Yes — Llama 3.1 8B (8B) runs at 62 tok/s on M3 Pro with 18 GB RAM using Q4_K_M quantization via Ollama. First token latency is 0.7s. Meta's widely-adopted 8B Llama 3.1 model with great ecosystem support.
Want to run Llama 3.1 8B faster — or step up to bigger models? Find your Mac →The LLMCheck index estimates Llama 3.1 8B on M3 Pro using our published methodology: Q4_K_M quantization, memory-bandwidth scaling, and cross-referenced third-party benchmarks where available. Figures are transparent estimates — own this config? Submit a real benchmark →
| Metric | Value |
|---|---|
| Tokens per second | 62 tok/s |
| Time to first token | 0.7s |
| Quantization | Q4_K_M |
| Minimum RAM | 18 GB |
| Recommended engine | Ollama |
| Parameters | 8B |
| Benchmark date | 2026-01 |
Q4_K_M 8B Ollama M3 Pro
The recommended engine for Llama 3.1 8B on M3 Pro is Ollama. Install Ollama, then pull the model:
Ollama handles quantization automatically — it will download the Q4_K_M variant (~18 GB) and start an interactive chat session.
| Chip | Speed | First Token | Min RAM | Engine |
|---|---|---|---|---|
| M5 Max | 138 tok/s | 0.3s | 128 GB | MLX |
| M4 | 75 tok/s | 0.6s | 16 GB | Ollama |
| M2 | 48 tok/s | 0.8s | 8 GB | Ollama |
| M1 | 40 tok/s | 1.1s | 16 GB | Ollama |
To run Llama 3.1 8B on M3 Pro you need:
Llama 3.1 8B needs about 18 GB of unified memory. These current Apple Silicon Macs have the headroom to run it comfortably:
As an Amazon Associate, LLMCheck earns from qualifying purchases. These affiliate links cost you nothing extra and help keep our benchmarks free.
See how Llama 3.1 8B stacks up against other models on your specific Mac hardware.
Open Compare Tool Full Leaderboard