🌘 Kimi-K2.7-Code, our latest coding model, is now released and open-sourced! 🔷 Improved coding & agent performance over K2.6: 21.8% on Kimi Code Bench v2, 11.0% on Program Bench, and 31.5% on MLS Bench Lite. 🔷 Reasoning efficiency: Less overthinking, with 30% lower reasoning-token usage compared to K2.6. 🔷 Long-horizon coding: Improved instruction following, higher end-to-end coding task success rates. ⚡️ 6x High-Speed Mode coming soon! 🔌 Available today via Kimi API and Kimi Code. 🔗 Kimi Code: kimi.com/code 🔗 API: platform.moonshot.ai

Tldr Fable 5 low is solving in the least steps and is a great cost per task

🚀First try MiniMax 3. Not bad. Animations are a bit clunky, but overall it proposed me interesting design. Although I prefer what Kimi K2.6 proposed.

Introducing MiniMax M3: The First Open-Weights Model to Combine Three Frontier Capabilities - Coding & Agentic Frontier: 59.0% SWE-Bench Pro, 66.0% Terminal Bench 2.1, 34.8% SWE-fficiency, 28.8% KernelBench Hard, 74.2% MCP Atlas - MiniMax Sparse Attention scales context to 1M - Natively Multimodal from Step Zero API: platform.minimax.io Token Plan: platform.minimax.io/subscrib… 🚀New! MiniMax Code: code.minimax.io Weights & Tech Report in ~10 Days

Something BIG is coming

🚀 Better inference efficiency, lower costs, broader access. MiMo-V2.5 Series API pricing is now permanently reduced — by up to 99% compared to previous pricing. ✨ Unified pricing across all context lengths. MiMo Token Plans have also been upgraded: • 5–8× more usable tokens at the same price • Simpler and more transparent billing rules 🎁 As a thank-you to current users, all current Token Plan credits will be fully reset. 🎧 MiMo-V2.5-TTS remains free for a limited time. ⏰ Effective May 26 at 6:00 PM PDT. These improvements are powered by continued inference optimization and serving efficiency upgrades across the MiMo stack. 🛠️ We’ll also publish a detailed technical blog on the inference optimizations later — stay tuned.

We are making our discount permanent! 🎉 Enjoy building with DeepSeek-V4-Pro and bring your innovative ideas to life! 🚀

Gemini 3.5 Flash is built to help you execute complex, agentic workflows. 3.5 Flash rivals flagship models to deliver frontier performance for agents and coding, at the lightning speeds you expect from the Flash series.

running Hermes locally with Qwen 3.6-35b-a3b is possible on a RTX 4060 Ti 8GB. my params are: ~~~ llama-server \ -m ~/llama-models/Qwen3.6-35B-A3B-UD-Q4_K_M.gguf \ -ngl 999 -ncmoe 30 -fa on \ --cache-type-k q8_0 --cache-type-v q8_0 \ -c 32768 -n 8192 -np 1 -t 6 \ --reasoning off \ --no-cache-prompt --checkpoint-every-n-tokens -1 \ --jinja --metrics --host 0.0.0.0 --port 8080 ~~~ biggest flaws: - context: if you are coding, a few prompts will eat it all - speed: it took 17min to create a medium-difficult .py file but it works! I'm going to test /goal feature as well, to see how Qwen handle multiple compactions and see if it can finish a goal.