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Your Fine-Tuned Models Now Work Inside FastRouter
Add fine-tuned and custom model endpoints to FastRouter. Route them like any standard model — with full observability, cost tracking, and governance.

Latest articles
Explore practical routing guides, API performance notes, and product updates from the Fastrouter team.
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Add fine-tuned and custom model endpoints to FastRouter. Route them like any standard model — with full observability, cost tracking, and governance.

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Cut LLM costs on repeated context with Prompt Caching on FastRouter. Automatic for OpenAI, DeepSeek, and Gemini. One field for Anthropic Claude.

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Cut batch processing costs ~50% by appending :flex to your model ID. No code refactors, no migration — just cheaper inference.



Compare FastRouter and OpenRouter on pricing, routing, evals, governance, and latency. Side-by-side matrix, benchmarks, and a decision guide.



Compare FastRouter and Portkey after the Palo Alto Networks acquisition: features, routing, evals, roadmap risk, and a decision guide.



Helicone is in maintenance mode after Mintlify acquired it. Compare features, plan a migration, and see three paths off Helicone Cloud.



FastRouter is a managed LLM gateway. Langfuse is an OSS observability and evals platform. Different categories. We cover where they overlap, when to pick one, and how to run them together.



FastRouter (managed) vs LiteLLM (open-source proxy): operations, routing, evals, total cost, and a decision guide for production teams.



Compare FastRouter and Requesty on EU data residency, routing, evals, governance, and pricing. Decision guide for global and EU teams.

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FastRouter now supports AI video evaluation with LLM-as-judge scoring. Automate quality checks on Veo, Sora, and Kling — no manual review.

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Managing tool integration across multiple LLM providers leads to scattered auth logic, credential sprawl, and zero visibility. Here's how centralized MCP Gateway architecture solves it.

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A high eval pass rate tells you your test set is easy, not that your system is working. A practitioner argument for adversarial evaluation, done right
