What GPU do I need to run typhoon-ai/llama3.1-typhoon2-8b-instruct?
8.0B parameters, published in BF16. View on Hugging Face
llama3.1-typhoon2-8b-instruct is published by typhoon-ai on Hugging Face, with 72,466 downloads and 14 likes to date. It's a LlamaForCausalLM model built for text-generation, published natively in BF16.
VRAM required & cheapest live GPU fit
Required VRAM = weight size at each precision, plus a fixed overhead for KV-cache, activations, and fragmentation. Full formula and assumptions: methodology.
A GPU is only matched to a row if its hardware supports that precision, and the primary recommendation is always a single-GPU fit when one exists.
INT4 caveat: requires a quantized checkpoint actually published for this model, check its Hugging Face page before relying on this row.
Cheapest way to run llama3.1-typhoon2-8b-instruct at its published (BF16) precision: 1× RTX 3090 on simplepod, at $0.160/hr per GPU ($0.160/hr total). Quantizing to FP8 or INT4 (rows above) can cost less, but requires a compatible quantized checkpoint to exist for this model.
Weight-to-VRAM math, the fit rules, and how live prices are normalized: full methodology.
More typhoon-ai models
- typhoon-ocr-3b (3.8B, BF16)
- typhoon2.5-qwen3-4b (4.0B, BF16)
- typhoon-ocr1.5-2b (2.1B, BF16)
- llama-3-typhoon-v1.5-8b-instruct (8.0B, BF16)
- typhoon2.5-qwen3-30b-a3b (30.5B, BF16)
- Qwen3-0.6B (752M, BF16)
