Qwen3.5 9B needs ~14.4 GB VRAM. Mac mini M4 64GB has 46.1 GB. With Q4_K_M quantization, expect ~15 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
14.5 tok/s
TTFT
13371 ms
Safe context
497K
Memory
14.4 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 | 14.5 tok/s | 7293 ms | 497K |
| Coding | C | Runs well | 14.5 tok/s | 13371 ms | 497K |
| Agentic Coding | C | Runs well | 14.5 tok/s | 19449 ms | 497K |
| Reasoning | C | Runs well | 14.5 tok/s | 15803 ms | 497K |
| RAG | C | Runs well | 14.5 tok/s | 24312 ms | 497K |
How Qwen3.5 9B (9B params) fits at each quantization level on Mac mini M4 64GB (46.1 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 3.5 GB | Low | C42 |
Q3_K_S | 3 | 4.4 GB | Low | C42 |
NVFP4 | 4 | 5.0 GB | Medium | C42 |
Q4_K_M | 4 | 5.5 GB | Medium | C42 |
Q5_K_M | 5 | 6.5 GB | High | C42 |
Q6_K | 6 | 7.4 GB | High | C43 |
Q8_0 | 8 | 9.6 GB | Very High | C43 |
F16Best for your GPU | 16 | 18.5 GB | Maximum | C46 |
Copy-paste commands to run Qwen3.5 9B on your machine.
Run
docker run --rm -it ghcr.io/ggerganov/llama.cpp:full \
--hf-repo "lmstudio-community/Qwen3.5-9B-GGUF" \
--hf-file "Qwen3.5-9B-GGUF-Q4_K_M.gguf" \
-c 4096 -ngl 99Opciones de mejora
Sube la velocidad estimada de decodificación alrededor de un 371%.
Añade margen de memoria para más contexto y para que el modelo envejezca mejor.
~$2,499 MSRP
Sube la velocidad estimada de decodificación alrededor de un 201%.
Añade margen de memoria para más contexto y para que el modelo envejezca mejor.
~$2,499 MSRP
Sube la velocidad estimada de decodificación alrededor de un 599%.
Añade margen de memoria para más contexto y para que el modelo envejezca mejor.
~$3,999 MSRP
Yes, Mac mini M4 64GB can run Qwen3.5 9B with a C grade (Runs well). Expected decode speed: 14.5 tok/s.
Qwen3.5 9B (9B parameters) requires approximately 14.4 GB of memory with Q4_K_M quantization.
The recommended quantization for Qwen3.5 9B is Q4_K_M, which balances quality and memory efficiency.
On Mac mini M4 64GB, Qwen3.5 9B achieves approximately 14.5 tokens per second decode speed with a time-to-first-token of 13371ms using Q4_K_M quantization.
For coding workloads, Qwen3.5 9B on Mac mini M4 64GB receives a C grade with 14.5 tok/s and 497K context.
On Mac mini M4 64GB, Qwen3.5 9B can safely use up to 497K tokens of context. The model's official context limit is —, but available memory constrains the safe maximum.
Not always. Mac mini M4 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--qwen3-5-9b-gguf-on-m4-mini-64gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview: