Blog
News, engineering deep-dives, tutorials, and comparison guides on LLM gateways, routing, agents, and EU-hosted AI from the team building Opper.
Highlights
Car Wash Test on 53 leading AI models: "I want to wash my car. The car wash is 50 meters away. Should I walk or drive?"
How to run Claude Cowork with third-party inference providers
Introduction to Schema Based Prompting: Structured inputs for Predictable outputs
All posts
Opper AI partners with Novita to bring 80+ open-weight models to the gateway
Opper AI partners with Novita to bring one of the broadest open-weight catalogues to the Opper gateway: 80+ models from DeepSeek, Moonshot, Z.ai, MiniMax, Meta, Qwen, Google, and more, on an OpenAI-compatible API at competitive prices.
Felix Wunderlich · Jul 13, 2026Opper AI partners with Morph to add speed-optimised inference for coding agents
Opper AI partners with Morph to bring its speed-optimised inference for coding agents to the Opper gateway: fast open-weight models including DeepSeek V4 Flash, GLM 5.2, Qwen, and MiniMax, on an OpenAI-compatible API with no training on customer data.
Felix Wunderlich · Jun 26, 2026High-availability inference: same model, every provider
Call a model by its plain name like claude-sonnet-4-5 and Opper serves it across every provider and region that runs it, with automatic failover, region policy, and session-sticky routing. No provider lock-in.
Göran Sandahl · Jun 23, 2026Opper AI partners with Geodd to add European inference, hosted in Norway
Opper AI partners with Geodd to bring European open-weight inference to the Opper gateway: a Norway-hosted route alongside a US route, on custom-tuned GPU infrastructure with zero data retention.
Felix Wunderlich · Jun 17, 2026Universal web search: give any model the web, on any endpoint
Give any model, Mistral, DeepSeek, Llama and more, live web search through one OpenAI-compatible tool. EU-hosted, GDPR-friendly, no search loop to build.
Jose Sabater · Jun 3, 2026We gave Hugging Face's Reachy Mini robot a brain in one hour
How the Opper team turned a Hugging Face Reachy Mini into a talking, moving robot in an hour at MagasinX, Stockholm. A realtime voice AI model through the Opper gateway gave it sight, speech and motion. A hands-on take on physical AI and embodied agents, and why realtime is the easiest way to add an AI brain to any robot or interface.
Jose Sabater · May 29, 2026Opper AI partners with Infercom for sovereign LLM inference
Opper AI partners with Infercom to add sovereign LLM inference to the Opper AI gateway. Open-weight models on SambaNova RDU dataflow hardware, available across EU, US, and JP regions.
Felix Wunderlich · May 12, 2026LLM Router Latency Benchmark 2026: OpenAI Direct vs Router APIs
Do LLM routers add latency? Does region beat model tier? We benchmarked OpenAI direct, OpenRouter, Opper, and 10+ inference backends in 2026.
Göran Sandahl · Apr 21, 2026Introducing Opper Skills for AI Coding Agents
Opper Skills bring the full power of the Opper platform directly into your AI coding agent. Install once, and your agent knows how to use Opper.
Jose Sabater · Jan 30, 2026How we reduced agent costs by 98.6% using Opper context features
A technical deep-dive into how Opper AI context features enabled a small open-weight model to match the quality of a large frontier model, at a fraction of the cost and with faster response times.
Göran Sandahl · Jan 22, 2026Automating In-Context Learning using Feedback
Turn your agent behavior into high-quality training data automatically. Learn how Opper's new feedback system creates a self-improving loop for your LLM applications.
Jose Sabater · Dec 4, 2025Introducing Model Interaction Protocol (MIP) - a Spec for Decoupling AI What from AI How
Introducing Model Interaction Protocol (MIP) - a task specification that decouples what we want models to do from how they should do it, enabling scalable, reliable AI agents in production without constant maintenance.
Göran Sandahl · Nov 25, 2025Introducing Opper Agent SDKs - Framework for reliable, headless agents
Introducing Opper Agent SDKs - powerful Python and TypeScript frameworks for building intelligent, reliable, headless agents with seamless MCP integration, multi model support, comprehensive hooks, and built-in observability.
Göran Sandahl · Oct 14, 2025Keep Your LLM Apps Running: How Opper Handles Fallbacks and Aliases
Opper makes LLM calls more reliable with built-in fallbacks, aliases, and observability—so your apps stay stable without extra code.
Mattias Lundell · Sep 30, 2025Opper AI Acquires FinetuneDB to Accelerate Reliable AI Agents at Scale
Opper AI has acquired FinetuneDB and will integrate its fine-tuning workflow into Opper’s reliability stack to accelerate reliable, task-specific agents.
