internlm3 8b instruct abliterated i1 needs ~10.6 GB VRAM. MacBook Pro M4 Max 36GB has 25.9 GB. With Q4_K_M quantization, expect ~58 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
57.7 tok/s
TTFT
3356 ms
Safe context
277K
Memory
10.6 GB / 25.9 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 | 57.7 tok/s | 1830 ms | 277K |
| Coding | C | Runs well | 57.7 tok/s | 3356 ms | 277K |
| Agentic Coding | C | Runs well | 57.7 tok/s | 4881 ms | 277K |
| Reasoning | C | Runs well | 57.7 tok/s | 3966 ms | 277K |
| RAG | C | Runs well | 57.7 tok/s | 6101 ms | 277K |
How internlm3 8b instruct abliterated i1 (8B params) fits at each quantization level on MacBook Pro M4 Max 36GB (25.9 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 3.1 GB | Low | C44 |
Q3_K_S | 3 | 3.9 GB | Low | C44 |
NVFP4 | 4 | 4.5 GB | Medium | C44 |
Q4_K_M | 4 | 4.9 GB | Medium | C44 |
Q5_K_M | 5 | 5.8 GB | High | C45 |
Q6_K | 6 | 6.6 GB | High | C45 |
Q8_0 | 8 | 8.6 GB | Very High | C46 |
F16Best for your GPU | 16 | 16.4 GB | Maximum | C49 |
Copy-paste commands to run internlm3 8b instruct abliterated i1 on your machine.
Run
lms load hf-mradermacher--internlm3-8b-instruct-abliterated-i1-gguf && lms server startYes, MacBook Pro M4 Max 36GB can run internlm3 8b instruct abliterated i1 with a C grade (Runs well). Expected decode speed: 57.7 tok/s.
internlm3 8b instruct abliterated i1 (8B parameters) requires approximately 10.6 GB of memory with Q4_K_M quantization.
The recommended quantization for internlm3 8b instruct abliterated i1 is Q4_K_M, which balances quality and memory efficiency.
On MacBook Pro M4 Max 36GB, internlm3 8b instruct abliterated i1 achieves approximately 57.7 tokens per second decode speed with a time-to-first-token of 3356ms using Q4_K_M quantization.
For coding workloads, internlm3 8b instruct abliterated i1 on MacBook Pro M4 Max 36GB receives a C grade with 57.7 tok/s and 277K context.
On MacBook Pro M4 Max 36GB, internlm3 8b instruct abliterated i1 can safely use up to 277K tokens of context. The model's official context limit is —, but available memory constrains the safe maximum.
Not always. MacBook Pro M4 Max 36GB 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-mradermacher--internlm3-8b-instruct-abliterated-i1-gguf-on-m4-max-36gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
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