{"id":19747984,"url":"https://github.com/tensorchord/inference-benchmark","last_synced_at":"2025-04-30T08:33:02.734Z","repository":{"id":175216738,"uuid":"652545614","full_name":"tensorchord/inference-benchmark","owner":"tensorchord","description":"Benchmark for machine learning model online serving (LLM, embedding, Stable-Diffusion, Whisper)","archived":false,"fork":false,"pushed_at":"2023-06-28T11:28:22.000Z","size":48,"stargazers_count":23,"open_issues_count":2,"forks_count":3,"subscribers_count":6,"default_branch":"main","last_synced_at":"2024-02-25T12:34:19.449Z","etag":null,"topics":["benchmark","inference-server","llm","stable-diffusion","whisper"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/tensorchord.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null}},"created_at":"2023-06-12T09:39:42.000Z","updated_at":"2024-02-25T07:18:22.000Z","dependencies_parsed_at":"2024-01-30T00:10:03.972Z","dependency_job_id":null,"html_url":"https://github.com/tensorchord/inference-benchmark","commit_stats":null,"previous_names":["tensorchord/inference-benchmark"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/tensorchord%2Finference-benchmark","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/tensorchord%2Finference-benchmark/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/tensorchord%2Finference-benchmark/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/tensorchord%2Finference-benchmark/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/tensorchord","download_url":"https://codeload.github.com/tensorchord/inference-benchmark/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":224203383,"owners_count":17272939,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["benchmark","inference-server","llm","stable-diffusion","whisper"],"created_at":"2024-11-12T02:19:42.077Z","updated_at":"2024-11-12T02:19:42.732Z","avatar_url":"https://github.com/tensorchord.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"\u003cdiv align=\"center\"\u003e\n\n# Inference Benchmark\n\nMaximize the potential of your models with the inference benchmark (tool).\n\n\u003c/div\u003e\n\n\u003cp align=center\u003e\n\u003ca href=\"https://discord.gg/KqswhpVgdU\"\u003e\u003cimg alt=\"discord invitation link\" src=\"https://dcbadge.vercel.app/api/server/KqswhpVgdU?style=flat\"\u003e\u003c/a\u003e\n\u003ca href=\"https://twitter.com/TensorChord\"\u003e\u003cimg src=\"https://img.shields.io/twitter/follow/tensorchord?style=social\" alt=\"trackgit-views\" /\u003e\u003c/a\u003e\n\u003c/p\u003e\n\n# What is it\n\nInference benchmark provides a standard way to measure the performance of inference workloads. It is also a tool that allows you to evaluate and optimize the performance of your inference workloads.\n\n# Results\n\n## Bert\n\nWe benchmarked [pytriton (triton-inference-server)](https://github.com/triton-inference-server/pytriton) and [mosec](https://github.com/mosecorg/mosec) with bert. We enabled dynamic batching for both frameworks with max batch size 32 and max wait time 10ms. Please checkout the [result](./benchmark/results/bert.md) for more details.\n\n![DistilBert](./benchmark/results/distilbert_serving_benchmark.png)\n\nMore [results with different models on different serving frameworks](https://github.com/tensorchord/inference-benchmark/issues/7) are coming soon.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftensorchord%2Finference-benchmark","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ftensorchord%2Finference-benchmark","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftensorchord%2Finference-benchmark/lists"}