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Pixtral Large 124B needs ~88.8 GB but MacBook Pro M4 Max 64GB only has 46.1 GB. Try a smaller quantization or lighter model.
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
42.7 GB over capacity — needs offload or smaller quantization
Fit status
Too heavy
Decode
3.9 tok/s
TTFT
49824 ms
Safe context
4K
Memory
88.8 GB / 46.1 GB
Offload
50%
Usable shared or unified memory is the main blocker for this model.
Not enough usable memory
The model needs 88.8 GB, but this setup only exposes 46.1 GB of usable shared or unified memory.
Move to a larger memory pool
A larger unified-memory SKU or a discrete high-bandwidth GPU is the cleanest way to make this model practical.
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | F | Too heavy | 4.0 tok/s | 26702 ms | 4K |
| Coding | F | Too heavy | 3.9 tok/s | 49824 ms | 4K |
| Agentic Coding | F | Too heavy | 3.9 tok/s | 72471 ms | 4K |
| Reasoning | F | Too heavy | 3.9 tok/s | 58883 ms | 4K |
| RAG | F | Too heavy | 3.9 tok/s | 90589 ms | 4K |
How Pixtral Large 124B (124B params) fits at each quantization level on MacBook Pro M4 Max 64GB (46.1 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 48.4 GB | Low | F0 |
Q3_K_S | 3 | 60.8 GB | Low | F0 |
NVFP4 | 4 | 69.4 GB | Medium | F0 |
Q4_K_M | 4 | 75.6 GB | Medium | F0 |
Q5_K_M | 5 | 89.3 GB | High | F0 |
Q6_K | 6 | 101.7 GB | High | F0 |
Q8_0 | 8 | 132.7 GB | Very High | F0 |
F16 | 16 | 254.2 GB | Maximum | F0 |
Upgrade options
Makes the model fit on the accelerator instead of staying completely out of reach.
Removes host-memory offload, which is usually the single biggest latency and throughput win.
~$2,499 MSRP
Makes the model fit on the accelerator instead of staying completely out of reach.
Removes host-memory offload, which is usually the single biggest latency and throughput win.
~$3,999 MSRP
Makes the model fit on the accelerator instead of staying completely out of reach.
Removes host-memory offload, which is usually the single biggest latency and throughput win.
~$3,999 MSRP
Makes the model fit on the accelerator instead of staying completely out of reach.
Removes host-memory offload, which is usually the single biggest latency and throughput win.
~$12,000 MSRP