{"data":{"node":{"slug":"nvidia-tensorrt-llm","name":"TensorRT-LLM","tagline":"Python API for defining and optimizing Large Language Models (LLMs) on NVIDIA GPUs","github_url":"https://github.com/NVIDIA/TensorRT-LLM","owner":"NVIDIA","repo":"TensorRT-LLM","owner_avatar_url":"https://avatars.githubusercontent.com/u/1728152?v=4","primary_language":"Python","stars":14317,"forks":2641,"topics":["blackwell","cuda","llm-serving","moe","pytorch"],"archived":false,"github_pushed_at":"2026-08-07T05:40:26+00:00","maintenance_label":"Very active","url":"https://www.graphcanon.com/tools/nvidia-tensorrt-llm","markdown_url":"https://www.graphcanon.com/tools/nvidia-tensorrt-llm.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/nvidia-tensorrt-llm","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=nvidia-tensorrt-llm"},"categories":[{"slug":"inference-serving","name":"Inference & Serving","url":"https://www.graphcanon.com/categories/inference-serving","markdown_url":"https://www.graphcanon.com/categories/inference-serving.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/inference-serving"},{"slug":"llm-frameworks","name":"LLM Frameworks","url":"https://www.graphcanon.com/categories/llm-frameworks","markdown_url":"https://www.graphcanon.com/categories/llm-frameworks.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/llm-frameworks"}],"tags":[{"slug":"blackwell","name":"blackwell"},{"slug":"cuda","name":"cuda"},{"slug":"llm-serving","name":"llm-serving"},{"slug":"moe","name":"moe"},{"slug":"pytorch","name":"pytorch"}],"edges":[],"neighbours":[{"slug":"ggml-org-llama-cpp","name":"llama.cpp","tagline":"LLM inference in C/C++","github_url":"https://github.com/ggml-org/llama.cpp","owner":"ggml-org","repo":"llama.cpp","owner_avatar_url":"https://avatars.githubusercontent.com/u/134263123?v=4","primary_language":"C++","stars":122941,"forks":21406,"topics":["ggml"],"archived":false,"github_pushed_at":"2026-08-07T05:28:54+00:00","maintenance_label":"Active","url":"https://www.graphcanon.com/tools/ggml-org-llama-cpp","markdown_url":"https://www.graphcanon.com/tools/ggml-org-llama-cpp.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/ggml-org-llama-cpp","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=ggml-org-llama-cpp","shared_categories":["inference-serving"]},{"slug":"vllm-project-vllm","name":"vllm","tagline":"A high-throughput and memory-efficient inference and serving engine for LLMs","github_url":"https://github.com/vllm-project/vllm","owner":"vllm-project","repo":"vllm","owner_avatar_url":"https://avatars.githubusercontent.com/u/136984999?v=4","primary_language":"Python","stars":87847,"forks":20135,"topics":["amd","blackwell","cuda","deepseek","deepseek-v3","gpt","gpt-oss","inference","kimi","llama","llm","llm-serving","model-serving","moe","openai","pytorch","qwen","qwen3","tpu","transformer"],"archived":false,"github_pushed_at":"2026-08-01T11:55:36+00:00","maintenance_label":"Active","url":"https://www.graphcanon.com/tools/vllm-project-vllm","markdown_url":"https://www.graphcanon.com/tools/vllm-project-vllm.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/vllm-project-vllm","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=vllm-project-vllm","shared_categories":["inference-serving"]},{"slug":"lyogavin-airllm","name":"airllm","tagline":"AirLLM 70B inference with single 4GB GPU","github_url":"https://github.com/lyogavin/airllm","owner":"lyogavin","repo":"airllm","owner_avatar_url":"https://avatars.githubusercontent.com/u/1113905?v=4","primary_language":"Jupyter Notebook","stars":24183,"forks":2722,"topics":["chinese-llm","chinese-nlp","finetune","generative-ai","instruct-gpt","instruction-set","llama","llm","lora","open-models","open-source","open-source-models","qlora"],"archived":false,"github_pushed_at":"2026-07-23T08:29:43+00:00","maintenance_label":"Steady","url":"https://www.graphcanon.com/tools/lyogavin-airllm","markdown_url":"https://www.graphcanon.com/tools/lyogavin-airllm.