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It is the most common way to self-host open-weight models in production on GPU and accelerator clusters.","https:\u002F\u002Fassets.tekyous.dev\u002Flogos\u002Ftools\u002Fvllm.svg","dark",{"slug":20,"display_name":21,"description":22},"open_source","Open Source","Source code is publicly available and free to use, modify, and distribute. 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It takes open-weight models from Hugging Face, such as Llama, Qwen, DeepSeek, Mistral, Gemma, and gpt-oss, and serves them at high throughput behind an **OpenAI-compatible API**, so applications and agent frameworks built for hosted providers can point at a self-hosted endpoint instead.\n\nIts speed comes from memory and scheduling techniques it popularised. **PagedAttention** manages the KV cache like virtual memory pages, which cuts wasted GPU memory and lets far more requests share a card, and continuous batching adds new requests to running batches instead of waiting for a batch to finish. The re-architected V1 engine adds near-zero-overhead prefix caching, chunked prefill, speculative decoding, structured outputs, multi-LoRA serving, quantization formats such as FP8, AWQ, and GPTQ, and tensor, pipeline, and expert parallelism for models that span many GPUs or nodes.\n\nvLLM runs on NVIDIA and AMD GPUs, Google TPUs, AWS Trainium, and Intel Gaudi, with community plugins for other accelerators. It is installed with pip or run from official Docker images, and on Kubernetes it serves as the engine inside larger stacks such as llm-d and many managed inference platforms. Companies including Amazon, Meta, Stripe, and Roblox run it in production, and several cloud inference providers build on it.\n\nThe project is **Apache-2.0 licensed** and free. 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download the weights and self-host, or call them through dozens of managed API providers.","https:\u002F\u002Fassets.tekyous.dev\u002Flogos\u002Ftools\u002Fmeta-llama.svg",{"slug":20,"display_name":21,"description":22},{"category_id":126,"name":127,"slug":128},19,"LLM","llm",{"subcategory_id":130,"name":131,"slug":132},52,"Open-weight","open-weight",[],[],[],{},"vLLM serves Meta's Llama models from their Hugging Face weights behind an OpenAI-compatible API, the usual route for running Llama at production throughput.",{"relationship_type":94,"relationship_display_name":95,"relationship_description":96,"relationship_display_order":44,"tool":139,"strength":113,"notes":155},{"tool_id":140,"name":141,"slug":142,"tooltip_description":143,"logo_url":144,"logo_bg":18,"pricing_model":145,"learning_curve_score":113,"popularity_score":40,"hosting_assignment_type":26,"hosting_provider_restriction":25,"hosting_target_restriction":25,"hosting_compatible_tool_ids":26,"parent_tool_id":26,"category":149,"subcategory":150,"categories":151,"subcategories":152,"flexibility_score":40,"performance_score":40,"portability_score":40,"is_featured":41,"tags":153,"score_reasonings":154,"published_date":26,"last_updated_date":26},161,"DeepSeek","deepseek","Chinese open-weight LLM family under the MIT license, led by DeepSeek-V4.1-Flash, offering frontier-level results at very low API prices, with full self-hosting through vLLM, SGLang, and Ollama.","https:\u002F\u002Fassets.tekyous.dev\u002Flogos\u002Ftools\u002Fdeepseek.svg",{"slug":146,"display_name":147,"description":148},"freemium","Freemium","A free tier is available; 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Use Ollama for local and small-scale use, vLLM once many users hit the same model.",{"relationship_type":227,"relationship_display_name":228,"relationship_description":229,"relationship_display_order":230,"tool":246,"strength":113,"notes":262},{"tool_id":247,"name":248,"slug":249,"tooltip_description":250,"logo_url":251,"logo_bg":18,"pricing_model":252,"learning_curve_score":44,"popularity_score":23,"hosting_assignment_type":179,"hosting_provider_restriction":25,"hosting_target_restriction":25,"hosting_compatible_tool_ids":26,"parent_tool_id":26,"category":256,"subcategory":257,"categories":258,"subcategories":259,"flexibility_score":113,"performance_score":40,"portability_score":105,"is_featured":41,"tags":260,"score_reasonings":261,"published_date":26,"last_updated_date":26},220,"Groq","groq","Fast LLM inference on Groq's own LPU hardware: unlike aggregators such as OpenRouter, Groq runs the compute itself, with low time-to-first-token and per-token pricing among the lowest of the major providers.","https:\u002F\u002Fassets.tekyous.dev\u002Flogos\u002Ftools\u002Fgroq.svg",{"slug":253,"display_name":254,"description":255},"usage_based","Usage-Based","Pricing scales with consumption: API calls, data volume, compute time, or similar metered units.",{"category_id":28,"name":29,"slug":30},{"subcategory_id":32,"name":33,"slug":34},[],[],[],{},"vLLM lets you serve open-weight models on GPUs you run yourself; Groq serves them as a hosted API on its own LPU hardware. vLLM gives control over models and data, Groq removes the operations work.",{"relationship_type":227,"relationship_display_name":228,"relationship_description":229,"relationship_display_order":230,"tool":264,"strength":113,"notes":277},{"tool_id":265,"name":266,"slug":267,"tooltip_description":268,"logo_url":269,"logo_bg":18,"pricing_model":270,"learning_curve_score":44,"popularity_score":23,"hosting_assignment_type":26,"hosting_provider_restriction":25,"hosting_target_restriction":25,"hosting_compatible_tool_ids":26,"parent_tool_id":26,"category":271,"subcategory":272,"categories":273,"subcategories":274,"flexibility_score":23,"performance_score":23,"portability_score":23,"is_featured":41,"tags":275,"score_reasonings":276,"published_date":26,"last_updated_date":26},299,"LM Studio","lm-studio","Desktop app for downloading and running open-weight language models locally on macOS, Windows, and Linux, with a chat interface and a local OpenAI-compatible API server. 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