Can I run Tev1-4B-experimental on an RTX 5070?

Yes, just

Its published weights (9.32 GB) fit in the 10.8 GB an RTX 5070 can use, with room for ≈ 43K tokens of context.

Full analysis of Tev1-4B-experimental Everything that runs on RTX 5070 Get the weights on Hugging Face

hf download togethercomputer/Tev1-4B-experimental

Files and context on RTX 5070

Each file of Tev1-4B-experimental (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 RTX 5070	Context (16-bit)	Context (8-bit)
As published	9.32 GB	Tight	43K	85K
4-bit (estimate)	2.62 GB	Fits	242K	256K

Tev1-4B-experimental on other hardware

NVIDIA H100Yes
RTX 5090Yes
RTX 4090Yes
RTX 3090Yes
RTX 5060 Ti 16 GBYes
RTX 5070Yes, just
RTX 3060 12 GBYes, just
RTX 4060Probably, at 4-bit
Mac with 32 GBYes
Mac with 64 GBYes
Mac with 128 GBYes

Popular models that run on RTX 5070

Qwen3-0.6BQwen · 752M
gpt2openai-community · 137M
Qwen3-Coder-30B-A3B-Instruct-GGUFunsloth · 30.5B
Qwen2.5-0.5B-InstructQwen · 494M
Qwen2.5-1.5B-InstructQwen · 1.54B
Qwen3-4BQwen · 4.02B
Qwen3.5-4BQwen · 4.66B
Ornith-1.5-9B-GGUFornith-ai · 9.20B

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.