Göran Sandahl · Sep 11, 2025Opper AI partners with Berget AI to bring EU-hosted serverless inference to one API
Opper AI partners with Berget AI to bring EU-hosted serverless inference to one API
Opper AI · Sep 3, 2025Lost in Context: Where LLMs Shine — and Fail — at Using What They’re Given
We present results of our Benchmark for Context tasks, with insights into what is easy and hard for each of the models
Jose Sabater · Aug 1, 2025Introducing Opper Taskbench - A Real‑World Benchmark for Task‑Oriented LLMs
We built TaskBench to measure real-world LLM performance on practical tasks like RAG, SQL generation, and agentic workflows. Here are our findings across accuracy, cost, and model size.
Jose Sabater · Jul 15, 2025Reference‑Free LLM Evaluation with Opper SDK
Three reference‑free evaluators to demonstrate how to evaluate RAG systems at runtime without gold references.
Mattias Lundell · May 6, 2025Building a Simple GitHub PR Review Agent with ReAct
In this post, we will build an initial version of a simple but effective GitHub PR review agent using the ReAct pattern.
Johnny Chadda · Apr 8, 2025Indexing docs and websites using Github Actions
This guide explores how to automatically index your documentation in Opper Indexes using GitHub Actions for integration with your CI/CD pipelines
Johnny Chadda · Mar 11, 2025New OpenAI-compatible endpoint: Use Opper with OpenAI SDKs and frameworks
Opper now provides an OpenAI-compatible API endpoint that works seamlessly with OpenAI SDKs and its ecosystem of popular AI tools and frameworks.
Göran Sandahl · Feb 17, 2025Introducing Opperator: A composable agent to automate tasks on the web
Opperator is a programmable, autonomous web agent for automating tasks on the web built with the Opper SDK.
Göran Sandahl · Feb 7, 2025Reason then respond with DeepSeek-R1 and Mistral Tiny
Using a reasoning model to generate detailed thought traces that improve the quality of AI responses, while keeping costs low.
Göran Sandahl · Jan 27, 2025Buy to build: an enterprise case for renting the AI gateway
The objective of an enterprise AI program is not to own a gateway — it is to learn, fast, how AI drives business outcomes, while the right architecture is still unsettled. That makes optionality and time-to-value the assets to protect. We make the analyst case for buying the model-access layer and spending your engineering on the differentiated work above it.
Göran Sandahl · Jan 15, 2025Agentic customer service chatbot with tools, tracing and evals
We build a chatbot to assist users by utilising tools, while maintaining context and handling errors gracefully.
Göran Sandahl · Nov 27, 2024Using o1-preview and o1-mini with RAG and structured output
In this blog post we explore how OpenAIs reasoning models o1-mini and o1-preview perform in a RAG pipeline with structured output
Göran Sandahl · Sep 15, 2024Takeaways from AI Engineer World Fair, San Fransisco 2024
Three days at the AI Engineering World Fair in San Francisco, covering the what, how and why of LLMs and how to best use them.
Göran Sandahl · Jun 27, 2024Using Examples and Few Shot Retrieval to Shape LLM Responses
We build a pipeline to shape the output of LLM calls with synthetic examples and few shot retrieval, and see how multiple non-frontier models perform
Göran Sandahl · Jun 20, 2024Resilient Azure OpenAI using Azure API Management
Exploring how to set up APIM with an OpenAI-compatible API, and how to connect it to multiple OpenAI deployments. We will also cover how to set up failover and load-balancing.
Johnny Chadda · Jun 7, 2024RAG metrics: answer correctness
In this blog post we explore how to implement and use RAG metrics to evaluate the quality of answers generated by a model. We will use the answer correctness metric to evaluate the quality of answers generated by a model.
Mattias Lundell · May 28, 2024Introducing Delvin: State of the art bug fixing agent
Delvin is an agent fixing issues from the SWE-Bench Lite dataset, achieving state-of-the-art accuracy(23%) with very simple code leveraging the Opper SDK.
Alexandre Pesant · May 21, 2024Extracting recipes from images using gpt-4o in Opper
In this blog post we explore how to use multimodal models in Opper. We will use the newly released model gpt-4o to generate structured data from images
Mattias Lundell · May 15, 2024Simple RAG with citations
In this blog post we show how to build a simple RAG feature with citations, using Opper with structured input/output and Mistral-Large.
Göran Sandahl · May 9, 2024Examples are all you need: getting the most out of LLMs part 2
Getting GPT 3.5 Turbo to 80% accuracy on the GSM8k benchmark by leveraging the teacher student pattern, synthetic examples and few shot retrieval.
Alexandre Pesant · Apr 30, 2024Getting the best out of LLMs, part 1
Dramatically improving LLMs accuracy with structured generation and chain of thought
Alexandre Pesant · Apr 12, 2024Introducing Opper
At Opper, our mission is to accelerate adoption of Generative AI by making it simpler to build production grade reasoning applications, agents and features.
Göran · Apr 11, 2024