RTX PRO 5000 Blackwell 48GBBudget pick1344 GB/s (+798)
C
Raises estimated decode speed by about 88%.52.9 tok/s decode
Raises estimated decode speed by about 88%.
~$4,999 MSRP
Qwen3.5 35B A3B needs ~33.3 GB VRAM. MacBook Pro M4 Max 64GB has 46.1 GB. With Q4_K_M quantization, expect ~28 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
28.1 tok/s
TTFT
6882 ms
Safe context
66K
Memory
33.3 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 | C | Runs well | 28.1 tok/s | 3754 ms | 66K |
| Coding | C | Runs well | 28.1 tok/s | 6882 ms | 66K |
| Agentic Coding | C | Runs well | 28.1 tok/s | 10010 ms | 66K |
| Reasoning | C | Runs well | 28.1 tok/s | 8133 ms | 66K |
| RAG | C | Runs well | 28.1 tok/s | 12513 ms | 66K |
How Qwen3.5 35B A3B (35B params) fits at each quantization level on MacBook Pro M4 Max 64GB (46.1 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 13.7 GB | Low | C45 |
Q3_K_S | 3 | 17.2 GB | Low | C46 |
NVFP4 | 4 | 19.6 GB | Medium | C47 |
Q4_K_M | 4 | 21.3 GB | Medium | C47 |
Q5_K_M | 5 | 25.2 GB | High | C49 |
Q6_K | 6 | 28.7 GB | High | C48 |
Q8_0Best for your GPU | 8 | 37.5 GB | Very High | C48 |
F16 | 16 | 71.8 GB | Maximum | F0 |
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
Yes, MacBook Pro M4 Max 64GB can run Qwen3.5 35B A3B with a C grade (Runs well). Expected decode speed: 28.1 tok/s.
Qwen3.5 35B A3B (35B parameters) requires approximately 33.3 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 Max 64GB, Qwen3.5 35B A3B achieves approximately 28.1 tokens per second decode speed with a time-to-first-token of 6882ms using Q4_K_M quantization.
For coding workloads, Qwen3.5 35B A3B on MacBook Pro M4 Max 64GB receives a C grade with 28.1 tok/s and 66K context.
On MacBook Pro M4 Max 64GB, Qwen3.5 35B A3B can safely use up to 66K tokens of context. The model's official context limit is —, but available memory constrains the safe maximum.
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.
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-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: