What GPU do I need to run defog/sqlcoder-7b-2?

6.7B parameters, published in F16. View on Hugging Face

6.7B
Parameters
F16
Native precision
LlamaForCausalLM
Architecture
text-generation
Pipeline

sqlcoder-7b-2 is published by defog on Hugging Face, with 14,322 downloads and 441 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.

PrecisionWeight sizeRequired VRAMCheapest live fitGPUs neededEst. $/hr (full fit)
FP1612.6 GB15.1 GBV1001$0.088/hr
FP8 (quantized)6.3 GB7.5 GBRTX 5060 Ti1$0.110/hr
INT4 (quantized)3.1 GB3.8 GBRTX 5060 Ti1$0.110/hr

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 requires a quantized checkpoint actually published for this model, check its Hugging Face page before relying on this row.

Cheapest way to run sqlcoder-7b-2 at its published (F16) precision: 1× V100, at $0.088/hr per GPU ($0.088/hr total). Quantizing to FP8 or INT4 (rows above) can cost less, but requires a compatible quantized checkpoint to exist for this model.

sqlcoder-7b-2: common questions

Does sqlcoder-7b-2 fit on a 16 GB GPU?

Yes. At FP16 it needs 15.1 GB of VRAM, so a 16 GB card holds it with 0.9 GB to spare. A 12 GB card is not enough for it at FP16.

What is the least VRAM sqlcoder-7b-2 can run in?

3.8 GB, at INT4 (quantized), which fits a 6 GB card, against 15.1 GB at FP16. That row assumes an INT4 checkpoint has actually been published for this model, so check its Hugging Face page before planning around it.

Weight-to-VRAM math, the fit rules, and how live prices are normalized: full methodology.

defog models

Related reading: V100 pricing and specs, and The best GPUs for AI, ranked.

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