... Launched last week, open-source frontier model @MiniMax M2.7 scores 56.2% on SWE Bench Pro, converging towards the best proprietary models like @Claude by Anthropic Opus 4.6. How do they compare in practice? The @Kilo Code team just ran both models through three coding tasks to see if the benchmark numbers hold up. They created three TypeScript codebases, each model received the same prompt with no hints, and they scored each model independently after all tests were complete. Key takeaways ... ... Both models found all bugs and security vulnerabilities. Claude Opus 4.6 produced more thorough fixes and 2x more tests. MiniMax

... model definitely depends on your workflows and priorities. High success rate, fast completions, or cost efficient? For coding tasks, there's this thread [1] suggesting @Claude by Anthropic , @Gemini , and @OpenAI 's GPT models, while open-weight models like @MiniMax are bridging the gap with every release. [2] Curious what the community recommends for @OpenClaw ? Note: The poll is inspired by the current leaderboard on pinchbench.com by @KiloClaw [1]: What's the best AI model for coding? [2]: MiniMax

... Anthropic said it uncovered industrial-scale efforts by Chinese Labs ( @DeepSeek , Moonshot and @MiniMax-M2.5 ) to extract capabilities from its Claude models via distillation. According to Anthropic, the campaigns involved: 16M+ exchanges ~24,000 fraudulent accounts Proxy networks to bypass regional restrictions Targeted extraction of reasoning, coding and tool-use abilities Distillation is a common technique for training smaller models from larger ones. The controversy here is using a competitor