L40S on RunPod
for LLM Fine-Tuning

Is the L40S on RunPod good for LLM Fine-Tuning?

Excellent fit. AIMC's fit score combines VRAM headroom, GPU class match, and FP16 compute against the workload's requirements — independent of pricing.

• Datacenter class is well-suited for LLM Fine-Tuning
• 48 GB VRAM provides ample headroom (3.0x the minimum)
• 366 FP16 TFLOPS substantially exceeds the 80 TFLOPS threshold

What this costs on RunPod

Listing-weighted median across 12 observed L40S listings at RunPod. The same GPU is tracked at 14 marketplaces total.

Same L40S at other marketplaces

Top 5 alternative providers for the same GPU, sorted by price ascending.

Other RunPod GPUs for LLM Fine-Tuning

Alternative high-fit options at the same provider, sorted by fit score.

About LLM Fine-Tuning

Adapting pre-trained large language models to specific domains via LoRA, QLoRA, or full fine-tuning. LLM Fine-Tuning requires at least 16 GB VRAM and benefits from Datacenter or Workstation-class compute.