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#Microsoft

All collected and published items, ordered by time. Picks are a selected subset.
Models

New models and versions, open weights, and changes in capability and pricing, with their evaluations.

10/16Fri
  1. Mustafa Suleyman · X72

    MAI announces in-house pre-trained base models in the 3T-parameter weight class

    We now have state-of-the-art pre-trained base models in the 3T-parameter weight class, built entirely in-house at MAI. Post-training results coming soon—stay tuned! Lots of details in our technical blog post. https://microsoft.ai/news/frontier-pre-training-at-microsoft-ai/

    Why it matters: The announcement places MAI’s reported progress at the pre-training stage, with post-training results still forthcoming, providing context for interpreting its claim of state-of-the-art base models.

10/12Mon
  1. Satya Nadella · X73

    Microsoft introduces Maia 300 and plans multi-gigawatt Maia deployments

    Microsoft is introducing Maia 300, which Satya Nadella says delivers 40% more tokens per watt compared to leading GPU-based systems. Starting next calendar year, Microsoft will scale its Maia family to multi-gigawatt deployments, making it the primary inference system for its own products and services. Microsoft is already deploying Maia 200 across the US, Europe, and Australia, delivering up to 1.7x more tokens per watt across experiences in Teams and Copilot, with a goal of building on full-stack efficiency gains while continuing to bring ecosystem innovations into its fleet.

    Why it matters: Making Maia the primary inference system for Microsoft’s own products and services gives its stated efficiency gains a concrete deployment context.

  2. 雷锋网57

    Microsoft releases Qwen-based Microsoft-Decision-1 and tests applications across domains

    Microsoft released Microsoft-Decision-1, a decision model post-trained from Qwen3.5-9B, and says it outperforms LLMs and decision models including Jev 1.13.0 on latency and accuracy in structured decision tasks. Its Xbox research team has used it to process more than 10,000 player feedback entries, while CEO Satya Nadella says Microsoft is testing applications across domains, including incident response, quality control, and scientific discovery. The report describes decision models as smaller, faster models that output predictions, probabilities, and confidence scores rather than natural language.

10/10Sat
  1. The Decoder66

    Microsoft launches Decision-1 decision model based on Qwen3.5-9B

    Microsoft released Decision-1, a decision model for classifications, evaluations and routing decisions, built on Qwen3.5-9B. Microsoft says it tops 36 benchmarks covering nearly 150,000 questions with 83.5% accuracy and 85 ms latency, and is 2.5 times faster than runner-up H2O-Lightning-4B. It is available through Microsoft Foundry and OpenRouter at $0.042 per million input tokens, with output tokens free.

  2. Satya Nadella · X49

    Introducing Microsoft-Decision-1, our new model for fast decision-making. It delivers top performance on structured decision tasks, outperforming both LLMs and other decision models in latency and quality. We’re already testing it across Microsoft for everything from incident response and quality control to scientific discovery.

    Introducing Microsoft-Decision-1, our new model for fast decision-making. It delivers top performance on structured decision tasks, outperforming both LLMs and other decision models in latency and quality. We’re already testing it across Microsoft for everything from incident response and quality control to scientific discovery.

10/8Thu
  1. Latent Space82

    Anthropic releases Claude Haiku 5.5 at GPT-6 Luna pricing

    Anthropic released Claude Haiku 5.5, the first Haiku-series update in about a year. Its pricing matches OpenAI's GPT-6 Luna. On the same day, Anthropic also cut prices for Sonnet 5.5 and its subscription plans.

    Why it matters: The report brings together Haiku 5.5 pricing, independent evaluations, and token-usage data to help assess cost tradeoffs for small models in agent workflows.

10/2Fri
  2. Mustafa Suleyman · X66

    Microsoft AI launches MAI-Transcribe-2-Streaming, topping AA-WER Streaming accuracy rankings

    Microsoft AI is launching MAI-Transcribe-2-Streaming, which Mustafa Suleyman calls the world's most accurate real-time transcription model. He claims it is 55% faster and 60% cheaper than ElevenLabs and invites developers to build agents on Microsoft's platform. In the quoted post, Artificial Analysis reports #1 rankings for final and first partial transcript accuracy on AA-WER Streaming, with final transcript WER of 2.5% at 0.13s after speech ends and streaming pricing of $0.54 per hour of audio.

    Why it matters: The quoted benchmark comparison pairs transcription accuracy with latency and pricing, giving readers concrete tradeoffs to consider when choosing a streaming speech model for agents.

9/29Tue
  1. Microsoft Research62

    Microsoft Research releases Quine, an AI research system for biological complexity

    Microsoft Research has released Quine, an AI research system designed for biological complexity. It combines a biological world model with an interactive harness connecting models, scientific tools, literature, and experimentalists. In work with the Broad Institute on pancreatic ductal adenocarcinoma, it predicted and prioritized thousands of compounds; the top-ranked compound produced the largest classical-to-ground-state transition in wet-lab experiments. The process from narrowing the search space to selecting a candidate for validation took one weekend.

    Why it matters: Microsoft Research describes Quine's multimodal biological world model and experimental loop, including wet-lab validation in pancreatic cancer compound screening.

9/1Tue