Qwen 2.5 Coder 3B needs ~7.5 GB VRAM. MacBook Pro M3 24GB has 17.3 GB. With Q4_K_M quantization, expect ~39 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
39.0 tok/s
TTFT
4962 ms
Safe context
87K
Memory
7.5 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 | 39.0 tok/s | 2707 ms | 87K |
| Coding | A | Runs well | 39.0 tok/s | 4962 ms | 87K |
| Agentic Coding | A | Runs well | 39.0 tok/s | 7217 ms | 87K |
| Reasoning | A | Runs well | 39.0 tok/s | 5864 ms | 87K |
| RAG | A | Runs well | 39.0 tok/s | 9022 ms | 87K |
How Qwen 2.5 Coder 3B (3B params) fits at each quantization level on MacBook Pro M3 24GB (17.3 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 1.2 GB | Low | A71 |
Q3_K_S | 3 | 1.5 GB | Low | A71 |
NVFP4 | 4 |
Copy-paste commands to run Qwen 2.5 Coder 3B on your machine.
Run
ollama run qwen2.5-coder:3bYour hardware
| Model | Params | Grade | Decode | Capabilities |
|---|---|---|---|---|
| 9B | S | 13.3 tok/s | ||
| 24B | B | 3.8 tok/s |
Yes, MacBook Pro M3 24GB can run Qwen 2.5 Coder 3B with a A grade (Runs well). Expected decode speed: 39.0 tok/s.
Qwen 2.5 Coder 3B (3B parameters) requires approximately 7.5 GB of memory with Q4_K_M quantization.
The recommended quantization for Qwen 2.5 Coder 3B is Q4_K_M, which balances quality and memory efficiency.
On MacBook Pro M3 24GB, Qwen 2.5 Coder 3B achieves approximately 39.0 tokens per second decode speed with a time-to-first-token of 4962ms using Q4_K_M quantization.
For coding workloads, Qwen 2.5 Coder 3B on MacBook Pro M3 24GB receives a A grade with 39.0 tok/s and 87K context.
On MacBook Pro M3 24GB, Qwen 2.5 Coder 3B can safely use up to 87K 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/qwen-2.5-coder-3b-on-m3-24gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview:
1.7 GB |
| Medium |
| A71 |
Q4_K_M | 4 | 1.8 GB | Medium | A71 |
Q5_K_M | 5 | 2.2 GB | High | A72 |
Q6_K | 6 | 2.5 GB | High | A72 |
Q8_0 | 8 | 3.2 GB | Very High | A72 |
F16Best for your GPU | 16 | 6.1 GB | Maximum | A75 |
| 24B | B | 3.8 tok/s |
| 14B | S | 8.6 tok/s |
| 4B | S | 30 tok/s |
Not always. MacBook Pro M3 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.