Yes — Llama 3.3 70B (70B) runs at 7 tok/s on M2 Max with 96 GB RAM using Q4_K_M quantization via Ollama. First token latency is 1.2s. Meta's 70B Llama 3.3 model for Macs with 64–128 GB RAM.
Want to run Llama 3.3 70B faster — or step up to bigger models? Find your Mac →The LLMCheck index estimates Llama 3.3 70B on M2 Max 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 | 7 tok/s |
| Time to first token | 1.2s |
| Quantization | Q4_K_M |
| Minimum RAM | 96 GB |
| Recommended engine | Ollama |
| Parameters | 70B |
| Benchmark date | 2026-08 |
Q4_K_M 70B Ollama M2 Max
The recommended engine for Llama 3.3 70B on M2 Max is Ollama. Install Ollama, then pull the model:
Ollama handles quantization automatically — it will download the Q4_K_M variant (~96 GB) and start an interactive chat session.
| Chip | Speed | First Token | Min RAM | Engine |
|---|---|---|---|---|
| M4 Ultra | 18 tok/s | 2.0s | 192 GB | MLX |
| M5 Max | 15 tok/s | 2.4s | 128 GB | MLX |
| M3 Ultra | 15 tok/s | 0.7s | 256 GB | Ollama |
| M1 Ultra | 14 tok/s | 0.8s | 128 GB | Ollama |
| M5 Max | 12 tok/s | 2.8s | 128 GB | Ollama |
To run Llama 3.3 70B on M2 Max you need:
Llama 3.3 70B needs about 96 GB of unified memory. These current Apple Silicon Macs have the headroom to run it comfortably:
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See how Llama 3.3 70B stacks up against other models on your specific Mac hardware.
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