Model Anatomy See what's inside open-weight AI models

Can I run Qwen3.5-0.8B-weight-space-programming on an RTX 6000 Ada?

Yes

Its published weights (1.75 GB) fit in the 43.2 GB an RTX 6000 Ada can use, with room for ≈ 256K tokens of context.

Full analysis of Qwen3.5-0.8B-weight-space-programming Everything that runs on RTX 6000 Ada Get the weights on Hugging Face
hf download RikiyaT/Qwen3.5-0.8B-weight-space-programming

Files and context on RTX 6000 Ada

Each file of Qwen3.5-0.8B-weight-space-programming (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.

FileSizeOn RTX 6000 Ada Context (16-bit)Context (8-bit)
As published1.75 GBFits256K256K
4-bit (estimate)491 MBFits256K256K

Qwen3.5-0.8B-weight-space-programming on other hardware

Popular models that run on RTX 6000 Ada

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.