Question 1

What AI models can run on RTX A6000?

Accepted Answer

The RTX A6000 (48 GB VRAM) can run models including Llama-2-7b, Llama-2-7b-chat, NV-Llama2-13B-RLHF-RM, MediPhi-MedWiki, intent-aware-lfqa-qwen3-4b-baseline and more — 10 compatible models indexed so far. Compatible models are determined by whether the model's memory footprint fits within the GPU's 48 GB VRAM, potentially using quantization (Q8, Q6, or Q4) to reduce memory usage.

Question 2

What is the cheapest cloud option for RTX A6000?

Accepted Answer

The cheapest on-demand option for the RTX A6000 is Lambda at $1.09/hr (gpu_1x_a6000). We track pricing across 17 providers to help you find the best deal.

Question 3

Is RTX A6000 good for fine-tuning?

Accepted Answer

Yes, the RTX A6000 is well-suited for fine-tuning. With 48 GB of VRAM, it can handle LoRA/QLoRA fine-tuning of models up to ~30B parameters and full fine-tuning of smaller models (up to ~7B parameters). For larger models, consider multi-GPU setups.

Question 4

How much VRAM does RTX A6000 have?

Accepted Answer

The RTX A6000 has 48 GB of VRAM (GDDR6). It also offers 768 GB/s memory bandwidth, 77.4 TFLOPS of FP16 compute.

Question 5

What quantization formats work on RTX A6000?

Accepted Answer

The RTX A6000 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 ~163B parameters (by VRAM estimate) fit on the RTX A6000.

RTX A6000

Specifications

Cloud pricing

Compatible models

Compare this GPU

Frequently asked questions

VRAM	48 GB
Memory type	GDDR6
Bandwidth	768 GB/s
FP16 TFLOPS	77.4
FP8 support	No