Langfuse vs LiteLLM
Side-by-side comparison of features, pricing, and ratings
Langfuse or LiteLLM: which should you choose?
| Dimension | Langfuse | LiteLLM |
|---|---|---|
| Pricing | Free · from $29/mo | Free plan · paid plans on request |
| Best for | AI engineering teams tracing multi-turn chat, coding, or workflow agents in production, Enterprises needing self-hosting, FIPS 140-3 mode, or a US/EU/JP data region for SOC 2, ISO 27001, or HIPAA requirements | Platform teams standardizing the whole org on one key for 140+ models, MCP servers, and agents, FinOps-minded teams enforcing per-tag budgets across prod, staging, and eval |
| Standout features | Hierarchical tracing of LLM calls, tool invocations, retrieval, and other API calls · Session tracking for multi-turn chat and agentic workflows · Agent graphs that visualize complex agentic workflows | One OpenAI-compatible API across 140+ providers and 1,800+ models · Day-zero support for new models: Grok 4.7 (2026-09-21), Qwen3.8-Omni-Flash (2026-09-18) · Multimodal input: text, image, audio, and video via Qwen3.8-Omni-Flash |
| Viability score | 89/100 | 81/100 |
| API | Yes | Yes |
Langfuse is the stronger pick for ai engineering teams tracing multi-turn chat, coding, or workflow agents in production; LiteLLM fits better for platform teams standardizing the whole org on one key for 140+ models, mcp servers, and agents.
Built from live tool data, last verified 2026-11-08.
Open-source LLM observability and agent evals: trace, evaluate, and improve AI agents on one MIT-licensed platform
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LiteLLM is a self-hosted AI gateway that puts 140+ providers and 1,800+ models behind one OpenAI-compatible API.
Visit WebsiteWhat do real users say about Langfuse vs LiteLLM?
Not marketing copy and not our opinion — a structured sweep of public discussion (reviews, forums, communities and video comments), showing what people praise and what they complain about for each tool.
Langfuse
73 mentions across 6 sources · 76% positive (weighted across 6 sources)
Hacker News, YouTube, Product Hunt, Stack Overflow, GitHub, Lemmy
What users praise
- • Open-source and MIT-licensed, avoiding vendor lock-in with self-hosting.
- • Hierarchical traces give great depth for debugging LangChain and LangGraph.
- • Recent v4 boasts up to 165x faster real-time processing with ClickHouse.
- • LLM-as-a-judge and human annotation queues are easy to set up.
What frustrates them
- • Learning curve for beginners; UI/UX less intuitive than some alternatives.
- • Initial setup can be complex, especially for self-hosting.
- • Documentation sometimes too high-level; concrete examples missing.
- • Native SDKs don't cover all languages, requiring extra components.
Researched Sep 9, 2026
LiteLLM
53 mentions across 5 sources · 48% positive — mixed (weighted across 5 sources)
Hacker News, Product Hunt, Stack Overflow, GitHub, Lemmy
What users praise
- • One OpenAI-compatible API across 140+ providers and 1,800+ models cuts integration work dramatically
- • Free self-hosted tier includes virtual keys, teams, spend tracking, budget caps and rate limits
- • Day-0 support for new models like Grok 4.7 and Qwen3.8-Omni-Flash is a genuine differentiator
- • Community clearly runs it in real production — VPS hobbyists, enterprises, and platforms embedding it
What frustrates them
- • Repeated high-severity CVEs including an actively exploited pre-auth SQLi raise real deployment risk
- • Security incident coverage touched thousands of orgs — trust damage lingers even where attribution shifted
- • Large footprint (700MB, 100k+ LOC) pushed users to build a de-bloated fork just to escape it
- • 5,408 open GitHub issues signals a backlog that can outpace triage on security-sensitive bugs
Researched Oct 10, 2026
Frequently Asked Questions
Which is better, Langfuse or LiteLLM?
The best choice between Langfuse and LiteLLM depends on your specific use case — we compare them independently on features, current pricing, integrations, and real-world signals (with an on-demand sentiment scan available for each). See the side-by-side breakdown above to match them to your needs.
What are the main differences between Langfuse and LiteLLM?
The key differences include pricing model, feature set, platform support, and skill level requirements. Review the full comparison on RightAIChoice for a detailed breakdown.
Is there a free version of Langfuse or LiteLLM?
Check the pricing section in the comparison for the latest pricing details on both tools, including free tiers, trial options, and paid plans.
What else are Langfuse and LiteLLM compared with?
If you need deep agent debugging with autonomous failure clustering and fix suggestions, LangSmith is the edge. If you want open-source flexibility, self-hosting, and unified prompt management plus ob
If you’re building complex, multi-step agents and need deep observability and evaluation, LangChain is your pick. If you’re a platform team unifying access to many models with strict cost and access c
Where can you read more about Langfuse and LiteLLM?
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Analysis generated by our model pipeline from live data: