# Qwen3.5-397B-A17B GPU requirements

Qwen3.5-397B-A17B has 403B parameters. To serve it, plan for about 968 GB of GPU memory in 16-bit, 484 GB in 8-bit or 242 GB in 4-bit, including about 20% for the KV cache and activations.

It is a mixture of experts: 512 experts, 10 of them active for each token. All of them stay in GPU memory, so plan memory for all 403B parameters.

[Deploy it on Arrakis](/console/#/models?model=Qwen/Qwen3.5-397B-A17B).

## What it takes to serve it

| Precision | Memory and the smallest setup |
|---|---|
| 16-bit | 968 GB: 4 × [B300](/gpus/b300.html.md), from $18.40 per hour for all 4 |
| 8-bit | 484 GB: 2 × [B300](/gpus/b300.html.md), from $9.20 per hour for all 2 |
| 4-bit | 242 GB: one [B300](/gpus/b300.html.md), from $4.60 per GPU-hour |

## What it takes to fine-tune it

| Method | Memory and the smallest setup |
|---|---|
| QLoRA | 282 GB: 4 × [H100](/gpus/h100.html.md), from $6.60 per hour for all 4 |
| LoRA | 968 GB: 4 × [B300](/gpus/b300.html.md), from $18.40 per hour for all 4 |
| Full fine-tuning | 6,454 GB: more than one 8-GPU machine |

## About the model

| | |
|---|---|
| Parameters | `403B` |
| Active for each token | `17B` |
| Experts | `512` |
| Experts for each token | `10` |
| Context window (tokens) | `262,144` |
| Published in | `BF16` |
| License | `apache-2.0` |
| Released | `2026-02-16` |
| Weights | [Qwen/Qwen3.5-397B-A17B](https://huggingface.co/Qwen/Qwen3.5-397B-A17B) |

## Serve it yourself

```
vllm serve Qwen/Qwen3.5-397B-A17B --tensor-parallel-size 4
```

## Questions

**How much GPU memory does Qwen3.5-397B-A17B need?** To serve it, about 968 GB in 16-bit, 484 GB in 8-bit, 242 GB in 4-bit, including about 20% for the KV cache and activations. To fine-tune it, about 282 GB with QLoRA, 968 GB with LoRA and 6,454 GB for full fine-tuning with Adam, before activations.

**Can I run Qwen3.5-397B-A17B on one GPU?** Yes, quantized. In 4-bit it needs about 242 GB, which fits on one B300. In 16-bit it needs 4 B300 GPUs.

**What does it cost to run Qwen3.5-397B-A17B?** In 16-bit it needs 4 B300 GPUs; in 4-bit, one B300. Each setup on this page shows the lowest price per GPU-hour on Arrakis right now, and you pay by the hour from a prepaid balance.

**How do I deploy Qwen3.5-397B-A17B on Arrakis?** Open Models in the Arrakis console, paste Qwen/Qwen3.5-397B-A17B, choose vLLM, SGLang or llama.cpp, and rent a GPU it fits on. You get an OpenAI-compatible endpoint with its own API key, and root SSH to the machine.


More models: [/models](/models.html.md).