Llama 3.1 models

42 Llama 3.1 models on Hugging Face, from 950M to 405.9B parameters. At the precision each one is published in, the smallest needs about 2.1 GB of VRAM (Llama-3.1-8B-Instruct-speculator.eagle3, cheapest live fit: RTX 5060 Ti) and the largest about 907 GB (Llama-3.1-405B). The cheapest way to run Llama-3.1-8B-Instruct-speculator.eagle3 is $0.110/hr.

Llama 3.1 models

ModelParametersPublished asVRAM neededLive GPU fitEst. $/hr
Llama-3.1-8B-Instruct-speculator.eagle3950MBF162.1 GBRTX 5060 Ti$0.110/hr
LLaMA3.1-8B-Instruct-DFlash-UltraChat1.0BBF162.3 GBRTX 5060 Ti$0.110/hr
KONI-Llama3.1-8B-Instruct-202410248.0BBF1617.9 GBRTX A5000$0.176/hr
Llama-3.1-8B8.0BBF1617.9 GBRTX A5000$0.176/hr
Llama-3.1-8B-Instruct8.0BBF1617.9 GBRTX A5000$0.176/hr
Meta-Llama-3.1-8B-Instruct-abliterated8.0BBF1617.9 GBRTX A5000$0.176/hr
Meta-Llama-3.1-8B8.0BBF1617.9 GBRTX A5000$0.176/hr
Meta-Llama-3.1-8B-Instruct8.0BBF1617.9 GBRTX A5000$0.176/hr
Llama-3.1-8B-Instruct-FP88.0BF8_E4M39.0 GBRTX 5060 Ti$0.110/hr
Llama-3.1-Nemotron-Nano-8B-v18.0BBF1617.9 GBRTX A5000$0.176/hr
Llama-3.1-Nemotron-Safety-Guard-8B-v38.0BBF1617.9 GBRTX A5000$0.176/hr
Llama-3.1-8B-Lexi-Uncensored-V28.0BBF1617.9 GBRTX A5000$0.176/hr
llama3_1_relevance_dev8.0BF1617.9 GBRTX A5000$0.176/hr
Meta-Llama-3.1-8B-Instruct-FP88.0BF8_E4M39.0 GBRTX 5060 Ti$0.110/hr
Llama3.1-8B-PRM-Deepseek-Data8.0BBF1617.9 GBRTX A5000$0.176/hr
Dobby-Mini-Unhinged-Llama-3.1-8B8.0BBF1617.9 GBRTX A5000$0.176/hr
Llama-3.1-Swallow-8B-Instruct-v0.58.0BBF1617.9 GBRTX A5000$0.176/hr
Llama-3.1-8B-Instruct8.0BBF1617.9 GBRTX A5000$0.176/hr
Meta-Llama-3.1-8B8.0BBF1617.9 GBRTX A5000$0.176/hr
Meta-Llama-3.1-8B-Instruct8.0BBF1617.9 GBRTX A5000$0.176/hr
Meta-Llama-3.1-8B-FP88.0BF8_E4M39.0 GBRTX 5060 Ti$0.110/hr
Llama-3.1-Tulu-3-8B-DPO8.0BBF1617.9 GBRTX A5000$0.176/hr
Llama-3.1-Tulu-3-8B-SFT8.0BBF1617.9 GBRTX A5000$0.176/hr
Foundation-Sec-1.1-8B-Instruct8.0BBF1617.9 GBRTX A5000$0.176/hr
Foundation-Sec-8B-Reasoning8.0BBF1617.9 GBRTX A5000$0.176/hr
Foundation-Sec-8B-Instruct8.0BBF1618.0 GBRTX A5000$0.176/hr
Meta-Llama-3.1-8B-Instruct-FP8-dynamic8.0BF8_E4M39.0 GBRTX 5060 Ti$0.110/hr
Llama-3.1-Nemotron-Nano-VL-8B-V18.7BBF1619.5 GBRTX A5000$0.176/hr
Llama-3.1-70B-LatamGPT-SFT-1.070.6BBF16158 GBRTX A5000 × 7$1.23/hr
Llama-3.1-70B70.6BBF16158 GBRTX A5000 × 7$1.23/hr
Llama-3.1-70B-Instruct70.6BBF16158 GBRTX A5000 × 7$1.23/hr
Meta-Llama-3.1-70B-Instruct70.6BBF16158 GBRTX A5000 × 7$1.23/hr
Llama-3.1-70B-Instruct-FP870.6BF8_E4M378.8 GBRTX PRO 6000$1.38/hr
Llama-3.1-Nemotron-70B-Instruct-HF70.6BBF16158 GBRTX A5000 × 7$1.23/hr
Llama-3.3-70B-Instruct70.6BBF16158 GBRTX A5000 × 7$1.23/hr
Meta-Llama-3.1-70B70.6BBF16158 GBRTX A5000 × 7$1.23/hr
Meta-Llama-3.1-70B-Instruct70.6BBF16158 GBRTX A5000 × 7$1.23/hr
Meta-Llama-3.1-70B-Instruct-FP870.6BF8_E4M378.8 GBRTX PRO 6000$1.38/hr
Llama-3.3-70B-Instruct-FP8-dynamic70.6BF8_E4M378.9 GBRTX PRO 6000$1.38/hr
Llama-3.1-405B405.9BBF16907 GBNo live fit–
Llama-3.1-405B-Instruct405.9BBF16907 GBNo live fit–
Llama-3.1-405B-FP8405.9BF8_E4M3454 GBRTX PRO 6000 × 5$6.88/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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