Can I run DeepSeek-R1-Distill-Llama-70B (Q4_K_M (4-bit Medium)) on Apple M4 Max (128GB)?
Estimated 12.80 tokens per second (usable) on Apple M4 Max (128GB). Fit quality: comfortable with 75GB headroom for context.
The Math
| Model Size (Q4_K_M (4-bit Medium)) | 42.6 GB |
|---|---|
| KV Cache (default context) | ~6.4 GB (15% of model size) |
| Total Required | 0 GB |
| Hardware Memory | 128 GB total |
| Reserved (OS/driver) | ~128 GB |
| Usable Memory | 0 GB |
| Memory Bandwidth | 546 GB/s |
| Estimated Speed | 12.80 tok/s (bandwidth ÷ active model size = 546 ÷ 42.6) |
What to Expect
Speed: At 12.80 tok/s, this is usable for interactive use. Good enough for chat — responses arrive at roughly reading speed or slightly faster.
Context headroom: 75GB remaining after loading the model. Comfortable fit with room to spare for longer conversations and larger prompts.
Estimated only — no community benchmarks yet for this combo. Submit yours →
Specifications
DeepSeek-R1-Distill-Llama-70B
| Parameters | 70.55B |
|---|---|
| Family | DeepSeek |
| Quantization | Q4_K_M (4-bit Medium) (42.6GB) |
| Source | HuggingFace → |
| License | MIT |
Apple M4 Max (128GB)
| Type | Apple unified |
|---|---|
| Memory | 128 GB |
| Bandwidth | 546 GB/s |
| Released | 2024 |
| MSRP | $3,499 |
| Source | Spec page → |
Quick Questions
What quantization should I use for Apple M4 Max (128GB)?
With 128GB, you have plenty of room. Q4_K_M is the community default and offers the best quality-size tradeoff. Q6_K or Q8_0 are worth considering if you prioritize quality and the model still fits.
How much VRAM does DeepSeek-R1-Distill-Llama-70B need?
DeepSeek-R1-Distill-Llama-70B has 70.55B parameters. At Q4_K_M (4-bit Medium), it requires approximately 42.6GB of storage plus ~6.4GB for KV cache at default context, for a total of roughly 0GB.
Is 12.80 tok/s fast enough for real-time chat?
At 12.80 tok/s, responses arrive at roughly reading speed. It's usable for chat, though streaming helps the perceived responsiveness. Not instant, but not frustrating either.
Explore Further
Other Hardware for DeepSeek-R1-Distill-Llama-70B
| Hardware | Fits? | Est. tok/s |
|---|---|---|
| NVIDIA H100 SXM 80GB | ✓ | 78.70 tok/s |
| NVIDIA A100 SXM 80GB | ✓ | 47.00 tok/s |
| Apple M3 Ultra (512GB) | ✓ | 19.20 tok/s |
| Apple M3 Ultra (192GB) | ✓ | 19.20 tok/s |
| Apple M3 Ultra (96GB) | ✓ | 19.20 tok/s |
Other Models for Apple M4 Max (128GB)
| Model | Fits? | Est. tok/s |
|---|---|---|
| Qwen 2.5 0.5B (IQ2_XXS (iMatrix 2-bit XXS)) | ✓ | 3900.00 tok/s |
| Qwen3 0.6B (IQ2_XXS (iMatrix 2-bit XXS)) | ✓ | 3211.80 tok/s |
| Qwen 2.5 0.5B (Q2_K (2-bit)) | ✓ | 2600.00 tok/s |
| Qwen 2.5 0.5B (Q3_K_M (3-bit Medium)) | ✓ | 2275.00 tok/s |
| Qwen3 0.6B (Q2_K (2-bit)) | ✓ | 2184.00 tok/s |