# Hy3 GPU requirements

Hy3 has 299B parameters. To serve it, plan for about 717 GB of GPU memory in 16-bit, 359 GB in 8-bit or 179 GB in 4-bit, including about 20% for the KV cache and activations.

It is a mixture of experts: 192 experts, 8 of them active for each token. All of them stay in GPU memory, so plan memory for all 299B parameters.

[Deploy it on Arrakis](/console/#/models?model=tencent/Hy3).

## What it takes to serve it

| Precision | Memory and the smallest setup |
|---|---|
| 16-bit | 717 GB: 4 × [B200](/gpus/b200.html.md), from $27.16 per hour for all 4 |
| 8-bit | 359 GB: 2 × [B200](/gpus/b200.html.md), from $13.58 per hour for all 2 |
| 4-bit | 179 GB: one [B200](/gpus/b200.html.md), from $6.79 per GPU-hour |

## What it takes to fine-tune it

| Method | Memory and the smallest setup |
|---|---|
| QLoRA | 209 GB: one [B300](/gpus/b300.html.md), from $4.60 per GPU-hour |
| LoRA | 717 GB: 4 × [B200](/gpus/b200.html.md), from $27.16 per hour for all 4 |
| Full fine-tuning | 4,781 GB: more than one 8-GPU machine |

## About the model

| | |
|---|---|
| Parameters | `299B` |
| Experts | `192` |
| Experts for each token | `8` |
| Context window (tokens) | `262,144` |
| Published in | `BF16` |
| License | `apache-2.0` |
| Released | `2026-07-02` |
| Weights | [tencent/Hy3](https://huggingface.co/tencent/Hy3) |

## Serve it yourself

```
vllm serve tencent/Hy3 --tensor-parallel-size 4
```

## Questions

**How much GPU memory does Hy3 need?** To serve it, about 717 GB in 16-bit, 359 GB in 8-bit, 179 GB in 4-bit, including about 20% for the KV cache and activations. To fine-tune it, about 209 GB with QLoRA, 717 GB with LoRA and 4,781 GB for full fine-tuning with Adam, before activations.

**Can I run Hy3 on one GPU?** Yes, quantized. In 4-bit it needs about 179 GB, which fits on one B200. In 16-bit it needs 4 B200 GPUs.

**What does it cost to run Hy3?** In 16-bit it needs 4 B200 GPUs; in 4-bit, one B200. 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 Hy3 on Arrakis?** Open Models in the Arrakis console, paste tencent/Hy3, 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).