Mac mini M4 64GBBudget pick
64 GB Unified (+16)
C
Adds memory headroom for longer context windows and future model growth.7.3 tok/s decode
Adds memory headroom for longer context windows and future model growth.
~$1,099 MSRP
Qwen3.5 35B A3B needs ~31.5 GB VRAM. MacBook Pro M4 Pro 48GB has 34.6 GB. With Q4_K_M quantization, expect ~18 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
Tight fit
Decode
17.7 tok/s
TTFT
10924 ms
Safe context
28K
Memory
31.5 GB / 34.6 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 | C | Tight fit | 17.7 tok/s | 5958 ms | 28K |
| Coding | C | Tight fit | 17.7 tok/s | 10924 ms | 28K |
| Agentic Coding | C | Runs with offload (needs ~0.6 GB host RAM) | 16.6 tok/s | 16919 ms | 28K |
| Reasoning | C | Tight fit | 17.7 tok/s | 12910 ms | 28K |
| RAG | C | Runs with offload (needs ~0.6 GB host RAM) | 16.6 tok/s | 21149 ms |
How Qwen3.5 35B A3B (35B params) fits at each quantization level on MacBook Pro M4 Pro 48GB (34.6 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 13.7 GB | Low | C48 |
Q3_K_S | 3 | 17.2 GB | Low | C49 |
NVFP4 | 4 |
Copy-paste commands to run Qwen3.5 35B A3B on your machine.
Run
docker run --rm -it ghcr.io/ggerganov/llama.cpp:full \
--hf-repo "lmstudio-community/Qwen3.5-35B-A3B-GGUF" \
--hf-file "Qwen3.5-35B-A3B-GGUF-Q4_K_M.gguf" \
-c 4096 -ngl 99Upgrade options
Adds memory headroom for longer context windows and future model growth.
~$1,099 MSRP
Adds memory headroom for longer context windows and future model growth.
~$1,599 MSRP
Adds memory headroom for longer context windows and future model growth.
~$2,499 MSRP
Yes, MacBook Pro M4 Pro 48GB can run Qwen3.5 35B A3B with a C grade (Tight fit). Expected decode speed: 17.7 tok/s.
Qwen3.5 35B A3B (35B parameters) requires approximately 31.5 GB of memory with Q4_K_M quantization.
The recommended quantization for Qwen3.5 35B A3B is Q4_K_M, which balances quality and memory efficiency.
On MacBook Pro M4 Pro 48GB, Qwen3.5 35B A3B achieves approximately 17.7 tokens per second decode speed with a time-to-first-token of 10924ms using Q4_K_M quantization.
For coding workloads, Qwen3.5 35B A3B on MacBook Pro M4 Pro 48GB receives a C grade with 17.7 tok/s and 28K context.
On MacBook Pro M4 Pro 48GB, Qwen3.5 35B A3B can safely use up to 28K tokens of context. The model's official context limit is —, 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/hf-lmstudio-community--qwen3-5-35b-a3b-gguf-on-m4-pro-48gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview:
| 28K |
19.6 GB |
| Medium |
| C49 |
Q4_K_M | 4 | 21.3 GB | Medium | C49 |
Q5_K_MBest for your GPU | 5 | 25.2 GB | High | C49 |
Q6_K | 6 | 28.7 GB | High | F0 |
Q8_0 | 8 | 37.5 GB | Very High | F0 |
F16 | 16 | 71.8 GB | Maximum | F0 |
Not always. MacBook Pro M4 Pro 48GB 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.