Blog — OpenRouter Blog

ElevenLabs is now on OpenRouter

ElevenLabs is now on OpenRouter with 9 Text to Speech and 2 Speech to Text models. Deliver speech with human-like emotion with Eleven v4, give your agent low-latency replies with v4 Turbo, and turn meetings into notes that show who said what with Scribe v2. Here's which model to pick, and one project built start to finish.

October 7, 2026

How an AI Sales Agent Saved Our Sales Team 600 Hours a Month

Rasp gives OpenRouter's five-person sales team about 600 hours a month back, adds room for two more calls a day per rep, and runs for about $30 a day on Ori.

October 7, 2026

Server-Side Code Execution Tools for AI Agents, Compared

A server-side code execution tool runs the model's commands in the provider's sandbox during your API request, so you don't provision or secure a container. OpenAI, Anthropic, and Google run code for their own models. Our openrouter:shell tool runs commands for any model on the Responses and Messages APIs, and our openrouter:bash tool does the same on the Messages API. This article compares the four on runtime, isolation, persistence, and cost, shows a complete request against our sandbox with the output it returned, and describes the jobs that still need a sandbox platform of your own.

October 5, 2026

Agent Frameworks Compared: Tool-Calling Schema Handling

OpenAI, Anthropic, and Google each use a different request and response shape for the same tool. Agent frameworks handle that difference in different places. Some translate one definition into each provider's format, some are native to a single provider, and some hand the question to a connector underneath. This article compares six frameworks on schema definition, translation, and MCP support, then shows how OpenRouter normalizes tool calling at the API layer so a model swap is a change to one string.

October 2, 2026

LangChain vs CrewAI: Orchestration Compared to OpenRouter-Native Routing

Multi-model orchestration is three layers. Workflow orchestration is planning, state, memory, and delegation, and LangGraph and CrewAI are built for it. Model routing is choosing a model per call and falling back when it fails, and provider routing is choosing which provider serves that model. OpenRouter does the second two. This article separates the layers, shows the same two-step pipeline in direct OpenRouter calls and in LangChain, and describes when to add a framework, when to use our Agent SDK, and how to put OpenRouter underneath LangGraph or CrewAI.

October 2, 2026

Model Router Benchmarks

We now benchmark model routers side by side across six suites. Our Router Index weighs quality, speed, and cost so you can decide if you need a router and pick the best one for your needs.

October 2, 2026

Model Routing for Support Bots: Cheap-First FAQ Handling

Cheap-first routing sends routine support questions to a small, inexpensive model and escalates selected hard or uncertain requests to a stronger one. This guide compares the three application-side routing patterns, separates what your application owns from what OpenRouter's Auto Router and model fallbacks handle, walks through a support flow with a copyable request, and sets out how to measure escalation rate and cost per resolved ticket.

October 2, 2026

Confidence Thresholds for Model Escalation Routing

Confidence-based escalation keeps most requests on a cheap model and sends only the ones it is unsure about to a stronger one. This guide covers forcing a numeric confidence field with structured outputs, setting the threshold from error rates on your own traffic, tuning it against accuracy, cost, and latency, routing the escalation in your code, and re-tuning it after launch.

October 1, 2026

Cost vs. Quality Tradeoff Framework for Agent Models

The cheapest model that clears your quality bar is usually not the model at the top of a leaderboard. This framework sets the bar for one task, measures cost per quality point across a cheap, a mid-tier, and a frontier model on your own examples, and picks the cheapest one that clears the bar with margin. It uses live catalog prices and the cost each OpenRouter response reports.

October 1, 2026

How to Gate Pull Requests on LLM Evals in CI

A one-line prompt change can ship an agent that tells customers the wrong refund window, and nothing in a normal CI pipeline checks what the model says. This guide builds a fixed eval set for a support agent, a script that exits non-zero below a measured threshold, and a GitHub Actions job that blocks the merge when the pass rate drops.

October 1, 2026

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ElevenLabs is now on OpenRouter

OpenRouter is Joining Stripe

Ori Eval: Find the Best Model for What You're Building

Surpassing Frontier Performance with Fusion

How an AI Sales Agent Saved Our Sales Team 600 Hours a Month

Server-Side Code Execution Tools for AI Agents, Compared

Agent Frameworks Compared: Tool-Calling Schema Handling

LangChain vs CrewAI: Orchestration Compared to OpenRouter-Native Routing

Model Router Benchmarks

Model Routing for Support Bots: Cheap-First FAQ Handling

Confidence Thresholds for Model Escalation Routing

Cost vs. Quality Tradeoff Framework for Agent Models

How to Gate Pull Requests on LLM Evals in CI