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/lyogavin-airllm","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=lyogavin-airllm","shared_categories":["inference-serving"]},{"slug":"nvidia-megatron-lm","name":"Megatron-LM","tagline":"Ongoing research training transformer models at scale","github_url":"https://github.com/NVIDIA/Megatron-LM","owner":"NVIDIA","repo":"Megatron-LM","owner_avatar_url":"https://avatars.githubusercontent.com/u/1728152?v=4","primary_language":"Python","stars":17341,"forks":4333,"topics":["large-language-models","model-para","transformers"],"archived":false,"github_pushed_at":"2026-08-06T23:12:52+00:00","maintenance_label":"Active","url":"https://www.graphcanon.com/tools/nvidia-megatron-lm","markdown_url":"https://www.graphcanon.com/tools/nvidia-megatron-lm.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/nvidia-megatron-lm","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=nvidia-megatron-lm","shared_categories":[]},{"slug":"lightning-ai-litgpt","name":"litgpt","tagline":"High-performance LLMs with recipes for pretraining, finetuning and deployment","github_url":"https://github.com/Lightning-AI/litgpt","owner":"Lightning-AI","repo":"litgpt","owner_avatar_url":"https://avatars.githubusercontent.com/u/58386951?v=4","primary_language":"Python","stars":13605,"forks":1483,"topics":["ai","artificial-intelligence","deep-learning","large-language-models","llm","llm-inference","llms"],"archived":false,"github_pushed_at":"2026-07-20T10:24:12+00:00","maintenance_label":"Steady","url":"https://www.graphcanon.com/tools/lightning-ai-litgpt","markdown_url":"https://www.graphcanon.com/tools/lightning-ai-litgpt.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/lightning-ai-litgpt","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=lightning-ai-litgpt","shared_categories":["llm-frameworks","inference-serving"]},{"slug":"kalyanks-nlp-llm-engineer-toolkit","name":"llm-engineer-toolkit","tagline":"A curated list of over 120 LLM libraries categorized.","github_url":"https://github.com/KalyanKS-NLP/llm-engineer-toolkit","owner":"KalyanKS-NLP","repo":"llm-engineer-toolkit","owner_avatar_url":"https://avatars.githubusercontent.com/u/202506543?v=4","primary_language":null,"stars":10767,"forks":1682,"topics":["ai-engineer","generative-ai","large-language-models","llm-engineer","llms"],"archived":false,"github_pushed_at":"2026-08-16T13:05:43+00:00","maintenance_label":"Active","url":"https://www.graphcanon.com/tools/kalyanks-nlp-llm-engineer-toolkit","markdown_url":"https://www.graphcanon.com/tools/kalyanks-nlp-llm-engineer-toolkit.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/kalyanks-nlp-llm-engineer-toolkit","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=kalyanks-nlp-llm-engineer-toolkit","shared_categories":["inference-serving"]},{"slug":"fminference-flexllmgen","name":"FlexLLMGen","tagline":"Running large language models on a single GPU for throughput-oriented scenarios.","github_url":"https://github.com/FMInference/FlexLLMGen","owner":"FMInference","repo":"FlexLLMGen","owner_avatar_url":"https://avatars.githubusercontent.com/u/125944572?v=4","primary_language":"Python","stars":9361,"forks":590,"topics":["deep-learning","gpt-3","high-throughput","large-language-models","machine-learning","offloading","opt"],"archived":true,"github_pushed_at":"2024-10-28T03:05:41+00:00","maintenance_label":"Archived","url":"https://www.graphcanon.com/tools/fminference-flexllmgen","markdown_url":"https://www.graphcanon.com/tools/fminference-flexllmgen.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/fminference-flexllmgen","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=fminference-flexllmgen","shared_categories":["inference-serving"]},{"slug":"ericlbuehler-mistral-rs","name":"mistral.rs","tagline":"Fast flexible LLM inference","github_url":"https://github.com/EricLBuehler/mistral.rs","owner":"EricLBuehler","repo":"mistral.rs","owner_avatar_url":"https://avatars.githubusercontent.com/u/65165915?v=4","primary_language":"Rust","stars":7575,"forks":671,"topics":["llm","rust","uqff"],"archived":false,"github_pushed_at":"2026-07-29T20:21:17+00:00","maintenance_label":"Active","url":"https://www.graphcanon.com/tools/ericlbuehler-mistral-rs","markdown_url":"https://www.graphcanon.com/tools/ericlbuehler-mistral-rs.