HomeCan I run it?Llama 3.3 70BLlama 3.3 70B on a Mac Studio 256GB
Yes. Llama 3.3 70B at FP16 needs about 163.3 GB, and the Mac Studio M5 Ultra 256GB has 192.0 GB usable at a ~4k context.
Can I run Llama 3.3 70B on a Mac Studio 256GB?
Llama 3.3 70B at FP16 needs about 163.3 GB, and the Mac Studio M5 Ultra 256GB has 192.0 GB usable. That figure is 256 GB of unified memory on the spec sheet, of which 192.0 GB is usable for weights and cache, at 1200 GB/s memory bandwidth. Meta’s flagship 70B instruct model, the usual target for a high-end local chat box. These are estimates from our formula, not measured benchmarks.
- Quant that fits
- FP16 Fits with headroom
- Memory needed
- 163.3 GB at FP16, ~4k context
- Usable unified memory
- 192.0 GB of 256 GB unified memory
- Est. tokens/sec
- 4–7 estimate
Memory at each quant
| Quant | Need vs 192.0 GB | Verdict |
|---|---|---|
| Q4_K_M | 50.2 GB | Q4Fits |
| Q8_0 | 87.2 GB | Q8Fits |
| FP16 | 163.3 GB | FP16Fits |
Estimated tokens per second
Estimate: 4–7 tokens/sec at FP16. This is a bandwidth-derived range, not a bench. Efficiency is a 45–80% unified-memory band from How we calculate.
Context headroom
At FP16, this machine has headroom out to about 64k tokens under our KV estimate. Longer chats need more memory for the cache. Figures assume an FP16 KV cache.
| Context | KV cache (FP16) | Total at FP16 | Verdict |
|---|---|---|---|
| 4k | 1.3 GB | 163.3 GB | Fits |
| 8k | 2.7 GB | 164.6 GB | Fits |
| 16k | 5.4 GB | 167.3 GB | Fits |
| 32k | 10.7 GB | 172.7 GB | Fits |
| 64k | 21.5 GB | 183.4 GB | Tight |
| 128k | 42.9 GB | 204.9 GB | Won’t fit |
What to do instead
- See the best GPU for this model family and the Llama-3.3-70B-Instruct model page.
Other hardware for Llama 3.3 70B
- Llama 3.3 70B on an RTX 3060 12GBWon’t fit
- Llama 3.3 70B on an RTX 3070 TiWon’t fit
- Llama 3.3 70B on an RTX 3080Won’t fit
- Llama 3.3 70B on an RTX 3090Won’t fit
- Llama 3.3 70B on an RTX 4060 Ti 16GBWon’t fit
- Llama 3.3 70B on an RTX 4070 Ti SuperWon’t fit
Other models on a Mac Studio 256GB
- R1 Distill 70B on a Mac Studio 256GBFits
- gpt-oss-120b on a Mac Studio 256GBFits
- Qwen3-235B on a Mac Studio 256GBFits
- DeepSeek-R1 on a Mac Studio 256GBWon’t fit
- DeepSeek-V3.2 on a Mac Studio 256GBWon’t fit
- Mixtral 8x22B on a Mac Studio 256GBTight
Quick answers
- Can I run Llama 3.3 70B on a Mac Studio 256GB?
- Yes. Llama 3.3 70B at FP16 needs about 163.3 GB, and the Mac Studio M5 Ultra 256GB has 192.0 GB usable.
- How much VRAM does Llama 3.3 70B need?
- About 50.2 GB at Q4_K_M, 87.2 GB at Q8_0 and 163.3 GB at FP16, estimated for a ~4k context.
- How fast is Llama 3.3 70B on a Mac Studio 256GB?
- Our estimate is 4–7 tokens per second at FP16. It is not a measured benchmark.
- What context length can I use?
- At FP16, our KV estimate supports up to about 64k tokens before the cache pushes the total over usable memory.