What GPU do I need to run upstage/SOLAR-10.7B-Instruct-v1.0?
10.7B parameters, published in F16. View on Hugging Face
SOLAR-10.7B-Instruct-v1.0 is published by upstage on Hugging Face, with 32,492 downloads and 658 likes to date. It's a LlamaForCausalLM model built for text-generation, published natively in F16.
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 SOLAR-10.7B-Instruct-v1.0 at its published (F16) precision: 1× P40 on akash, at $0.137/hr per GPU ($0.137/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 upstage models
- Solar-Open2-250B (250.3B, BF16)
- Solar-Open-100B (102.7B, BF16)
- SOLAR-10.7B-v1.0 (10.7B, F16)
- solar-pro-preview-instruct (22.1B, BF16)
- Qwen3-0.6B (752M, BF16)
- gpt2 (137M, F32)
