Question 1

What AI models can run on L40?

Accepted Answer

The L40 (48 GB VRAM) can run models including gemma-3-12b-it, gemma-3-4b-it, gemma-3-4b-pt, Llama-4-Scout-17B-16E, gemma-3-12b-pt 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 L40?

Accepted Answer

The cheapest on-demand option for the L40 is RunPod at $0.99/hr (1x_L40_SECURE). Spot/preemptible pricing is available at $0.50/hr. We track pricing across 8 providers to help you find the best deal.

Question 3

Is L40 good for fine-tuning?

Accepted Answer

Yes, the L40 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 L40 have?

Accepted Answer

The L40 has 48 GB of VRAM (GDDR6). It also offers 864 GB/s memory bandwidth, 181.1 TFLOPS of FP16 compute, FP8 support for efficient inference.

Question 5

What quantization formats work on L40?

Accepted Answer

The L40 supports the following quantization formats: FP16 (full precision), FP8, Q8 (8-bit), Q6 (6-bit), Q4 (4-bit). FP16 works for models up to ~7B parameters. FP8 halves memory vs FP16 with minimal quality loss. Q4 quantization lets models up to ~163B parameters (by VRAM estimate) fit on the L40.

L40

Specifications

Cloud pricing

Compatible models

Compare this GPU

Frequently asked questions

VRAM	48 GB
Memory type	GDDR6
Bandwidth	864 GB/s
FP16 TFLOPS	181.1
FP8 support	Yes

L40