lmms-eval vs langfuse

Common questions

What is the difference between lmms-eval and langfuse?

lmms-eval: One-for-All Multimodal Evaluation Toolkit Across Text, Image, Video, and Audio Tasks. langfuse: Open source agent evals & observability: Trace, evaluate, and improve LLM applications with one open platform.. See the comparison table for live GitHub stats and shared categories.

When should I choose lmms-eval over langfuse?

Choose lmms-eval over langfuse when lmms-eval is primarily Python; langfuse is TypeScript; Both tools focus on evaluating LLMs, but they offer different functionalities and approaches. Langfuse offers a broader platform for AI engineering with observability features, whereas lmms-eval is specialized in multimodal evaluations; Tags unique to lmms-eval: agi, audio-evaluation, benchmark, large-language-models; You need to evaluate LLaVA series models on different datasets with precise control over reproducibility details like torch/cuda versions.

When should I choose langfuse over lmms-eval?

Choose langfuse over lmms-eval when langfuse is primarily TypeScript; lmms-eval is Python; Both tools focus on evaluating LLMs, but they offer different functionalities and approaches. Langfuse offers a broader platform for AI engineering with observability features, whereas lmms-eval is specialized in multimodal evaluations; Tags unique to langfuse: analytics, llm-observability, monitoring, open-source; langfuse ships Docker support for self-hosted deployment; When you need a self-hosted solution for evaluating and monitoring large language model applications, as Langfuse supports local, VM, and Kubernetes environments.

When should I avoid lmms-eval?

Looking for a tool that supports less than Python 3.12, as uv setup mandates this version. Requiring support beyond text, image, video, and audio modalities which lmms-eval specifically covers. Your project doesn't benefit from extensive results tracking in Google Sheets or relies solely on alternative reproducibility mechanisms without external dependencies.

When should I avoid langfuse?

If you are looking for a fully managed service without the need for self-hosting, as Langfuse requires setting up and maintaining the infrastructure yourself. When you need enterprise features that are not covered by the open-source version, as the ee folders are not open-source and may require additional licensing or services.

Is lmms-eval or langfuse more popular on GitHub?

langfuse has more GitHub stars (34,763 vs 4,368). Stars measure visibility, not whether either tool fits your constraints.

Are lmms-eval and langfuse open source?

Yes - both are open-source projects on GitHub (lmms-eval: Other, langfuse: Other).

Where can I find alternatives to lmms-eval or langfuse?

GraphCanon lists graph-backed alternatives at lmms-eval alternatives and langfuse alternatives (lmms-eval markdown twin, langfuse markdown twin), ranked by typed relationship edges rather than popularity votes.

Is there a machine-readable version of this comparison?

Yes. The markdown twin at this comparison mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.

Which is better maintained, lmms-eval or langfuse?

lmms-eval: Active. langfuse: Very active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.

Where are the full trust reports for lmms-eval and langfuse?

GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: lmms-eval trust report; langfuse trust report.