gpt-oss models
6 gpt-oss models on Hugging Face, from 350M to 116.8B parameters. At the precision each one is published in, the smallest needs about 0.8 GB of VRAM (EAGLE3-gpt-oss-20b, cheapest live fit: RTX 5060 Ti) and the largest about 80.0 GB (gpt-oss-120b, cheapest live fit: A100). The cheapest way to run EAGLE3-gpt-oss-20b is $0.110/hr.
gpt-oss models
| Model | Parameters | Published as | VRAM needed | Live GPU fit | Est. $/hr |
|---|---|---|---|---|---|
| EAGLE3-gpt-oss-20b | 350M | BF16 | 0.8 GB | RTX 5060 Ti | $0.110/hr |
| gpt-oss-120b-Eagle3-short-context | 787M | BF16 | 1.8 GB | RTX 5060 Ti | $0.110/hr |
| Huihui-gpt-oss-20b-BF16-abliterated | 20.9B | BF16 | 46.7 GB | RTX A6000 | $0.363/hr |
| gpt-oss-20b | 20.9B | MXFP4 | 16.0 GB | RTX 5060 Ti | $0.110/hr |
| gpt-oss-20b-BF16 | 20.9B | BF16 | 46.7 GB | RTX A6000 | $0.363/hr |
| gpt-oss-120b | 116.8B | MXFP4 | 80.0 GB | A100 | $1.31/hr |
VRAM is for the precision the model is published in, with the same overhead and an 8,192-token context assumed on every page; see the methodology. The fit shown is the lowest-priced single GPU type that holds the model at that precision, or the lowest-priced multi-GPU set (up to 8) when none does.
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