Apple M4 Pro (20-core GPU, 48GB) × Llama 3.1 8B Instruct
Can the Apple M4 Pro (20-core GPU, 48GB) run Llama 3.1 8B Instruct?
Yes
Yes. The Apple M4 Pro (20-core GPU, 48GB) can run Llama 3.1 8B Instruct at up to F16 (needs ~18.4 GB of 36.0 GB usable), at an estimated ~40.0 tokens/sec at Q4_K_M.
Speed is estimated from memory bandwidth calibrated with a measured 50.74 tok/s Llama 2 7B Q4_0 result (source). No direct public benchmark of this exact pair is recorded yet.
By quantization (8K context)
| Quant | Memory needed | Fits? | Est. tok/s |
|---|---|---|---|
| Q3_K_M | 5.9 GB | ✅ | ~49.7 |
| Q4_K_M | 6.9 GB | ✅ | ~40.0 |
| Q5_K_M | 7.7 GB | ✅ | ~34.0 |
| Q6_K | 8.7 GB | ✅ | ~29.4 |
| Q8_0 | 10.6 GB | ✅ | ~22.8 |
| F16 | 18.4 GB | ✅ | ~12.1 |
Fastest hardware for Llama 3.1 8B Instruct
- NVIDIA GeForce RTX 5090 — ~229 tok/s at Q4_K_M
- NVIDIA GeForce RTX 4090 — ~147 tok/s at Q4_K_M
- AMD Radeon RX 7900 XTX — ~145 tok/s at Q4_K_M
- NVIDIA GeForce RTX 5080 — ~143 tok/s at Q4_K_M
- NVIDIA GeForce RTX 5070 Ti — ~139 tok/s at Q4_K_M
No suitable GPU? Rent one by the hour on Vast.ai or RunPod (affiliate links).
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