M3 Ultra 256GB vs NVIDIA V100 32GB for local LLMs
10 reports on the M3 Ultra 256GB and 25 on the NVIDIA V100 32GB
Which is faster for local LLMs?
On Qwen3.8 27B at 4-bit, the M3 Ultra 256GB has 14.0 generation tokens/s (one run); prompt processing 93.1 tokens/s (one run); the NVIDIA V100 32GB has 31.4 generation tokens/s (2 runs); prompt processing 940.5 tokens/s (2 runs). Those are community reports whose engines and settings differ, so the gap is a rough sign, not a controlled measure of the two cards. Memory bandwidth, which caps how fast a card can write, is 10% higher on the NVIDIA V100 32GB (819 GB/s on the M3 Ultra 256GB, 900 on the NVIDIA V100 32GB).
- Memory
- 256GB unified
- Memory bandwidth
- 819 GB/s
- FP16 compute
- 28.4 TFLOPS
- Reports
- 10
- Memory
- 32GB
- Memory bandwidth
- 900 GB/s
- FP16 compute
- 125 TFLOPS
- Reports
- 25
Measured on both
Generation and prompt processing speeds from plain runs (one device, one request, no speculative decoding, the whole model in the device's memory) of the same model size at the same bit class. Each side shows the engines and reported context behind its median. Context can mean a configured window or prompt depth, so these are community comparisons with differing settings. How to read these
| Model | M3 Ultra 256GB | NVIDIA V100 32GB |
|---|---|---|
| Qwen3.8 27B4-bit | 14.0one runPP 93.1 (one run)Ollamacontext not stated | 31.42 runsPP 940.5 (2 runs)llama.cpp, 1 not stated32K to 128K context |
Estimated by the calculator
The quant the calculator recommends for each card and its estimated speed at a 32,768-token context with 32 GB of system RAM, from memory bandwidth and the model's shape. Where a model was also measured above, the measurement wins.
| Model | M3 Ultra 256GB | NVIDIA V100 32GB |
|---|---|---|
| Qwen3.8 27B | 8.0 t/sFP16 | 22.6 t/sQ6_K |
| Qwen3.8 125B · 6B active | 27.3 t/sQ8_0 | 19.4 t/sQ2_K, experts in RAM |
| DeepSeek V4 Flash 284B · 13B active | 36.0 t/sQ4_K_M | doesn't fit at these settings |
| Qwen3.6 35B · 3B active | 28.7 t/sFP16 | 81.9 t/sQ5_K_M |
| Qwen3.6 27B | 8.0 t/sFP16 | 22.6 t/sQ6_K |
| Gemma 4 26B · 4B active | 21.5 t/sFP16 | 57.5 t/sQ6_K |
| GLM-5.3 320B · 18B active | 19.1 t/sQ3_K_M | doesn't fit at these settings |
Change the context, RAM or model in the calculator: M3 Ultra 256GB · NVIDIA V100 32GB
Every report on each card, with its source: M3 Ultra 256GB · NVIDIA V100 32GB