openchat 3.6 8b 20240522 IMat needs ~13.6 GB VRAM. Mac mini M4 64GB has 46.1 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
Runs well
Decode
16.3 tok/s
TTFT
11886 ms
Safe context
570K
Memory
13.6 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 | 17.7 tok/s | 5964 ms | 570K |
| Coding | C | Runs well | 17.7 tok/s | 10935 ms | 570K |
| Agentic Coding | C | Runs well | 17.7 tok/s | 15905 ms | 570K |
| Reasoning | C | Runs well | 17.7 tok/s | 12923 ms | 570K |
| RAG | C | Runs well | 17.7 tok/s | 19881 ms | 570K |
How openchat 3.6 8b 20240522 IMat (8B params) fits at each quantization level on Mac mini M4 64GB (46.1 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 3.1 GB | Low | C41 |
Q3_K_S | 3 | 3.9 GB | Low | C41 |
NVFP4 | 4 |
Copy-paste commands to run openchat 3.6 8b 20240522 IMat on your machine.
Run
lms load hf-legraphista--openchat-3-6-8b-20240522-imat-gguf && lms server startUpgrade options
Raises estimated decode speed by about 371%.
Adds memory headroom for longer context windows and future model growth.
~$2,499 MSRP
Raises estimated decode speed by about 202%.
Adds memory headroom for longer context windows and future model growth.
~$2,499 MSRP
Raises estimated decode speed by about 587%.
Adds memory headroom for longer context windows and future model growth.
~$3,999 MSRP
Yes, Mac mini M4 64GB can run openchat 3.6 8b 20240522 IMat with a C grade (Runs well). Expected decode speed: 17.7 tok/s.
openchat 3.6 8b 20240522 IMat (8B parameters) requires approximately 13.6 GB of memory with Q4_K_M quantization.
The recommended quantization for openchat 3.6 8b 20240522 IMat is Q4_K_M, which balances quality and memory efficiency.
On Mac mini M4 64GB, openchat 3.6 8b 20240522 IMat achieves approximately 17.7 tokens per second decode speed with a time-to-first-token of 10935ms using Q4_K_M quantization.
For coding workloads, openchat 3.6 8b 20240522 IMat on Mac mini M4 64GB receives a C grade with 17.7 tok/s and 570K context.
On Mac mini M4 64GB, openchat 3.6 8b 20240522 IMat can safely use up to 570K 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-legraphista--openchat-3-6-8b-20240522-imat-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:
4.5 GB |
| Medium |
| C42 |
Q4_K_M | 4 | 4.9 GB | Medium | C42 |
Q5_K_M | 5 | 5.8 GB | High | C42 |
Q6_K | 6 | 6.6 GB | High | C42 |
Q8_0 | 8 | 8.6 GB | Very High | C42 |
F16Best for your GPU | 16 | 16.4 GB | Maximum | C45 |
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.