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Langfuse is an open-source LLM engineering platform that helps teams collaboratively debug, analyze, and iterate on their LLM applications.
Which is more popular?
Based on our record, Langfuse should be more popular than Optimage. It has been mentioned 32 times since March 2021.
Website, pricing, platforms and company facts side by side.
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|---|---|---|
| Website | optimage.app | langfuse.com |
| Pricing | — | |
| Company | — | Startup from the United States |
| Listed in |
In their own words, as submitted to SaaSHub.


No description of Optimage yet.
Langfuse is an open-source LLM engineering platform designed to empower developers by providing insights into user interactions with their LLM applications. We offer tools that help developers understand usage patterns, diagnose issues, and improve application performance based on real user data....
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Langfuse in two minutes
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Ten free AI prompt tools in 2026 across four categories: prompt generators (SurePrompts, Anthropic Console, OpenAI Playground), libraries (AIPRM, PromptHero, FlowGPT, Awesome ChatGPT Prompts), open-source workflow...
Recommendations tracked on public social media and blogs since March 2021.


I use the one https://optimage.app/. Source: about 3 years ago
Optimage is a batch image compression/resize app that I use to standardise images sent to me by clients for their website. Source: almost 4 years ago
I’ve found Optimage to work better, at least for me. Source: about 4 years ago
Langfuse is the other serious option in this category if you also want observability, evals and traces bundled with prompt management. Different scope, more setup, worth comparing honestly. - Source: dev.to / 20 days ago
Langfuse with Microsoft.Extensions.AI has an appealing story: update prompts without redeploying. A prompt fetches its config blob—model, tokens, temperature—which the code passes straight to the LLM. - Source: dev.to / 24 days ago
Langfuse is not a replacement for OpenTelemetry; it is a specialization layer built on top of it. Langfuse was engineered specifically for the unique telemetry needs of LLM applications. It acts as the semantic layer that OTel lacks. - Source: dev.to / 29 days ago
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