Home / Can I run it? / gpt-oss-120b / gpt-oss-120b on dual RTX 3090s

No. gpt-oss-120b at Q4_K_M needs about 82.5 GB, and dual RTX 3090s have 48.0 GB usable at a ~4k context.

Can I run gpt-oss-120b on dual RTX 3090s?

gpt-oss-120b at Q4_K_M needs about 82.5 GB, and dual RTX 3090s have 48.0 GB usable. Two cards add memory, not decode speed; the speed estimate uses one RTX 3090’s 936 GB/s. 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

None of Q4, Q8 or FP16 needs 82.5 GB

Memory needed

82.5 GB at Q4_K_M, ~4k context

Usable VRAM

48.0 GB of 48 GB VRAM

Est. tokens/sec

n/a does not fit

gpt-oss-120b · GeForce RTX 3090 · Multi-GPU · Dual 3090 build · Everything this machine runs · Q4 vs Q8 vs FP16

Memory at each quant

Estimated tokens per second

No speed estimate: gpt-oss-120b does not fit in the 48.0 GB this machine can use, so we do not publish a tokens/sec figure for CPU offload.

Context headroom

Even at a short ~4k context, the weights do not fit. Extending context would only increase the gap.

From the model’s config. Try other sizes in the VRAM calculator or see the context length guide.

What to do instead

• Run R1 Distill 32B instead (23.8 GB at Q4). It is a different model, not a drop-in, but it does fit this machine.
• To hold gpt-oss-120b at Q4, you need about 82.5 GB. The MacBook Pro M5 Max 128GB has 96.0 GB usable ($6699 Apple list price, 14-inch M5 Max 18C CPU/40C GPU, 128GB/2TB).
• CPU offload can load the weights anyway, but it is slow. We do not publish an offload tokens/sec figure.
• 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 a Mac mini 64GBWon’t fit
• gpt-oss-120b on a Mac Studio 256GBFits
• gpt-oss-120b on a Mac Studio 512GBFits

Other models on dual RTX 3090s

• Llama 3.3 70B on dual RTX 3090sWon’t fit
• R1 Distill 70B on dual RTX 3090sWon’t fit
• Qwen3-235B on dual RTX 3090sWon’t fit
• DeepSeek-R1 on dual RTX 3090sWon’t fit
• Mixtral 8x22B on dual RTX 3090sWon’t fit
• GLM-4.5-Air on dual RTX 3090sWon’t fit