Llama 3.1 8B needs ~14.6 GB VRAM. MacBook Pro M4 Max 64GB has 46.1 GB. With Q4_K_M quantization, expect ~83 tok/s.
Operating mode
Interactive favors responsiveness, while light API and scale-out lean harder on serving readiness. The fit stays the same, but the recommendation lens changes.
Current mode
Balanced
Balanced for general local use. Keeps the ranking neutral across personal and serving workflows.
Select quantization to explore
Fit status
Runs well
Decode
82.6 tok/s
TTFT
2344 ms
Safe context
128K
Memory
14.6 GB / 46.1 GB
This setup is broadly balanced for this model.
Shared-memory contention still exists
The OS, browser, and inference runtime all compete for the same physical memory pool, so real-world headroom is less forgiving than raw capacity suggests.
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | B | Runs well | 82.6 tok/s | 1279 ms | 128K |
| Coding | B | Runs well | 82.6 tok/s | 2344 ms | 128K |
| Agentic Coding | A | Runs well | 82.6 tok/s | 3409 ms | 128K |
| Reasoning | B | Runs well | 82.6 tok/s | 2770 ms | 128K |
| RAG | A | Runs well | 82.6 tok/s | 4262 ms | 128K |
How Llama 3.1 8B (8B params) fits at each quantization level on MacBook Pro M4 Max 64GB (46.1 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 3.1 GB | Low | B63 |
Q3_K_S | 3 | 3.9 GB | Low | B63 |
NVFP4 | 4 |
Copy-paste commands to run Llama 3.1 8B on your machine.
Run
ollama run llama3.1Yes, MacBook Pro M4 Max 64GB can run Llama 3.1 8B with a B grade (Runs well). Expected decode speed: 82.6 tok/s.
Llama 3.1 8B (8B parameters) requires approximately 14.6 GB of memory with Q4_K_M quantization.
The recommended quantization for Llama 3.1 8B is Q4_K_M, which balances quality and memory efficiency.
On MacBook Pro M4 Max 64GB, Llama 3.1 8B achieves approximately 82.6 tokens per second decode speed with a time-to-first-token of 2344ms using Q4_K_M quantization.
For coding workloads, Llama 3.1 8B on MacBook Pro M4 Max 64GB receives a B grade with 82.6 tok/s and 128K context.
On MacBook Pro M4 Max 64GB, Llama 3.1 8B can safely use up to 128K tokens of context. The model's official context limit is 128K, but available memory constrains the safe maximum.
Paste this snippet into any page to show a live fit card.
<iframe src="https://willitrunai.com/embed/llama-3.1-8b-on-m4-max-64gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview:
4.5 GB |
| Medium |
| B63 |
Q4_K_M | 4 | 4.9 GB | Medium | B63 |
Q5_K_M | 5 | 5.8 GB | High | B63 |
Q6_K | 6 | 6.6 GB | High | B63 |
Q8_0 | 8 | 8.6 GB | Very High | B64 |
F16Best for your GPU | 16 | 16.4 GB | Maximum | B66 |
Not always. MacBook Pro M4 Max 64GB can often fit larger models thanks to unified memory, but a discrete GPU with dedicated high-bandwidth VRAM may still decode faster once the model fits. For this combination, the important distinction is capacity versus sustained throughput.