HomeCan I run it?gpt-oss-120bgpt-oss-120b on a Mac Studio 512GB
Yes. gpt-oss-120b at FP16 needs about 269.7 GB, and the Mac Studio M5 Ultra 512GB has 384.0 GB usable at a ~4k context.
Can I run gpt-oss-120b on a Mac Studio 512GB?
gpt-oss-120b at FP16 needs about 269.7 GB, and the Mac Studio M5 Ultra 512GB has 384.0 GB usable. That figure is 512 GB of unified memory on the spec sheet, of which 384.0 GB is usable for weights and cache, at 1200 GB/s memory bandwidth. OpenAI’s open 120B-class gpt-oss model. It needs large unified memory at Q4, with a much smaller active set per token. These are estimates from our formula, not measured benchmarks.
- Quant that fits
- FP16 Fits with headroom
- Memory needed
- 269.7 GB at FP16, ~4k context
- Usable unified memory
- 384.0 GB of 512 GB unified memory
- Est. tokens/sec
- up to 94 estimate
Memory at each quant
| Quant | Need vs 384.0 GB | Verdict |
|---|---|---|
| Q4_K_M | 82.5 GB | Q4Fits |
| Q8_0 | 143.8 GB | Q8Fits |
| FP16 | 269.7 GB | FP16Fits |
Estimated tokens per second
Estimate: up to 94 tokens/sec at FP16 (upper bound: this is a Mixture-of-Experts, and only the active weights are counted). 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 128k 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 | 0.2 GB | 269.7 GB | Fits |
| 8k | 0.3 GB | 269.9 GB | Fits |
| 16k | 0.6 GB | 270.2 GB | Fits |
| 32k | 1.2 GB | 270.8 GB | Fits |
| 64k | 2.4 GB | 272.0 GB | Fits |
| 128k | 4.8 GB | 274.4 GB | Fits |
What to do instead
- See the best GPU for this model family and the gpt-oss-120b model page.
Other hardware for gpt-oss-120b
- gpt-oss-120b on an RTX 4090Won’t fit
- gpt-oss-120b on an RTX 5090Won’t fit
- gpt-oss-120b on an RTX 3090Won’t fit
- gpt-oss-120b on dual RTX 3090sWon’t fit
- gpt-oss-120b on a Mac mini 64GBWon’t fit
- gpt-oss-120b on a Mac Studio 256GBFits
Other models on a Mac Studio 512GB
- Llama 3.3 70B on a Mac Studio 512GBFits
- Qwen3-235B on a Mac Studio 512GBFits
- DeepSeek-R1 on a Mac Studio 512GBWon’t fit
- DeepSeek-V3.2 on a Mac Studio 512GBWon’t fit
Quick answers
- Can I run gpt-oss-120b on a Mac Studio 512GB?
- Yes. gpt-oss-120b at FP16 needs about 269.7 GB, and the Mac Studio M5 Ultra 512GB has 384.0 GB usable.
- How much VRAM does gpt-oss-120b need?
- About 82.5 GB at Q4_K_M, 143.8 GB at Q8_0 and 269.7 GB at FP16, estimated for a ~4k context.
- How fast is gpt-oss-120b on a Mac Studio 512GB?
- Our estimate is up to 94 tokens per second at FP16, as an upper bound for this MoE. It is not a measured benchmark.
- What context length can I use?
- At FP16, our KV estimate supports up to about 128k tokens before the cache pushes the total over usable memory.