TTFT benchmark: LLM Gateway vs. OpenRouter (Claude-haiku-4.5, 150 runs)

Description and use

**Project Summary:**
The TTFT benchmark compares the LLM Gateway and OpenRouter, two AI/ML tools, to help developers add AI capabilities to their projects without starting from scratch. This project, specifically Claude-haiku-4.5 with 150 runs, enables prototyping AI features, building RAG or agent workflows, and evaluating model tooling. However, its production readiness is medium due to sparse integration signals and limited quality signals.

**Value Proposition:**
This project adds value to developers by providing a pre-built AI model stack that can be leveraged for various use cases, such as prototype AI features, building RAG or agent workflows, and evaluating model tooling. By using this project, developers can focus on integrating the AI capabilities into their existing workflows rather than building the AI model from scratch.

**Practical Adoption Path:**
To adopt this project, developers should first manually inspect the integration signals and verify the license, maintenance, documentation, issues, and release cadence. This will help ensure that the project meets their specific needs and is suitable for production use. Once the project is deemed suitable, developers can integrate it into their workflows and begin building AI-powered applications.

**Production Readiness:**
The production readiness of this project is medium, indicating that it is suitable

Use in a workflow

TTFT benchmark: LLM Gateway vs. OpenRouter (Claude-haiku-4.5, 150 runs) helps add AI capability without starting from a blank model stack.

• prototype AI features
• build RAG or agent workflows
• evaluate model tooling

Limitations and review notes

Medium: useful for prototypes or internal workflows, with dependency and maintenance checks before production.