Deepseek AI Deepseek Coder V2 Instruct 0724 speed on Apple M2 Ultra and quantization-level VRAM fit.
Apple M2 Ultra meets the minimum VRAM requirement for Q4 inference of Deepseek AI Deepseek Coder V2 Instruct 0724. Review the quantization breakdown below to see how higher precision settings impact VRAM and throughput.
Apple M2 Ultra can run Deepseek AI Deepseek Coder V2 Instruct 0724 with Q4 quantization. At approximately 16 tokens/second, you can expect Basic speed - best for non-interactive tasks.
You have 74GB headroom, which is sufficient for system overhead and smooth operation.
| Quantization | VRAM needed | VRAM available | Estimated speed | Verdict |
|---|---|---|---|---|
| Q4 | 118GB | 192GB | 16.10 tok/s | ✅ Fits comfortably |
| Q8 | 236GB | 192GB | 11.27 tok/s | ❌ Not recommended |
| FP16 | 472GB | 192GB | 6.12 tok/s | ❌ Not recommended |
Need a GPU with 118GB+ VRAM? These guides match your requirements.
Check current pricing links for Apple M2 Ultra and similar cards.
Open Apple M2 Ultra buy links →Use workload-focused recommendations before committing to a purchase.
Browse best GPU guides →Compare complete systems if you want ready-to-run hardware.
Compare prebuilt systems →Rent cloud GPUs by the hour — no upfront hardware cost.
Apple M2 Ultra can run Deepseek AI Deepseek Coder V2 Instruct 0724 at Q4 with an estimated 16 tok/s.
Q4 inference is estimated to need about 118GB VRAM on this page, while Apple M2 Ultra has 192GB available.
If you need more speed or context headroom, compare alternative GPUs below and check higher-tier VRAM options.