Maintenance status is four dated facts, and the one that predicts everything else is the last commit date - measured across all 100 engine repos with resolvable GitHub metadata
Fields
gotchas/ev-maintenance-status-is-four-dated-factsNotes
The two facts that would change a reader's decision most, and that are absent from most engine records: NVIDIA's FasterTransformer ([[fastertransformer]]) has had NO COMMIT SINCE 2023-10-19 - 35.5 months - while remaining unarchived with 40 contributors, 6457 stars and 288 open issues. It is one of the most-starred engines in this dataset and it has been frozen for nearly three years, and nothing in a reader's impression of 'NVIDIA's Fast Transformer' would tell them that. Second: [[fastertransformer]] and [[clip-as-service]] are the two records with no commit for over 30 months, and [[niche-torchserve]] is archived while carrying 443 open issues - the residue of an abandoned-but-popular project. METHOD AND LIMITS, stated plainly: contributor counts come from the Link-header last page of contributors?per_page=1&anon=1, which counts distinct committers INCLUDING anonymous ones, so for projects with meaningful anonymous contribution the count is an over-estimate of distinct humans - this affects [[ggml-org/llama.cpp]] (2077), [[whisper-cpp]] (1043) and [[ik-llama-cpp]] (856) most, and those three counts should be read as 'distinct committers including anon', not as team sizes. Last-release data uses releases/latest where a release object exists and falls back to the newest TAG NAME with a null publish date where none does, so a tag-only project has an unverified release date. pushed_at can move on a force-push or a branch deletion, so it is a floor, not a ceiling, on activity. 2 of 102 engine repos returned 404 and were EXCLUDED rather than estimated: [[local-webgpu]] (points at w3c/webgpu, private or renamed) and [[mxptq-research-harness]] (points at microsoft/NeuralCompression, 404).
Cross-references
Affects (27)
- Inference enginesvLLM
- Inference enginesSGLang
- Inference enginesllama.cpp
- Inference enginesOllama
- Inference enginesTensorRT-LLM
- Inference enginesFlashInfer
- Inference enginesNVIDIA Dynamo
- Inference enginesFasterTransformer
- Inference enginesMedusa
- Inference enginesSmoothQuant reference implementation (PyTorch W8A8)
- Inference enginesRouteLLM (LMSYS LLM router)contested
- Inference enginesLoongServe (elastic sequence parallelism for long-context LLM serving)
- Inference enginesSequoia (tree-based speculative decoding) and UMbreLLa successordraft
- Inference enginesSpinQuant research harness (fake-quant + Triton INT4 kernels)
- Inference enginesDistServe (research prototype)
- Inference enginesllm.c
- Inference enginesCLIP-as-service
- Inference enginesTorchServe (PyTorch Serve)
- Inference enginesSynapseAI / SynapseAI Core (Habana's Gaudi compiler and runtime)
- Inference enginesGroqFlow and the GroqWare Suite (Groq's compile-and-run tool flow)draft
- Inference enginesAirLLMdraft
- Inference enginesHabana Gaudi PyTorch Bridge and the Gaudi torch fork (torch-hpu)
- Inference enginesSemi-PD (research prototype)
- Inference enginesCerebras CSL SDK and fabric simulator (Cerebras' own software stack)draft
- Inference enginesText Generation Inference
- Inference enginesWebGPU (in-browser inference)
- Inference enginesMicroscaling PTQ research harness