🛠️ MiMo-V2.6 update: tool-call repetition, diagnosed & fixed. After the MiMo-V2.6 series models launched, we noticed them sometimes repeating identical or highly similar tool calls — burning context and stalling tasks, especially in MiMo Desktop, MiMo Code and OpenCode. Root cause A "reward blind spot" in scaling RL: when rewards only track final-answer correctness, inefficient behaviors along the way go unnoticed — and get amplified as training scales. Concretely, our flooding penalty only kicked in at >32 tool calls per turn, so anything below that threshold went completely unpunished. The fix We trained a light-weight repetition-specialized RL teacher — just 12 steps, ~7k examples — and merged it into the main model via MOPD, at roughly 4% of the cost of a full mixRL retrain. Repetition dropped sharply across harnesses and context lengths, while benchmarks held steady. 📦 Updated models, open-sourced (MOPD suffix): huggingface.co/collections/X… 📝 Full postmortem: mimo.xiaomi.com/blog/mimo-v2… Huge thanks to our community for the patience and feedback 🙏 Updated models go live on our API platform Sep 25, 06:00 (UTC+8), names unchanged. And for MiMo Desktop users: everyone's remaining quota in the current window will be reset.

LADIES AND GENTLEMEN, after 3 days of blessings, a 2.5 hour drive and a total of $4,500 in donations from this amazing blessing of a community I HAVE ACQUIRED THE DGX SPARK!! 😩😁😌🚀🚀🚀 Thank you to everyone who contributed and shared my post, I’m forever grateful for every single one of you!! I will be pumping out so much more quants and recipes for yall so stay tuned!! The crazy part about this is I got it for $4650, when it was posted at $4800 from Facebook marketplace, so I only needed to add $150 of my own cash!! 🤯😩 GOD IS SO GOOD!! A very special thank you to the most high, Jesus Christ for the provision and blessings brought my way. I’m forever grateful and will use this to continue glorifying your kingdom! 🙏

A lot of people in this community were genuinely shocked when they learned this: I do not own a DGX Spark. Much of the Spark-specific work I’ve released, including day-zero EXL3 and GGUF quants, vllm-exl3 development, custom kernels, SixCat evaluations, and reproducible serving recipes, has only been possible because incredible people in this community have loaned me access to their own hardware and clusters. I’m deeply grateful for that support. But borrowed access is temporary and unpredictable. I often have a new model, fix, or benchmark ready, then have to wait until someone else’s machine is available before I can validate and publish it properly. So I’m raising **$5,000 toward a DGX Spark of my own.** 🙏 𝗪𝗛𝗔𝗧 𝗔 𝗗𝗘𝗗𝗜𝗖𝗔𝗧𝗘𝗗 𝗦𝗣𝗔𝗥𝗞 𝗪𝗢𝗨𝗟𝗗 𝗘𝗡𝗔𝗕𝗟𝗘 → More true day-zero quantized model releases → Immediate hardware validation instead of projected results → Continuous vllm-exl3 and ExLlamaV3 kernel development → SixCat quality, speed, concurrency, and long-context benchmarks → Reproducible one-Spark recipes the community can run themselves → Faster debugging when new models or inference engines break It would turn a lot of: “I built it, but I need someone with a Spark to test it” into: “I built it, tested it, documented it, and released the recipe.” 𝗠𝗬 𝗣𝗨𝗕𝗟𝗜𝗖 𝗪𝗢𝗥𝗞 𝗦𝗧𝗔𝗬𝗦 𝗣𝗨𝗕𝗟𝗜𝗖 This is not an access fee, preorder, or paywall. The models, recipes, benchmarks, fixes, and tools will remain public. This is completely optional support for the hardware behind that work. I’m planning to place the order within 48 hours and will personally cover whatever the fundraiser does not. For complete transparency, I’ll publish: → The purchase receipt with private details removed → Photos of the actual DGX Spark → Total community contributions → Platform and payment fees → Final purchase cost → The amount I contributed myself To everyone who has loaned me hardware, funded compute, tested a build, submitted a PR, shared my work, or simply encouraged me: thank you. I genuinely could not have pushed this work as far as I have without this community. A contribution would mean a lot. A repost helps just as much. ❤️ ko-fi.com/victorangelcruz/go…

More details on the incident behind OpenAI’s pause: a researcher acknowledged the alert within 3 minutes, but the training run was only stopped manually 2.5 hours later. OpenAI says the automatic shutdown did not work as expected. The model had reached an external chatbot through a gap in DNS filtering. A separate detector for unusual DNS activity did not cover the affected environment. A retrospective review also found other external DNS requests that monitoring had failed to flag at the expected severity. In some cases, it treated an unhelpful response as evidence that internet access had failed. Here is what else happened: - New research into July’s Hugging Face hack documents internal Slack searches, credential collection and programs designed to maintain access to compromised servers. Agents also tried querying Claude, DeepSeek, Kimi and Qwen. - In May, another model published a researcher’s GitHub token while trying to obtain another team’s mathematical proof. It split the token to evade secret scanning, despite twice being told to solve the problem itself. - Reuters reports that agents leaked 53 ChatGPT user images online. OpenAI expects its broader investigation to take months. This is getting serious.

We are aware that codex is down and are working hard to bring back normal service.

did the codex team break something? inb4 a new Tibo reset