Question 1

What AI models can run on A10?

Accepted Answer

The A10 (24 GB VRAM) can run models including recurrentgemma-9b, MediPhi-Instruct, Llama-2-7b-chat, Llama-3.2-1B-Instruct-QLORA_INT4_EO8, Llama-3.2-1B-Instruct-SpinQuant_INT4_EO8 and more — 10 compatible models indexed so far. Compatible models are determined by whether the model's memory footprint fits within the GPU's 24 GB VRAM, potentially using quantization (Q8, Q6, or Q4) to reduce memory usage.

Question 2

What is the cheapest cloud option for A10?

Accepted Answer

The cheapest on-demand option for the A10 is Lambda at $1.29/hr (gpu_1x_a10). We track pricing across 31 providers to help you find the best deal.

Question 3

Is A10 good for fine-tuning?

Accepted Answer

The A10 can handle fine-tuning with some constraints. With 24 GB of VRAM, it's suitable for LoRA/QLoRA fine-tuning of models up to ~7B parameters. Full fine-tuning is limited to smaller models (~1-3B parameters). Techniques like gradient checkpointing and mixed precision help maximize what fits.

Question 4

How much VRAM does A10 have?

Accepted Answer

The A10 has 24 GB of VRAM (GDDR6). It also offers 600 GB/s memory bandwidth, 62.5 TFLOPS of FP16 compute.

Question 5

What quantization formats work on A10?

Accepted Answer

The A10 supports the following quantization formats: FP16 (full precision), Q8 (8-bit), Q6 (6-bit), Q4 (4-bit). FP16 works for models up to ~7B parameters. Q4 quantization lets models up to ~81B parameters (by VRAM estimate) fit on the A10.

Provider	On-demand	Spot	Actions
Lambda	$1.290/hr	—	—
Microsoft Azure	$3.200/hr	$0.800/hr	—

A10

Specifications

Cloud pricing

Compatible models

Compare this GPU

Frequently asked questions

VRAM	24 GB
Memory type	GDDR6
Bandwidth	600 GB/s
FP16 TFLOPS	62.5
FP8 support	No

A10