Apple M5 Max (40-core GPU, 128GB) × Llama 3.1 8B Instruct
Can the Apple M5 Max (40-core GPU, 128GB) run Llama 3.1 8B Instruct?
Yes
Yes. The Apple M5 Max (40-core GPU, 128GB) can run Llama 3.1 8B Instruct at up to F16 (needs ~18.4 GB of 96.0 GB usable), at an estimated ~94.5 tokens/sec at Q4_K_M.
Speed is estimated from memory bandwidth calibrated with a measured 119.92 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 | ✅ | ~118 |
| Q4_K_M | 6.9 GB | ✅ | ~94.5 |
| Q5_K_M | 7.7 GB | ✅ | ~80.4 |
| Q6_K | 8.7 GB | ✅ | ~69.5 |
| Q8_0 | 10.6 GB | ✅ | ~53.9 |
| F16 | 18.4 GB | ✅ | ~28.6 |
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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