Can I run xor on an NVIDIA H100?

Yes, just

Its published weights (70.2 GB) fit in the 72.0 GB an NVIDIA H100 can use, with room for ≈ 82K tokens of context.

Full analysis of xor Everything that runs on NVIDIA H100 Get the weights on Hugging Face

hf download juspay/xor

Files and context on NVIDIA H100

Each file of xor (and of GGUF versions the site has analyzed), and how much context fits next to it, with the context cache in 16-bit or 8-bit.

File	Size	On NVIDIA H100	Context (16-bit)	Context (8-bit)
As published	70.2 GB	Tight	82K	164K
4-bit (estimate)	19.7 GB	Fits	256K	256K

xor on other hardware

NVIDIA H100Yes, just
RTX 5090Probably, at 4-bit
RTX 4090Probably, at 4-bit
RTX 3090Probably, at 4-bit
RTX 5060 Ti 16 GBNo
RTX 3060 12 GBNo
RTX 4060No
Mac with 32 GBProbably, at 4-bit
Mac with 64 GBProbably, at 4-bit
Mac with 128 GBYes

Popular models that run on NVIDIA H100

Qwen3-0.6BQwen · 752M
Qwen3-VL-8B-InstructQwen · 8.77B
gpt2openai-community · 137M
Qwen3-8BQwen · 8.19B
Qwen3-Coder-30B-A3B-Instruct-GGUFunsloth · 30.5B
gemma-4-26B-A4B-itgoogle · 25.8B
Qwen2.5-7B-InstructQwen · 7.62B
Qwen3.5-9BQwen · 9.65B

Assumes 90% of the card's memory is usable and at least 4K tokens of context for one conversation, with the context cache in 16-bit unless noted. Fits leaves at least 20% of that memory for context; Tight leaves less.