Llama 3 8B Instruct 32k v0.1 needs ~11.9 GB VRAM. MacBook Pro M4 Pro 48GB has 34.6 GB. With Q4_K_M quantization, expect ~40 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
39.6 tok/s
TTFT
4885 ms
Safe context
403K
Memory
11.9 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 | 39.6 tok/s | 2665 ms | 403K |
| Coding | C | Runs well | 39.6 tok/s | 4885 ms | 403K |
| Agentic Coding | C | Runs well | 39.6 tok/s | 7106 ms | 403K |
| Reasoning | C | Runs well | 39.6 tok/s | 5773 ms | 403K |
| RAG | C | Runs well | 39.6 tok/s | 8882 ms | 403K |
How Llama 3 8B Instruct 32k v0.1 (8B params) fits at each quantization level on MacBook Pro M4 Pro 48GB (34.6 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 3.1 GB | Low | C43 |
Q3_K_S | 3 | 3.9 GB | Low | C43 |
NVFP4 | 4 | 4.5 GB | Medium | C43 |
Q4_K_M | 4 | 4.9 GB | Medium | C43 |
Q5_K_M | 5 | 5.8 GB | High | C44 |
Q6_K | 6 | 6.6 GB | High | C44 |
Q8_0 | 8 | 8.6 GB | Very High | C45 |
F16Best for your GPU | 16 | 16.4 GB | Maximum | C48 |
Copy-paste commands to run Llama 3 8B Instruct 32k v0.1 on your machine.
Run
lms load hf-maziyarpanahi--llama-3-8b-instruct-32k-v0-1-gguf && lms server startOpciones de mejora
Sube la velocidad estimada de decodificación alrededor de un 94%.
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 140%.
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 128%.
Añade margen de memoria para más contexto y para que el modelo envejezca mejor.
~$3,999 MSRP
Yes, MacBook Pro M4 Pro 48GB can run Llama 3 8B Instruct 32k v0.1 with a C grade (Runs well). Expected decode speed: 39.6 tok/s.
Llama 3 8B Instruct 32k v0.1 (8B parameters) requires approximately 11.9 GB of memory with Q4_K_M quantization.
The recommended quantization for Llama 3 8B Instruct 32k v0.1 is Q4_K_M, which balances quality and memory efficiency.
On MacBook Pro M4 Pro 48GB, Llama 3 8B Instruct 32k v0.1 achieves approximately 39.6 tokens per second decode speed with a time-to-first-token of 4885ms using Q4_K_M quantization.
For coding workloads, Llama 3 8B Instruct 32k v0.1 on MacBook Pro M4 Pro 48GB receives a C grade with 39.6 tok/s and 403K context.
On MacBook Pro M4 Pro 48GB, Llama 3 8B Instruct 32k v0.1 can safely use up to 403K tokens of context. The model's official context limit is —, but available memory constrains the safe maximum.
Not always. MacBook Pro M4 Pro 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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