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This is Claude Sonnet 4.6: our most capable Sonnet model yet. It’s a full upgrade across coding, computer use, long-context reasoning, agent planning, knowledge work, and design. It also features a 1M token context window in beta.

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Claude

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7,594,999 просмотров • 5 месяцев назад •via X (Twitter)

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Introducing Claude Opus 4.6. Our smartest model got an upgrade. Opus 4.6 plans more carefully, sustains agentic tasks for longer, operates reliably in massive codebases, and catches its own mistakes. It’s also our first Opus-class model with 1M token context in beta.
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Introducing Claude Opus 4.6. Our smartest model got an upgrade. Opus 4.6 plans more carefully, sustains agentic tasks for longer, operates reliably in massive codebases, and catches its own mistakes. It’s also our first Opus-class model with 1M token context in beta.

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HERMES AGENT JUST GOT A MASSIVE FREE UPGRADE AND ALMOST NOBODY IS TALKING ABOUT IT YET. 1M token context window, runs completely free on OpenRouter and can debug itself while you use it.
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Claude 3.7 Sonnet has serious competition! Gemini 2.5 Pro is a legit good model for code. - code quality is really good - 1M token context - native multimodality - long code generation - understand large codebases I used it with Windsurf to generate an AI search agent app:
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Claude Sonnet 5 just leaked. If this is real, dev teams change overnight. Here’s why: → Massive context window (entire codebases). → Multi-agent workflows running in parallel. → Faster reasoning + fewer hallucinations. → Planning, coding, testing happening at once. → Infrastructure built for speed. This isn’t “ask → answer.” It’s delegation. Save this video, you’ll prepare properly. Want the SOP? DM me. 💬
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Claude Sonnet 4.6 just landed in Bolt. The most agentic Sonnet yet: plans multi-step features, parallelizes work, executes without hand-holding. Opus-class skill at a fraction of the cost. 48h promo: With Sonnet 4.6 only, Pro users get their monthly limit as a bonus. Free users get 2x limits.
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CHINA JUST DROPPED AN AI CODING MODEL WITH A 1M CONTEXT WINDOW. And I connected it to Claude Code to see what it could actually do. Meet GLM-X Preview On paper, a few things immediately stood out: → 1M context window → Agentic coding capabilities → Works inside Claude Code → Designed for large-scale coding and reasoning workflows But specs don't matter much if the model can't deliver in practice. So I gave it a real-world task. THE TEST One prompt: > Build a modern AI lead generation dashboard using React and Tailwind CSS. Requirements: → Dark mode → Analytics dashboard → Lead table → Email outreach section → Responsive design → Production-ready component structure Instead of generating a few snippets, it planned the architecture, generated the dashboard components, created the Tailwind configuration, and walked through the implementation requirements. What impressed me most wasn't the code itself. It was how well it maintained context throughout the workflow. That's where a 1M context window starts becoming useful. Less time re-explaining requirements. Less context loss. More room for complex projects. The AI coding race is getting very interesting. And it's no longer just GPT, Claude, and Gemini competing for attention. Results from my test below 👇
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CHINA JUST DROPPED AN AI CODING MODEL WITH A 1M CONTEXT WINDOW. And I connected it to Claude Code to see what it could actually do. Meet GLM-X Preview On paper, a few things immediately stood out: → 1M context window → Agentic coding capabilities → Works inside Claude Code → Designed for large-scale coding and reasoning workflows But specs don't matter much if the model can't deliver in practice. So I gave it a real-world task. THE TEST One prompt: > Build a modern AI lead generation dashboard using React and Tailwind CSS. Requirements: → Dark mode → Analytics dashboard → Lead table → Email outreach section → Responsive design → Production-ready component structure Instead of generating a few snippets, it planned the architecture, generated the dashboard components, created the Tailwind configuration, and walked through the implementation requirements. What impressed me most wasn't the code itself. It was how well it maintained context throughout the workflow. That's where a 1M context window starts becoming useful. Less time re-explaining requirements. Less context loss. More room for complex projects. The AI coding race is getting very interesting. And it's no longer just GPT, Claude, and Gemini competing for attention. Results from my test below 👇

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GPT-5.5 is here. It’s our smartest frontier model yet, introducing a new class of intelligence for agentic coding, computer use, knowledge work, and scientific research. Rolling out in ChatGPT and Codex today. API is coming soon.

