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Multi-source AI news clustered, deduplicated, and scored 0–100 across authority, cluster strength, headline signal, and time decay.

  1. COMMENTARY · X — Nathan Lambert (Interconnects) English(EN) ·

    New podcast with @finbarrtimbers! We survey the latest post-training recipes, from GLM 5.1, Kimi K2.6, DeepSeek V4, Xiaomi MiMo V2.5, Nemotron Ultra, etc. and d

    A new podcast episode features Nathan Lambert and Finbarr Timbers discussing recent advancements in AI model post-training techniques. The conversation covers the industry's shift towards multi-teacher on-policy distillation, the application of Olmo-style recipes, and the broader implications of post-training for large-scale AI efforts. The episode also touches on career advice within the rapidly evolving AI landscape, reviewing models like GLM 5.1, Kimi K2.6, DeepSeek V4, Xiaomi MiMo V2.5, and Nemotron Ultra. AI

    IMPACT Provides insights into current AI model training methodologies and future trends, relevant for AI researchers and developers.

  2. SIGNIFICANT · dev.to — LLM tag English(EN) · · [3 sources]

    The 2026 Chinese LLM Price War: Top 5 Frontier API Costs Compared

    Chinese AI labs have significantly reduced LLM API prices in the first half of 2026, with DeepSeek, Xiaomi, and Moonshot making these cuts permanent. DeepSeek V4-Pro now offers the lowest cost per output token at $0.87 per million, while Xiaomi MiMo V2.5 provides a flat rate for long contexts at $3 per million output tokens. Other notable models include Alibaba's Qwen3 Max for general production balance and Moonshot's Kimi K2.6 for efficient handling of stable prompts. AI

    The 2026 Chinese LLM Price War: Top 5 Frontier API Costs Compared

    IMPACT Accelerates adoption of LLM APIs by making them significantly more affordable, especially for long-context and high-output workloads.