Text Generation Inference (TGI) hosting

TGI is Hugging Face's inference server, powering their own Inference Endpoints. It offers continuous batching, quantization support, and guided decoding. Choose it when you deploy through Hugging Face infrastructure or want their supported path; elsewhere the ecosystem has largely consolidated on vLLM.

Providers with a ready-made Text Generation Inference (TGI) path

ProviderHow
Hugging Face Inference Endpoints deploy any Hub model on TGI with autoscaling (the native path) Deploy
RunPod Run the ghcr.io/huggingface/text-generation-inference image on any pod Deploy
Vast.ai Run the official TGI Docker image on any instance Deploy

Everywhere else: `docker run --gpus all ghcr.io/huggingface/text-generation-inference --model-id <hf-repo>`.

Which GPU to rent

Same weight-size math as vLLM; TGI's default configs are more conservative on KV cache, so it fits slightly tighter on marginal GPUs.

Live floors refreshed 2026-08-23
Model classGPUVRAMFrom $/hrCheapest at
Up to ~17B (FP8) / ~34B (INT4) RTX 4090 24 GB $0.134marketplace Vast.ai Rent
Up to ~23B (FP8) / ~46B (INT4) RTX 5090 32 GB $0.321marketplace Vast.ai Rent
Up to ~34B (FP8) / ~69B (INT4) L40S 48 GB $0.467marketplace Vast.ai Rent
Up to ~58B (FP8) / ~116B (INT4) H100 SXM 80 GB $1.34marketplace Vast.ai Rent
Up to ~102B (FP8) / ~205B (INT4) H200 141 GB $2.00spot Verda
Up to ~130B (FP8) / ~261B (INT4) — MoE giants go multi-GPU B200 180 GB $3.06spot Verda

Rent vs API: when self-hosting Text Generation Inference (TGI) pays off

Self-hosting wins when utilization is high and steady. A rented GPU bills every hour whether you use it or not, while APIs bill per token. Run your numbers in the breakeven calculator, or check any open model's page (e.g. Llama 3.3 70B) for a side-by-side estimate.

Other stacks