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🚨 Big news for AI innovation: Claude Opus 4 and Claude Sonnet 4, Anthropic's most advanced models, are now available in Amazon Bedrock. These powerful models offer hybrid reasoning, 200K token context windows, and are designed for AI agents. From financial analysis to high-quality writing, to enhanced reasoning, coding, agentic capabilities and more—all with the enterprise-grade security of Amazon Web Services.
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🚨 Big news for AI innovation: Claude Opus 4 and Claude Sonnet 4, Anthropic's most advanced models, are now available in Amazon Bedrock. These powerful models offer hybrid reasoning, 200K token context windows, and are designed for AI agents. From financial analysis to high-quality writing, to enhanced reasoning, coding, agentic capabilities and more—all with the enterprise-grade security of Amazon Web Services.

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123,030 просмотров • 1 год назад

Two AI models just became a cheat code. Claude 4.6 thinks. Minimax M2.5 executes. That’s the split. Claude: • 1M token context window • Reads entire codebases • Builds full strategies • Reviews complex work Minimax: • 20x cheaper than flagship models • 80%+ on real coding benchmarks • 37% faster than older versions • Built for agent workflows Here’s the play: 1. Claude plans the system. 2. Minimax builds it. 3. Claude reviews it. 4. Minimax refines it. Strategy → Execution → Review → Scale. That loop is unfair.
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Two AI models just became a cheat code. Claude 4.6 thinks. Minimax M2.5 executes. That’s the split. Claude: • 1M token context window • Reads entire codebases • Builds full strategies • Reviews complex work Minimax: • 20x cheaper than flagship models • 80%+ on real coding benchmarks • 37% faster than older versions • Built for agent workflows Here’s the play: 1. Claude plans the system. 2. Minimax builds it. 3. Claude reviews it. 4. Minimax refines it. Strategy → Execution → Review → Scale. That loop is unfair.

Julian Goldie SEO

17,034 просмотров • 4 месяцев назад

Introducing Codespace A virtual computer that runs custom Claude Code on server. It is using 2 models: Kimi K2 + Claude Sonnet 4 in a sync. I achieved same code quality with 2x better reasoning and 53% less model cost. Access it today CodeGuide (500 credits for everyone)
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Introducing Codespace A virtual computer that runs custom Claude Code on server. It is using 2 models: Kimi K2 + Claude Sonnet 4 in a sync. I achieved same code quality with 2x better reasoning and 53% less model cost. Access it today CodeGuide (500 credits for everyone)

CJ Zafir

31,070 просмотров • 11 месяцев назад

This is wild. OpenAI just dropped GPT-5.4 and it will completely change the AI agent game. 1M context, huge leap for coding + agents, and native computer use. 7 wild examples. Bookmark this. 1. Build & Play 3D chess game
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This is wild. OpenAI just dropped GPT-5.4 and it will completely change the AI agent game. 1M context, huge leap for coding + agents, and native computer use. 7 wild examples. Bookmark this. 1. Build & Play 3D chess game

Min Choi

326,236 просмотров • 4 месяцев назад

The most hilarious part is that Claude Sonnet 4.5 is a gazillion times faster this way compared to using it via CC... The stats displayed in pi on the left are accumulative across all requests, while the context stats in CC are only for the last message.
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The most hilarious part is that Claude Sonnet 4.5 is a gazillion times faster this way compared to using it via CC... The stats displayed in pi on the left are accumulative across all requests, while the context stats in CC are only for the last message.

Mario Zechner

194,911 просмотров • 8 месяцев назад