What GPU do I need to run InternScience/Agents-A1-4B?

4.5B parameters, published in BF16. View on Hugging Face

4.5B
Parameters
BF16
Native precision
Qwen3_5ForConditionalGeneration
Architecture
text-generation
Pipeline

Agents-A1-4B is published by InternScience on Hugging Face, with 250,687 downloads and 82 likes to date. It's a Qwen3_5ForConditionalGeneration model built for text-generation, published natively in BF16.

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.

Precision
Weight size
Required VRAM
Cheapest live fit
GPUs needed
Est. $/hr (full fit)
BF16
8.5 GB
10.1 GB
RTX 3060 (simplepod)
1
$0.070/hr
FP8 (quantized)
4.2 GB
5.1 GB
RTX 4070 Super (simplepod)
1
$0.090/hr
INT4 (quantized)
2.1 GB
2.5 GB
RTX 3070 (simplepod)
1
$0.050/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 caveat: requires a quantized checkpoint actually published for this model — check its Hugging Face page before relying on this row.

Cheapest way to run Agents-A1-4B at its published (BF16) precision: 1× RTX 3060 on simplepod, at $0.070/hr per GPU ($0.070/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.

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