And don't just take our word for it: “The updated Gemini 2.5 Pro achieves leading performance on our junior-dev evals. It was the first-ever model that solved one of our evals involving a larger refactor of a request routing backend. It felt like a more senior developer because
LLMS
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Developers Embrace Gemini 2.5 Pro for High-Performance Tasks
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Developers really like 2.5 Pro: “We found Gemini 2.5 Pro to be the best frontier model when it comes to "capability over latency" ratio. I look forward to rolling it out on Replit Agent whenever a latency-sensitive task needs to be accomplished with a high degree of
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Gemini 2.5 Pro Enhanced for Coding and Web Development
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Gemini 2.5 Pro just got an upgrade & is now even better at coding, with significant gains in front-end web dev, editing, and transformation. We also fixed a bunch of function calling issues that folks have been reporting, it should now be much more reliable. More details in
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Gemini 2.5 Pro Preview Successor Auto Routes Seamlessly
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The new model, "gemini-2.5-pro-preview-05-06" is the direct successor / replacement of the previous version (03-25), if you are using the old model, no change is needed, it should auto route to the new version with the same price and rate limits.
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Gemini 2.5 Pro breaks 1400 ELO on WebDevArena leaderboard
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Ahead of I/O, we’re releasing an updated Gemini 2.5 Pro! It’s now #1 on WebDevArena leaderboard, breaking the 1400 ELO barrier! Our most advanced coding model yet, with stronger performance on code transformation & editing. Excited to build drastic agents on top of this!
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Google Unveils Gemini 2.5 Pro I/O Edition with Major Performance Gains
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Today we’re sharing an early look at our latest Gemini update for I/O! Introducing the updated Gemini 2.5 Pro (I/O edition), which ranks #1 on WebDev Arena and surpasses our previous 2.5 Pro model by +147 Elo points.
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Textbooks Have Zero Hallucination Rate Unlike AI
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you're not wrong. the only difference is that textbooks have a 0% hallucination rate
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Mixture of Experts: Historical Context and Evolution
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oh cool i didn't know about this! apparently MoEs are from the 90s. they're still not in the textbook. i had thought the first real implementation was from Shazeer et al. 2017:
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ContextGem: Open Source LLM Framework for Document Data Extraction
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Extract structured data and insights from documents with just a few lines of Python code! ContextGem is an LLM framework that makes extracting structured data and insights from documents radically easier with minimal code. 100% Open Source
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AI Agent System Automates Scientific Discovery and Lab Synthesis
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Des agents IA scientifiques peuvent automatiser les découvertes, depuis les idées de recherche jusqu’aux expériences en laboratoire ! Nous montrons qu’un système d’agents (LLMs, modèles de diffusion, équipements matériels) a été capable de découvrir et de synthétiser 5 nouvelles