Family Qwen · 397B parameters

Qwen 3.5 397B-A17B

Flagship MoE with 397B/17B active parameters. #5 on Artificial Analysis open. 262k ctx.

🇨🇳 Alibaba·License Apache 2.0·Context 255.859375k tokens·Output February 2026← Catalog

01What it can do

Strengths
  • #5 Artificial Analysis open
  • 262k ctx
  • Apache 2.0
Limitations to know
  • —240+ GB in Q4
  • —MoE → multi-GPU deployment
Architecture
397B/17B active MoE · 262k ctx · hybrid thinking
Training
New flagship Qwen 3.5 family.
Ideal for
Open frontierReasoningMultilingual

04Install

Install Ollama for your OS. Check the model and its quantization before downloading. Start with 4096 tokens of context, then check placement with ollama ps. A command below is not proof that a test was run on your machine.

$# HuggingFace : Qwen/Qwen3.5-397B-A17B (alternative locale plus accessible : ollama run qwen3.5:122b)
⚠
First download: between 2 and 40 GB depending on the selected quantization. Plan for sufficient disk space; a stable connection is recommended. Subsequent launches are instant.

02Required memory

Approximate GPU VRAM required to run this model, including 4k tokens of context overhead. For a longer context, add ~1 GB per 8k-token increment.

Q4_K_M
The lightest, ~5% loss
240 GB
Q5_K_M
Good quality/size compromise
285 GB
Q8_0
Nearly indistinguishable from FP16
425 GB
FP16
Full precision — server use
794 GB
Fallback CPU · If you don't have a GPU, allow 280 GB of RAM minimum to run this model at reduced speed.

What hardware do you need for Qwen 3.5 397B-A17B?

To run Qwen 3.5 397B-A17B locally with Q4 quantization, you need about 240 GB of VRAM. An option to compare: BOSGAME M5 128GB / 2TB (Ryzen AI Max+ 395) — this model exceeds this mini-PC's GPU capacity: choose a smaller model or suitable infrastructure.

Current offer: BOSGAME M5 128GB / 2TB (Ryzen AI Max+ 395)
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This model in your private ChatGPT, without the cloud

Too large for your machine? The kit gives you the model that fits in your VRAM

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03Expected speed

Tokens generated per second in Q4_K_M, 4k context. Beyond 20 t/s, reading is comfortable. Below 10 t/s, that's just for testing.

Entry-level
~2t/s
GTX 1650, RX 6600, MBA M2 8GB
Mid-range
~7t/s
RTX 4060, 4070, MBP M3 Pro
High-end
~20t/s
RTX 4090, M4 Max, Radeon 7900