DeepSeek V3.2 needs ~291.9 GB VRAM. AMD Instinct MI350X 288GB has 288.0 GB. With Q2_K quantization, expect ~44 tok/s.
Operating mode
Interactive favors responsiveness, while light API and scale-out lean harder on serving readiness. The fit stays the same, but the recommendation lens changes.
Current mode
Balanced
Balanced for general local use. Keeps the ranking neutral across personal and serving workflows.
Select quantization to explore
151.5 GB over capacity — needs offload or smaller quantization
Fit status
Too heavy
Decode
14.0 tok/s
TTFT
13787 ms
Safe context
4K
Memory
439.5 GB / 288.0 GB
Offload
30%
This setup is broadly balanced for this model.
Very little memory headroom
You can run the model, but there is not much room left for longer context, bigger batches, extra apps, or future model updates.
Buy headroom, not only minimum fit
A slightly larger memory tier gives you safer context growth and makes the recommendation more future-proof.
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | F | Too heavy | 14.1 tok/s | 7512 ms | 4K |
| Coding | F | Too heavy | 14.0 tok/s | 13787 ms | 4K |
| Agentic Coding | F | Too heavy | 14.0 tok/s | 20098 ms | 4K |
| Reasoning | F | Too heavy | 14.0 tok/s | 16293 ms | 4K |
| RAG | F | Too heavy | 12.7 tok/s | 27615 ms | 4K |
How DeepSeek V3.2 (671B params) fits at each quantization level on AMD Instinct MI350X 288GB (288.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 261.7 GB | Low | F0 |
Q3_K_S | 3 | 328.8 GB | Low | F0 |
NVFP4 | 4 |
Copy-paste commands to run DeepSeek V3.2 on your machine.
Run
ollama run deepseek-v3.2Yes, AMD Instinct MI350X 288GB can run DeepSeek V3.2 at Q2_K quantization (Runs with offload (needs ~3.5 GB host RAM)). The recommended Q4_K_M requires 439.5 GB which exceeds available memory, but at Q2_K it needs only 291.9 GB. Expected decode speed: 44.2 tok/s.
DeepSeek V3.2 (671B parameters) requires approximately 439.5 GB at Q4_K_M quantization. On AMD Instinct MI350X 288GB, it fits at Q2_K using 291.9 GB.
The recommended quantization is Q4_K_M, but on AMD Instinct MI350X 288GB the best fitting quantization is Q2_K, which uses 291.9 GB.
On AMD Instinct MI350X 288GB, DeepSeek V3.2 achieves approximately 44.2 tokens per second decode speed with a time-to-first-token of 4381ms using Q2_K quantization.
For coding workloads, DeepSeek V3.2 on AMD Instinct MI350X 288GB receives a F grade with 14.0 tok/s and 4K context.
On AMD Instinct MI350X 288GB, DeepSeek V3.2 can safely use up to 4K tokens of context at Q2_K quantization. The model's official context limit is 128K, but available memory constrains the safe maximum.
Paste this snippet into any page to show a live fit card.
<iframe src="https://willitrunai.com/embed/deepseek-v3.2-671b-on-instinct-mi350x-288gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview:
375.8 GB |
| Medium |
| F0 |
Q4_K_M | 4 | 409.3 GB | Medium | F0 |
Q5_K_M | 5 | 483.1 GB | High | F0 |
Q6_K | 6 | 550.2 GB | High | F0 |
Q8_0 | 8 | 718.0 GB | Very High | F0 |
F16 | 16 | 1375.6 GB | Maximum | F0 |
Buy headroom, not only minimum fit. A slightly larger memory tier gives you safer context growth and makes the recommendation more future-proof.