvidia · fits by VRAM, no benchmark yet
AMD Radeon RX 7900 XTX
24GB · amd · fits by VRAM, no benchmark yet
NVIDIA GeForce RTX 3090
24GB · nvidia · fits by VRAM, no benchmark yet
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Frequently asked

What's the minimum VRAM to run Qwen3.8 27B?

20GB of VRAM is enough to run Qwen3.8 27B at the Q4_K_M quantization (file size 16.5 GB). Higher-quality quantizations need more.

Can I use Qwen3.8 27B commercially?

Yes — Qwen3.8 27B ships under the Apache 2.0, which permits commercial use. Always read the license text before deployment.

What's the context length of Qwen3.8 27B?

Qwen3.8 27B supports a context window of 262,144 tokens (about 262K).

How do I install Qwen3.8 27B with Ollama?

Run `ollama pull qwen3.8:27b` to download, then `ollama run qwen3.8:27b` to start a chat session. The default quantization is Q4_K_M.

Does Qwen3.8 27B support images?

Yes — Qwen3.8 27B is multimodal and accepts text + vision inputs. Vision support requires a runner that handles its image-conditioning architecture.

Source: huggingface.co/Qwen/Qwen3.8-27B

Reviewed by RunLocalAI Editorial. See our editorial policy for how we research and verify model claims.

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Verify Qwen3.8 27B runs on your specific hardware before committing money.

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