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OpenAI and Anthropic just kicked off a new AI price war. GPT-6 Sol, Luna, and Claude Opus 5.5 are bringing stronger models at much lower costs. Full comparison 👇
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AI INSIGHTS
💸 GPT-6 Sol, GPT-6 Luna, Opus 5.5 Trigger a New AI Price War
Source: @_MaxBlade
Anthropic and OpenAI launched new frontier models on the same day. They’re starting a new AI model price war with the release of GPT-6 Sol, GPT-6 Luna, and Claude Opus 5.5. Main updates:
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GPT-6 Luna is now priced at $0.10/M input and $0.50/M output, around half the cost of GPT-5.6 Luna. OpenAI cut API prices by around 50% compared with previous models.
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GPT-6 Sol also dropped to $2/M input and $10/M output, matching strong performance models at a much lower price.
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Claude Opus 5.5 reduced pricing by 20% to $4/M input and $20/M output, with cheaper cached tokens for long agent workflows. Performance is reported to be close to Anthropic’s higher-end Fable 5.1 model.
The AI competition is shifting from only building the smartest model to building the best intelligence-per-dollar. Companies now care about cost per task, coding performance, and running millions of AI calls at scale.
So both OpenAI and Anthropic are lowering prices as open-weight models and cheaper competitors increase pressure on closed AI providers.
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🧠 LIVE Today: Master GPT-6 Astra: How to Prompt ChatGPT for Consistently Better Results
Jensen Huang tweeted “AGI has arrived” the day GPT-6 Astra dropped. The benchmark charts are everywhere. 99.9% on this, 98% on that.
But there’s a hidden problem:
The more powerful the model becomes, the easier it is to waste its potential.
Many users are either afraid to use it because they worry about wasting limits – or they use Astra for everything and burn through resources without getting better results.
By the end of our free webinar, you’ll learn how to:
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TODAY IN AI
AI HIGHLIGHTS
🧠 Save this newly updated Anthropic playbook to get the most out of Opus 5.5 in Claude and Claude Code. Try these prompts, workflows, and tips in your first session.
🔥 Anthropic added a new usage reset button on Claude web and desktop, letting users refresh banked limits and test Opus 5.5. Check your settings page, click here.
💸 Remember all the Siri AI hype? Apple is now paying $250M over delayed feature claims. If you had a qualifying iPhone, don’t forget to check this opportunity soon.
🦞 “OpenClaw for normies” went viral after people compared OpenClaw to Muse. Meta says it built Muse itself, but admits OpenClaw heavily shaped the product.
💻 Google’s new AI laptop, Googlebook, is finally up for pre-order. It brings Gemini directly into the workflow with screen actions, transcription & Android connections.
🤖 Qualcomm launched 2 new smartphone chips with a focus on facilitating better AI-focused features. The top model can now run a 30B-parameter MoE model locally.
💰 Big AI Fundraising: Snorkel AI raised $350M at a $3.5B valuation, nearly 3x higher than 17 months ago. Its revenue run rate also jumped 18x as AI demand for training data explodes.
NEW EMPOWERED AI TOOLS
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⭐ Opus 5.5 performs on par with Anthropic’s top-tier Claude Fable 5.1 model yet costs about 40% less to run than Opus 5.
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😎 GPT-6 Sol sits below the flagship GPT-6 Astra and above the budget-friendly GPT-6 Luna, designed for complex and professional tasks.
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🎬 Clueso MCP lets you create and edit videos by chatting with Claude or ChatGPT, and editing while keeping everything editable.
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📊 Anomalo Analyst monitors Snowflake, Databricks, and BigQuery to spot important trends, anomalies, real changes before you even ask.
AI BREAKTHROUGH
🔬 Alibaba Unveils Qwen4 AI Models and Powerful Zhenwu Chip
Alibaba is building a full AI stack with Qwen models, custom chips, cloud infrastructure, and AI agents as it pushes deeper into the global AI race:
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Qwen4 is currently in development, with future Qwen4.5 and Qwen5 models planned to scale toward 5–10 trillion parameters.
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Alibaba is researching autonomous AI systems, and recursive self-improvement workflows where models can test and improve themselves.
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The company introduced Zhenwu V900, a new AI chip that Alibaba claims delivers around 3× the performance of its previous generation and can scale into clusters of up to 500,000 chips.
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Alibaba plans to invest around $53 billion into AI infrastructure, targeting more than 20 gigawatts of data center capacity by 2032.
The bigger strategy is a full AI ecosystem:
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Qwen → foundation models
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T-Head chips → AI hardware
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Alibaba Cloud → compute infrastructure
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Agent platforms → AI applications
Alibaba wants to become China’s full-stack AI infrastructure player, combining Qwen models with its own chips and massive cloud capacity. However, trillion-parameter targets and chip performance claims are still company projections there.
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