Looking for something like Traceloop OpenLLMetry? Here are 24 alternatives, ranked by how closely they match it on purpose, features and platforms. Of these, 1 are free or have a free plan and 22 are open source.
OpenLLMetry provides OpenTelemetry-based observability for generative AI and large language model applications.
| # | Alternative | Pricing | Open source | Platforms |
|---|---|---|---|---|
| 1 | Adaptive Reliability Layer | — | Not stated | — |
| 2 | Eurybia | — | Yes | — |
| 3 | Deepchecks | — | Yes | — |
| 4 | NannyML | — | Yes | — |
| 5 | Evidently | — | Yes | — |
| 6 | Edge Impulse | — | Not stated | Web |
| 7 | GPTCache | — | Yes | — |
| 8 | OneComp | — | Yes | — |
| 9 | microsoft/LMOps | — | Yes | — |
| 10 | hpcaitech/ColossalAI | — | Yes | — |
Adaptive Reliability Layer decides when to retrain a model based on drift signals and delayed labels.
Eurybia tracks model drift and validates data during machine learning model deployment.
Deepchecks tests and validates machine learning models and data, covering workflows from research through production.
NannyML provides Python tools for post-deployment data science and monitoring model performance under data drift.
Evidently evaluates, tests, and monitors machine learning systems and data pipelines.
Edge Impulse provides MLOps workflows for developing, deploying, and monitoring edge and physical AI models.
GPTCache provides semantic caching for large language models and integrates with LangChain and LlamaIndex.
OneCompression is a Python package for compressing large language models.
This repository describes technologies for enabling AI capabilities with large and multimodal language models.
ColossalAI provides tools intended to make large AI models cheaper, faster, and more accessible.
Extensible Toolkit for Finetuning and Inference of Large Foundation Models.
PaddlePaddle provides a deep learning framework for training models across devices and platforms.
Mosec serves machine learning models with dynamic batching and CPU or GPU pipelines for inference workloads.
ClearML combines experiment and data management, pipelines, scheduling, orchestration, and model serving for AI workloads.
DyNet provides tools for building dynamic neural networks and deep learning models.
ClearML manages AI experiments, data, pipelines, orchestration, scheduling, and model serving in one MLOps platform.
BentoML helps build and serve AI apps and models through inference APIs, job queues, and multi-model pipelines.
GPT-NeoX implements model parallel autoregressive transformers on GPUs using Megatron and DeepSpeed libraries.
MII makes low-latency and high-throughput inference possible, powered by DeepSpeed.
The colibri-core NLP tool and library works with n-grams, skipgrams, and other linguistic patterns.
Gymnasium provides a standard API for single agent reinforcement learning environments and related utilities.
Butterfree provides tools for building feature stores and transforming raw data.
Chunk Tuner benchmarks document chunking strategies for RAG and recommends a configuration through a CLI, Python library, or MCP server.
PromptSite provides prompt version management for tracking, experimentation, and debugging LLM prompts.
Alternatives are suggested from the purpose and features described in our listings. Different pages for the same product appear once. Read each description to check whether it fits your task. How we choose alternatives · Suggest an alternative
