Luis Cano 🇪🇸
3.1K posts
@luichifree
Socio fundador de BlockchainMurcia, Emprendedor, trader de criptomonedas 💻
OpenAI beaten by Chinese open source. Joke company. Shameful they ever let Altman in the same room as the president.
MoonshotAI has released Kimi K2 Thinking, a new reasoning variant of Kimi K2 that achieves #1 in the Tau2 Bench Telecom agentic benchmark and is potentially the new leading open weights model Kimi K2 Thinking is one of the largest open weights models ever, at 1T total parameters with 32B active. K2 Thinking is the first reasoning model release within @Kimi_Moonshot's Kimi K2 model family, following non-reasoning Kimi K2 Instruct models released previously in July and September 2025. Key takeaways: ➤ Strong performance on agentic tasks: Kimi K2 Thinking achieves 93% in 𝜏²-Bench Telecom, an agentic tool use benchmark where the model acts as a customer service agent. This is the highest score we have independently measured. Tool use in long horizon agentic contexts was a strength of Kimi K2 Instruct and it appears this new Thinking variant makes substantial gains ➤ Reasoning variant of Kimi K2 Instruct: The model, as per its naming, is a reasoning variant of Kimi K2 Instruct. The model has the same architecture and same number of parameters (though different precision) as Kimi K2 Instruct and like K2 Instruct only supports text as an input (and output) modality ➤ 1T parameters but INT4 instead of FP8: Unlike Moonshot’s prior Kimi K2 Instruct releases that used FP8 precision, this model has been released natively in INT4 precision. Moonshot used quantization aware training in the post-training phase to achieve this. The impact of this is that K2 Thinking is only ~594GB, compared to just over 1TB for K2 Instruct and K2 Instruct 0905 - which translates into efficiency gains for inference and training. A potential reason for INT4 is that pre-Blackwell NVIDIA GPUs do not have support for FP4, making INT4 more suitable for achieving efficiency gains on earlier hardware. Our full set of Artificial Analysis Intelligence Index benchmarks are in progress and we will provide an update as soon as they are complete.
AlphaNet AI DEX to introduce a ground-breaking alpha-based fee model – if no alpha provided, then 0% maker fees and only 2bps taker fee for all users, which will make it the lowest base fee decentralized exchange on the market. If AlphaNet’s AI strategies and order algorithmic execution creates alpha or value for the user, then the fees assessed will be a small % of either 1) profit created or 2) slippage and execution costs saved. This speaks to the confidence in the alpha-generation capabilities and technology of the platform. Early bird VIP whitelist and real-time strategy and execution metrics to open mid-November. $PHB #AITrading
