What GPU do I need to run allenai/olmOCR-2-7B-1025-FP8?
8.3B parameters, published in F8_E4M3. View on Hugging Face
olmOCR-2-7B-1025-FP8 is published by allenai on Hugging Face, with 260,025 downloads and 254 likes to date. It's a Qwen2_5_VLForConditionalGeneration model built for image-text-to-text, published natively in F8_E4M3.
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 olmOCR-2-7B-1025-FP8 at its published (F8_E4M3) precision: 1× RTX 4070 on simplepod, at $0.080/hr per GPU ($0.080/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)
- olmOCR-2-7B-1025 (8.3B, BF16)
- OLMoE-1B-7B-0924 (6.9B, BF16)
- wildguard (7.2B, BF16)