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/ericlbuehler-mistral-rs","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=ericlbuehler-mistral-rs","shared_categories":["inference-serving"]},{"slug":"linkedin-liger-kernel","name":"Liger-Kernel","tagline":"Efficient Triton Kernels for LLM Training","github_url":"https://github.com/linkedin/Liger-Kernel","owner":"linkedin","repo":"Liger-Kernel","owner_avatar_url":"https://avatars.githubusercontent.com/u/357098?v=4","primary_language":"Python","stars":6555,"forks":573,"topics":["finetuning","gemma2","hacktoberfest","llama","llama3","llm-training","llms","mistral","phi3","triton","triton-kernels"],"archived":false,"github_pushed_at":"2026-08-07T08:48:09+00:00","maintenance_label":"Active","url":"https://www.graphcanon.com/tools/linkedin-liger-kernel","markdown_url":"https://www.graphcanon.com/tools/linkedin-liger-kernel.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/linkedin-liger-kernel","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=linkedin-liger-kernel","shared_categories":[]},{"slug":"algorithmicsuperintelligence-optillm","name":"optillm","tagline":"Optimizing inference proxy for LLMs","github_url":"https://github.com/algorithmicsuperintelligence/optillm","owner":"algorithmicsuperintelligence","repo":"optillm","owner_avatar_url":"https://avatars.githubusercontent.com/u/238764598?v=4","primary_language":"Python","stars":4244,"forks":385,"topics":["agent","agentic-ai","agentic-framework","agentic-workflow","agents","api-gateway","chain-of-thought","genai","large-language-models","llm","llm-inference","llmapi","mixture-of-experts","moa","monte-carlo-tree-search","openai","openai-api","optimization","prompt-engineering","proxy-server"],"archived":false,"github_pushed_at":"2026-07-18T12:56:27+00:00","maintenance_label":"Steady","url":"https://www.graphcanon.com/tools/algorithmicsuperintelligence-optillm","markdown_url":"https://www.graphcanon.com/tools/algorithmicsuperintelligence-optillm.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/algorithmicsuperintelligence-optillm","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=algorithmicsuperintelligence-optillm","shared_categories":["inference-serving"]},{"slug":"turboderp-exllama","name":"exllama","tagline":"Memory-efficient rewrite of HF transformers for Llama with quantized weights","github_url":"https://github.com/turboderp/exllama","owner":"turboderp","repo":"exllama","owner_avatar_url":"https://avatars.githubusercontent.com/u/11859846?v=4","primary_language":"Python","stars":2937,"forks":220,"topics":[],"archived":false,"github_pushed_at":"2023-09-30T19:06:04+00:00","maintenance_label":"Dormant","url":"https://www.graphcanon.com/tools/turboderp-exllama","markdown_url":"https://www.graphcanon.com/tools/turboderp-exllama.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/turboderp-exllama","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=turboderp-exllama","shared_categories":["llm-frameworks","inference-serving"]},{"slug":"vllm-project-vllm-ascend","name":"vllm-ascend","tagline":"Community maintained hardware plugin for vLLM on Ascend","github_url":"https://github.com/vllm-project/vllm-ascend","owner":"vllm-project","repo":"vllm-ascend","owner_avatar_url":"https://avatars.githubusercontent.com/u/136984999?v=4","primary_language":"C++","stars":2674,"forks":2081,"topics":["ascend","inference","llm","llm-serving","llmops","mlops","model-serving","transformer","vllm"],"archived":false,"github_pushed_at":"2026-08-20T12:01:45+00:00","maintenance_label":"Very active","url":"https://www.graphcanon.com/tools/vllm-project-vllm-ascend","markdown_url":"https://www.graphcanon.com/tools/vllm-project-vllm-ascend.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/vllm-project-vllm-ascend","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=vllm-project-vllm-ascend","shared_categories":["inference-serving"]}]}}