
MiniMax M2.5
MiniMax M2.5 is a 230B MoE model (10B active) that scores 80.2% on SWE-Bench Verified while costing 1/10th to 1/20th of frontier competitors like Claude Opus 4.6 and GPT-5.2.
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MiniMax M2.5 is a 230B MoE model (10B active) that scores 80.2% on SWE-Bench Verified while costing 1/10th to 1/20th of frontier competitors like Claude Opus 4.6 and GPT-5.2.

Anthropic's flagship model leads on agentic coding, enterprise knowledge work, and long-context retrieval with a 1M-token window, 128K output, and agent teams at $5/$25 per million tokens.

OpenAI's most capable agentic coding model combines frontier code generation with GPT-5-class reasoning, 400K context, and a 77.3% Terminal-Bench 2.0 score.

Four days after launch, Gemini 3.1 Pro's benchmark-topping performance is overshadowed by 90-hour lockouts for paying subscribers, quota draining while idle, and tool-calling bugs that break LangChain, n8n, and RooCode. Developers are switching to Claude.

A former Scale AI and DeepMind researcher told OpenClaw to only suggest email deletions. It hit a context limit, forgot the rule, and trashed hundreds of messages before she could stop it.

Microsoft is combining mass layoffs of middle managers with Large Action Model swarms and Copilot autonomous agents that handle resource allocation, project oversight, and multi-step business processes without human supervisors.

Four competing protocols from Visa, Mastercard, Stripe/OpenAI, and Google aim to control how AI agents spend money on your behalf in a market McKinsey projects at $5 trillion by 2030.

Alibaba releases Qwen 3.5, a 397-billion-parameter open-weight model that claims to outperform US frontier models at a fraction of the cost.

Compare the top AI agent frameworks of 2026: LangGraph, CrewAI, AutoGen, Agno, PydanticAI, Semantic Kernel, and more. Updated April 2026 with AutoGen maintenance mode warning.

Anthropic's November 2025 flagship model delivers top SWE-bench scores, a new effort parameter for reasoning control, and a 66% price cut from its predecessor.

Anthropic's fastest and most cost-efficient model, delivering 73.3% on SWE-bench Verified and first-in-family extended thinking and computer use at $1/$5 per million tokens.

Anthropic's first hybrid reasoning model with togglable extended thinking, a 200K context window, and state-of-the-art SWE-bench performance at $3/$15 per million tokens.