What GPU do I need to run mlabonne/NeuralMonarch-7B?
7.2B parameters, published in F16. View on Hugging Face
NeuralMonarch-7B is published by mlabonne on Hugging Face, with 25,122 downloads and 12 likes to date. It's a MistralForCausalLM 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 NeuralMonarch-7B 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 mlabonne models
- Qwen3-30B-A3B-abliterated (30.5B, F32)
- NeuralDaredevil-8B-abliterated (8.0B, F16)
- Meta-Llama-3.1-8B-Instruct-abliterated (8.0B, BF16)
- Qwen3-0.6B (752M, BF16)
- gpt2 (137M, F32)
- Qwen3-8B (8.2B, BF16)
