Pixtral 12B needs ~13.3 GB VRAM. MacBook Air M4 24GB has 17.3 GB. With Q4_K_M quantization, expect ~11 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
11.2 tok/s
TTFT
17339 ms
Safe context
42K
Memory
13.3 GB / 17.3 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 | A | Runs well | 11.2 tok/s | 9457 ms | 42K |
| Coding | A | Runs well | 11.2 tok/s | 17339 ms | 42K |
| Agentic Coding | A | Tight fit | 11.2 tok/s | 25220 ms | 42K |
| Reasoning | A | Runs well | 11.2 tok/s | 20491 ms | 42K |
| RAG | A | Tight fit | 11.2 tok/s | 31525 ms | 42K |
How Pixtral 12B (12B params) fits at each quantization level on MacBook Air M4 24GB (17.3 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 4.7 GB | Low | A71 |
Q3_K_S | 3 | 5.9 GB | Low | A72 |
NVFP4 | 4 |
Copy-paste commands to run Pixtral 12B on your machine.
Run
ollama run pixtralYour hardware
| Model | Params | Grade | Decode | Capabilities |
|---|---|---|---|---|
 Magistral Small 2507 | 24B | A | 7.3 tok/s | |
| Devstral Small 2 24B Instruct | 24B | A | 7.3 tok/s |
Yes, MacBook Air M4 24GB can run Pixtral 12B with a A grade (Runs well). Expected decode speed: 11.2 tok/s.
Pixtral 12B (12B parameters) requires approximately 13.3 GB of memory with Q4_K_M quantization.
The recommended quantization for Pixtral 12B is Q4_K_M, which balances quality and memory efficiency.
On MacBook Air M4 24GB, Pixtral 12B achieves approximately 11.2 tokens per second decode speed with a time-to-first-token of 17339ms using Q4_K_M quantization.
For coding workloads, Pixtral 12B on MacBook Air M4 24GB receives a A grade with 11.2 tok/s and 42K context.
On MacBook Air M4 24GB, Pixtral 12B can safely use up to 42K tokens of context. The model's official context limit is 131K, 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/pixtral-12b-on-m4-air-24gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview:
6.7 GB |
| Medium |
| A73 |
Q4_K_M | 4 | 7.3 GB | Medium | A74 |
Q5_K_M | 5 | 8.6 GB | High | A75 |
Q6_K | 6 | 9.8 GB | High | A75 |
Q8_0Best for your GPU | 8 | 12.8 GB | Very High | A74 |
F16 | 16 | 24.6 GB | Maximum | F0 |
 Qwen 3 14B | 14B | S | 9.6 tok/s |
 Phi-4-reasoning-plus 14B | 14.7B | S | 9.4 tok/s |
| Devstral Small 1.1 | 24B | B | 7.3 tok/s |
Not always. MacBook Air M4 24GB 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.