# DeepSeek-R1-0528 (671B)

> OnPrem World · https://onpremworld.com/en/models/deepseek-r1-0528 · Last updated: 2026-10-14 · CC BY 4.0

The full 671B DeepSeek-R1 (37B active per token): even at 4-bit it needs more memory than any single machine in our catalog.

|  |  |
|---|---|
| Developer | DeepSeek |
| Parameters | 671B (37B active, MoE) |
| Native context | 131,072 tokens |
| Licence | MIT |
| Commercial use | Yes |
| KV cache | Compressed latent KV (MLA), 61 layers |
| Released | 2025-05 |

```
ollama run deepseek-r1:671b
```

## Memory needed

Weights + KV cache + runtime overhead, in GiB. Lower quantization = less memory, slightly lower quality.

| Quantization | 4K | 8K | 32K |
|---|---|---|---|
| Q4_K_M | 398.6 GiB | 398.8 GiB | 400.4 GiB |
| Q5_K_M | 467.5 GiB | 467.7 GiB | 469.3 GiB |
| Q6_K | 541.3 GiB | 541.6 GiB | 543.2 GiB |
| Q8_0 | 697.9 GiB | 698.2 GiB | 699.8 GiB |
| FP16 | 1313.1 GiB | 1313.4 GiB | 1315.0 GiB |

## Which hardware runs it (8K)

| Hardware | Memory | Best quant | tok/s (est.) |
|---|---|---|---|
| GeForce RTX 3060 (12 GB) | 12 GB | Doesn't fit | – |
| GeForce RTX 3090 | 24 GB | Doesn't fit | – |
| GeForce RTX 4060 Ti 16GB | 16 GB | Doesn't fit | – |
| GeForce RTX 4080 SUPER | 16 GB | Doesn't fit | – |
| GeForce RTX 4090 | 24 GB | Doesn't fit | – |
| GeForce RTX 5060 Ti 16GB | 16 GB | Doesn't fit | – |
| GeForce RTX 5070 | 12 GB | Doesn't fit | – |
| GeForce RTX 5070 Ti | 16 GB | Doesn't fit | – |
| GeForce RTX 5080 | 16 GB | Doesn't fit | – |
| GeForce RTX 5090 | 32 GB | Doesn't fit | – |
| Radeon RX 7900 XT | 20 GB | Doesn't fit | – |
| Radeon RX 7900 XTX | 24 GB | Doesn't fit | – |
| Radeon RX 9060 XT 16GB | 16 GB | Doesn't fit | – |
| Radeon RX 9070 XT | 16 GB | Doesn't fit | – |
| Arc B580 | 12 GB | Doesn't fit | – |
| RTX A6000 | 48 GB | Doesn't fit | – |
| RTX 6000 Ada Generation | 48 GB | Doesn't fit | – |
| RTX PRO 5000 72GB Blackwell | 72 GB | Doesn't fit | – |
| RTX PRO 6000 Blackwell Workstation Edition | 96 GB | Doesn't fit | – |
| Radeon AI PRO R9700 | 32 GB | Doesn't fit | – |
| Arc Pro B60 | 24 GB | Doesn't fit | – |
| Arc Pro B70 | 32 GB | Doesn't fit | – |
| M4 Pro | 64 GB | Doesn't fit | – |
| M4 Max (14-core CPU / 32-core GPU) | 36 GB | Doesn't fit | – |
| M4 Max (16-core CPU / 40-core GPU) | 128 GB | Doesn't fit | – |
| M3 Ultra | 512 GB | Doesn't fit | – |
| M5 | 32 GB | Doesn't fit | – |
| M5 Pro | 64 GB | Doesn't fit | – |
| M5 Max (18-core CPU / 32-core GPU) | 36 GB | Doesn't fit | – |
| M5 Max (18-core CPU / 40-core GPU) | 128 GB | Doesn't fit | – |
| M5 Ultra | 512 GB | Doesn't fit | – |
| M6 (16GB configuration, 153 GB/s) | 16 GB | Doesn't fit | – |
| M6 (24GB/32GB configurations, 170 GB/s) | 32 GB | Doesn't fit | – |
| DGX Spark | 128 GB | Doesn't fit | – |
| RTX Spark (N1X) laptops & compact desktops | 128 GB | Doesn't fit | – |
| Ryzen AI Max+ 395 (Strix Halo) systems | 128 GB | Doesn't fit | – |
| Ryzen AI Max+ PRO 495 (Gorgon Halo) systems | 192 GB | Doesn't fit | – |

## Frequently asked questions

### How much VRAM does DeepSeek-R1-0528 (671B) need?

With an 8K context, about 398.8 GiB at Q4_K_M and 698.2 GiB at Q8_0 (weights + KV cache + runtime overhead). Longer contexts need more memory for the KV cache.

### Can DeepSeek-R1-0528 (671B) run on an GeForce RTX 4090?

DeepSeek-R1-0528 (671B) does not fit on the GeForce RTX 4090 (24 GB), even at Q4_K_M with an 8K context.

### Can I run DeepSeek-R1-0528 (671B) on a Mac?

DeepSeek-R1-0528 (671B) does not fit on the M3 Ultra (512 GB), even at Q4_K_M with an 8K context.

### Can DeepSeek-R1-0528 (671B) be used commercially?

DeepSeek-R1-0528 (671B) is released under MIT. The licence allows commercial use (read its conditions).

## Sources

- https://api-docs.deepseek.com/news/news250528
- https://huggingface.co/deepseek-ai/DeepSeek-R1-0528
- https://huggingface.co/deepseek-ai/DeepSeek-R1
- https://huggingface.co/deepseek-ai/DeepSeek-R1-0528/resolve/main/config.json
- https://huggingface.co/api/models/deepseek-ai/DeepSeek-R1-0528?expand[]=safetensors
- https://ollama.com/library/deepseek-r1/tags