What GPU do I need to run allenai/wildguard?
7.2B parameters, published in BF16. View on Hugging FaceGated
wildguard is published by allenai on Hugging Face, with 148,651 downloads and 57 likes to date. It's a MistralForCausalLM model built for text-generation, published natively in BF16, and gated — you'll need to accept the model's terms on Hugging Face before downloading weights.
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 wildguard 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 allenai models
- OLMo-2-0425-1B (1.5B, F32)
- Olmo-3-7B-Instruct (7.3B, BF16)
- OLMoE-1B-7B-0125-Instruct (6.9B, BF16)
- OLMoE-1B-7B-0924 (6.9B, BF16)
- Olmo-3-1025-7B (7.3B, BF16)
- Olmo-3-7B-Instruct-SFT (7.3B, BF16)
