MODEL · GPU GUIDE

Keye-VL-2.0-30B-A3B GPU Requirements: VRAM & Cheapest GPU

Keye-VL-2.0-30B-A3B has about 31.1B parameters. See exactly how much GPU memory it needs at FP16, INT8, and INT4, and the cheapest GPU to run it, with live hourly pricing from 5+ data center partners.

31.1BParameters
17 GBMin VRAM
$0.65/hrCheapest
< 2 minDeploy
Kwai-Keye/Keye-VL-2.0-30B-A3B
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31.1B paramsimage-text-to-textKeyeVL21.7K downloads107 likesupdated May 29, 2026

To run Keye-VL-2.0-30B-A3B for inference at FP16, you need roughly 68 GB of VRAM. The cheapest fit on Spheron is A100 80GB at about $0.82/hr. Quantize to INT4 to run it on a smaller, cheaper GPU.

GB VRAM REQUIRED
FP16INFERENCEBATCH 1CTX 4k

Estimated peak VRAM including weights, activations, and KV cache. Add 10% headroom for production traffic.

RANKCONFIGURATIONPER GPUTOTAL $/HR
  • 01
    1× A100 80GBCHEAPEST
    Ampere · HBM2e
    $0.82/hr$0.82/hr
  • 02
    1× RTX PRO 6000 96GB
    Blackwell · GDDR7
    $1.32/hr$1.32/hr
  • 03
    1× GH200 96GB
    Grace Hopper · HBM3
    $1.88/hr$1.88/hr
  • 04
    2× L40S 48GB
    Ada Lovelace · GDDR6
    $0.96/hr$1.92/hr
  • 05
    1× H100 80GB
    Hopper · HBM3
    $2.01/hr$2.01/hr

Live pricing aggregated from 5+ data center partners. Per-minute billing, no commitments.

VRAM required to run Keye-VL-2.0-30B-A3B

Estimated peak VRAM at context length 4,096 and batch size 1, including weights, activations, and KV cache. Quantizing to INT8 (Q8) or INT4 (Q4) cuts memory roughly in half and in quarter.

PrecisionInferenceLoRA fine-tuneFull fine-tune
FP1668 GB102 GB271 GB
INT834 GB51 GB136 GB
INT417 GB25 GB68 GB

Cheapest GPU to run Keye-VL-2.0-30B-A3B by precision

FP16
VRAM required68GB

Full precision. Best quality, highest memory.

Cheapest GPU
A100 80GB
Ampere · HBM2e
$0.82/hr
A100 80GB on Spheron
INT8
VRAM required34GB

8-bit quantized. ~2x smaller, minimal quality loss.

Cheapest GPU
A100 80GB
Ampere · HBM2e
$0.82/hr
A100 80GB on Spheron
INT4
VRAM required17GB

4-bit quantized. ~4x smaller, runs on smaller GPUs.

Cheapest GPU
RTX 4090 24GB
Ada Lovelace · GDDR6X
$0.65/hr
RTX 4090 24GB on Spheron

Inference vs fine-tuning Keye-VL-2.0-30B-A3B

InferenceWeights + KV cache
LoRA fine-tune~1.5×+ low-rank adapter
Full fine-tune~4×+ gradients + optimizer state

Inference only holds the model weights plus a KV cache, so it is the cheapest setup. LoRA fine-tuning adds a small adapter and roughly 50% more memory. Full fine-tuning holds gradients and optimizer state on top of the weights, which is about 4x the inference footprint, so it often needs multiple GPUs even when inference fits on one. For Keye-VL-2.0-30B-A3B, an on-demand A100 80GB instance covers inference and LoRA, while a full fine-tune needs several times that memory and often spans multiple GPUs. Check the live GPU pricing for current rates.

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Keye-VL-2.0-30B-A3B GPU questions