MD Judge v0 2 internlm2 7b i1 needs ~11.2 GB VRAM. MacBook Pro M3 Max 48GB has 34.6 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
56.2 tok/s
TTFT
3444 ms
Safe context
472K
Memory
11.2 GB / 34.6 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 | 56.2 tok/s | 1879 ms | 472K |
| Coding | C | Runs well | 56.2 tok/s | 3444 ms | 472K |
| Agentic Coding | C | Runs well | 56.2 tok/s | 5010 ms | 472K |
| Reasoning | C | Runs well | 56.2 tok/s | 4071 ms | 472K |
| RAG | C | Runs well | 56.2 tok/s | 6263 ms | 472K |
How MD Judge v0 2 internlm2 7b i1 (7B params) fits at each quantization level on MacBook Pro M3 Max 48GB (34.6 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 2.7 GB | Low | C42 |
Q3_K_S | 3 | 3.4 GB | Low | C42 |
NVFP4 | 4 | 3.9 GB | Medium | C42 |
Q4_K_M | 4 | 4.3 GB | Medium | C43 |
Q5_K_M | 5 | 5.0 GB | High | C43 |
Q6_K | 6 | 5.7 GB | High | C43 |
Q8_0 | 8 | 7.5 GB | Very High | C44 |
F16Best for your GPU | 16 | 14.3 GB | Maximum | C47 |
Copy-paste commands to run MD Judge v0 2 internlm2 7b i1 on your machine.
Run
lms load hf-mradermacher--md-judge-v0-2-internlm2-7b-i1-gguf && lms server startOpciones de mejora
Sube la velocidad estimada de decodificación alrededor de un 74%.
Añade margen de memoria para más contexto y para que el modelo envejezca mejor.
~$3,999 MSRP
Sube la velocidad estimada de decodificación alrededor de un 74%.
Añade margen de memoria para más contexto y para que el modelo envejezca mejor.
~$3,999 MSRP
Sube la velocidad estimada de decodificación alrededor de un 56%.
Añade margen de memoria para más contexto y para que el modelo envejezca mejor.
~$3,999 MSRP
Yes, MacBook Pro M3 Max 48GB can run MD Judge v0 2 internlm2 7b i1 with a C grade (Runs well). Expected decode speed: 56.2 tok/s.
MD Judge v0 2 internlm2 7b i1 (7B parameters) requires approximately 11.2 GB of memory with Q4_K_M quantization.
The recommended quantization for MD Judge v0 2 internlm2 7b i1 is Q4_K_M, which balances quality and memory efficiency.
On MacBook Pro M3 Max 48GB, MD Judge v0 2 internlm2 7b i1 achieves approximately 56.2 tokens per second decode speed with a time-to-first-token of 3444ms using Q4_K_M quantization.
For coding workloads, MD Judge v0 2 internlm2 7b i1 on MacBook Pro M3 Max 48GB receives a C grade with 56.2 tok/s and 472K context.
On MacBook Pro M3 Max 48GB, MD Judge v0 2 internlm2 7b i1 can safely use up to 472K tokens of context. The model's official context limit is —, but available memory constrains the safe maximum.
Not always. MacBook Pro M3 Max 48GB 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.
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<iframe src="https://willitrunai.com/embed/hf-mradermacher--md-judge-v0-2-internlm2-7b-i1-gguf-on-m3-max-48gb" 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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