A new model that lets you spend a full 1M tokens across input, thinking, and output just arrived, complete with a developer guide. Title: Gemini 4 Argon: Developer Guide URL: 📝 Overview This is the developer guide for Google DeepMind's latest frontier model, Gemini 4 Argon. It features a unified 1M-token context window and three Thinking Levels to tune reasoning depth. 🧠 Technical highlights Input, thinking, and output now share a single 1M-token window, and Long Decode lets a single response generate up to 1M tokens. The model ID is gemini-4-argon, and prompts over 4,096 tokens get automatic implicit caching at a 95% discount. 📊 Benchmarks Argon ranks #1# on the Vals Index across finance, coding, law, and tax; scores 87% on the robotics benchmark ERQA; and holds attackers to a 0.7% success rate on the Gray Swan IPI prompt-injection benchmark. 🏭 Real-world results Chrome used it to shrink a legacy code-separation effort spanning 6 million lines from months to weeks, and Gemma 4 E2B's inference throughput improved 2.85x. 💰 Availability Available now via Google AI Studio and the Gemini API, at launch pricing of $2 input / $10 output per million tokens (through November 30, 2026). #Gemini4Argon# #DeveloperGuide#

Analyzing long-form video in the Gemini API just got more accurate and up to 66% cheaper. Agentic video understanding uses tool calls to fetch only the media slices your prompt calls for. Read the full developer guide ↓

The next great token idea on @RobinhoodCrypto hasn’t been built yet. If you’re building it, Flap is here to support you. With Flap Vaults, anyone can create their own token mechanics, launch them through Flap, and even earn commissions when other builders use them. We’re also live on Robinhood Testnet, so you can test and iterate on your ideas before going live. Building something interesting? Reply here or reach out, we can help subsidize the cost of the audit. Vault Developer Guide 👇