Qwen3.5 4B needs ~17.6 GB VRAM. Mac Studio M2 Ultra 128GB has 92.2 GB. With Q4_K_M quantization, expect ~56 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
56.0 tok/s
TTFT
3457 ms
Safe context
2.6M
Memory
17.6 GB / 92.2 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 | 56.0 tok/s | 1886 ms | 2.6M |
| Coding | C | Runs well | 56.0 tok/s | 3457 ms | 2.6M |
| Agentic Coding | C | Runs well | 56.0 tok/s | 5029 ms | 2.6M |
| Reasoning | C | Runs well | 56.0 tok/s | 4086 ms | 2.6M |
| RAG | C | Runs well | 56.0 tok/s | 6286 ms | 2.6M |
How Qwen3.5 4B (4B params) fits at each quantization level on Mac Studio M2 Ultra 128GB (92.2 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 1.6 GB | Low | D39 |
Q3_K_S | 3 | 2.0 GB | Low | D39 |
NVFP4 | 4 |
Copy-paste commands to run Qwen3.5 4B on your machine.
Run
lms load hf-unsloth--qwen3-5-4b-gguf && lms server startYes, Mac Studio M2 Ultra 128GB can run Qwen3.5 4B with a C grade (Runs well). Expected decode speed: 56.0 tok/s.
Qwen3.5 4B (4B parameters) requires approximately 17.6 GB of memory with Q4_K_M quantization.
The recommended quantization for Qwen3.5 4B is Q4_K_M, which balances quality and memory efficiency.
On Mac Studio M2 Ultra 128GB, Qwen3.5 4B achieves approximately 56.0 tokens per second decode speed with a time-to-first-token of 3457ms using Q4_K_M quantization.
For coding workloads, Qwen3.5 4B on Mac Studio M2 Ultra 128GB receives a C grade with 56.0 tok/s and 2.6M context.
On Mac Studio M2 Ultra 128GB, Qwen3.5 4B can safely use up to 2.6M 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-unsloth--qwen3-5-4b-gguf-on-m2-ultra-128gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview:
2.2 GB |
| Medium |
| D39 |
Q4_K_M | 4 | 2.4 GB | Medium | D39 |
Q5_K_M | 5 | 2.9 GB | High | D39 |
Q6_K | 6 | 3.3 GB | High | D39 |
Q8_0 | 8 | 4.3 GB | Very High | D40 |
F16Best for your GPU | 16 | 8.2 GB | Maximum | D40 |
Not always. Mac Studio M2 Ultra 128GB 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.