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How much VRAM does gpt-oss 120B need?

gpt-oss 120B needs 59.0 GB for its weights as released (MXFP4), 60.2 GB with an 8K context and 61.1 GB with 32K.

Parameters
117B
Active per token
5.1B
Longest context
128K
Released
Aug 2025
License
Apache 2.0
Strongest at
Chat, Coding

Memory at each precision

Memory gpt-oss 120B needs at each precision and context length
PrecisionWeightsWith 8KWith 32KWith 128K
As released (MXFP4)59.0 GB60.2 GB61.1 GB64.5 GB
3-bit53.2 GB54.4 GB55.2 GB58.6 GB
2-bit40.8 GB42.0 GB42.9 GB46.2 GB
1.6-bit22.4 GB23.6 GB24.5 GB27.9 GB

One conversation, 16-bit context cache, runtime overhead included.

What runs it

The best way gpt-oss 120B runs on common GPUs, Macs and AI boxes
MachineBest fitContextSpeedFirst reply
RTX 3060 12 GBToo big
RTX 4060 Ti 16 GBToo big
RTX 3090Too big
RTX 4090Too big
RTX 5090Too big
2× RTX 30902-bit88K197 tok/s0.5 s
RTX PRO 6000 BlackwellMXFP4128K197 tok/s0.2 s
M4 Max 128 GBMXFP4128K65 tok/s4.6 s
M5 Max 128 GBMXFP4128K71 tok/s1.3 s
Ryzen AI Max+ 395 128 GBMXFP4128K37 tok/s2.7 s
DGX Spark 128 GBMXFP4128K47 tok/s1.3 s
M3 Ultra 256 GBMXFP4128K84 tok/s2.6 s
M5 Ultra 512 GBMXFP4128K103 tok/s0.8 s
H100 SXMMXFP4128K269 tok/s0.2 s
DGX Station GB300MXFP4128K346 tok/s0.1 s
8× H200 NVLMXFP4128K308 tok/s0.1 s

Best fit is the highest quality, up to 8-bit, that leaves 16K of context. First reply is the wait for a 2K prompt. Speeds are rough, plus or minus 25%.

How to run it

Ollama
ollama run gpt-oss:120b
llama.cpp
llama-server -hf unsloth/gpt-oss-120b-GGUF
vLLM
vllm serve openai/gpt-oss-120b
MLX (Mac)
mlx_lm.chat --model mlx-community/gpt-oss-120b-MXFP4-Q4

Questions

How much VRAM does gpt-oss 120B need?

gpt-oss 120B needs 59.0 GB for its weights as released (MXFP4), 60.2 GB with an 8K context and 61.1 GB with 32K.

Can gpt-oss 120B run on an RTX 4090?

Not on one card. The smallest machine here that runs it is the 2× RTX 3090.

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