7The Batch (DeepLearning.AI)·
Microsoft reveals MAI-Thinking-1, a from-scratch reasoning model with MoE architecture
Microsoft introduced MAI-Thinking-1, its first reasoning language model built without distillation from third-party models, comparable in size to Claude Sonnet 4.6. The model uses a mixture-of-experts architecture (1T total / 35B active parameters), was pretrained on 30 trillion tokens of primarily licensed human-generated data, and trained via reinforcement learning across specialist models for STEM, coding, and safety. It scored 97.0% on AIME 2025, placing third behind Claude Opus 4.6 and ahead of DeepSeek V3.2, and is available in private preview via Microsoft Foundry. The release marks a strategic shift as Microsoft moves to reduce dependence on OpenAI models following a renegotiated partnership in April 2026.
Related guides (5)
Related events (8)
Microsoft Build recap: MAI-Thinking-1 and MAI Family models announced
Microsoft unveiled MAI-Thinking-1 and the broader MAI family of models at Microsoft Build 2026, as covered in the Latent Space AINews recap. The announcement represents Microsoft's push into frontier reasoning models under its own brand, distinct from its OpenAI partnership. Technical details of the MAI model family are discussed, signaling a significant strategic move toward Microsoft-native AI model development.
Microsoft Build: Seven in-house AI models, GitHub Copilot desktop agent manager, and Web IQ search API for agents
Microsoft announced seven new AI models trained from scratch (not distilled from OpenAI), including the flagship MAI-Thinking-1 reasoning model and MAI-Transcribe-1.5, plus a 'Frontier Tuning' reinforcement learning approach for enterprise workflow training. GitHub released a desktop Copilot app designed to manage multiple parallel AI agents with isolated git worktrees and bidirectional canvases. Microsoft also launched Web IQ, an agent-native Bing-powered grounding API already powering search in Copilot and ChatGPT, running 2.5x faster than alternatives with lower token costs. The roundup also covers Nous Research's Hermes Desktop cross-platform agent app, Alibaba's Qwen3.7-Plus multimodal model, and OpenAI's role-specific Codex plugins.
Mistral AI Releases Magistral: First Reasoning Model in Open and Enterprise Variants
Mistral AI announces Magistral, its first reasoning model, released in two variants: Magistral Small (24B parameters, open-weight, Apache 2.0) and Magistral Medium (enterprise, closed). Magistral Medium scores 73.6% on AIME2024 (90% with majority voting @64), while Magistral Small scores 70.7% (83.3% respectively). Key differentiators include native multilingual chain-of-thought reasoning across eight major languages, transparent traceable reasoning steps, and up to 10x faster token throughput in Le Chat via Flash Answers. The release is accompanied by a research paper covering training infrastructure, reinforcement learning algorithm, and novel observations for training reasoning models.
DeepSeek-R1 Release: Open-Source Reasoning Model on Par with OpenAI o1
DeepSeek has released DeepSeek-R1, a reasoning-focused large language model claiming performance parity with OpenAI o1 on math, code, and reasoning benchmarks. The model is fully open-source under the MIT License, including weights and outputs, enabling distillation and commercial use. Six distilled smaller models (up to 32B and 70B) are also released, with the 32B and 70B variants reportedly matching OpenAI o1-mini. API access is live at significantly lower pricing than comparable frontier models ($0.55/M input tokens, $2.19/M output tokens).
Simon Willison on Microsoft's new MAI models
Simon Willison covers Microsoft's release of new MAI (Microsoft AI) models. The post is commentary from a tier-2 source on a Microsoft model announcement, likely summarizing capabilities and context. Microsoft's MAI model line represents the company's continued push to develop proprietary frontier models alongside its OpenAI partnership.
Learning to Reason with LLMs
OpenAI announced a new model or capability focused on reasoning in large language models, published on September 12, 2024. The post, hosted on the OpenAI blog, describes advances in training LLMs to perform complex multi-step reasoning. This likely corresponds to the release of the o1 (formerly 'Strawberry') model series, which uses chain-of-thought reasoning trained via reinforcement learning to achieve significantly improved performance on math, science, and coding benchmarks.
MiniMax M2.7 proprietary reasoning model competes with Gemini and Claude Opus; roundup covers Cursor Composer 2, MAI-Image-2, Claude Code Channels, and Anthropic defense dispute
MiniMax released M2.7, a proprietary reasoning model that achieved 66.6% on MLE Bench Lite (tying Gemini 3.1) and 56.22% on SWE-Pro, priced at $0.30/$1.20 per million tokens, with the shift to proprietary marking a potential strategic pivot among Chinese AI labs away from open weights. Cursor released Composer 2, an agentic coding model built on a fine-tuned Kimi 2.5 (via Moonshot partnership), priced 86% cheaper than its predecessor and scoring 73.7 on SWE-bench Multilingual. Anthropic released Claude Code Channels, routing Telegram and Discord messages into local Claude Code sessions via MCP plugins, and separately filed a court response denying it has any backdoor or kill switch into military deployments of Claude. Microsoft announced MAI-Image-2, a text-to-image model ranking third on Arena.ai among research labs.
DeepSeek-R1-Lite-Preview Launched with o1-Level Reasoning Performance
DeepSeek has released DeepSeek-R1-Lite-Preview, a reasoning-focused model claiming o1-preview-level performance on AIME and MATH benchmarks. The model features a transparent, real-time chain-of-thought process and demonstrates inference scaling behavior where longer reasoning chains yield better results. DeepSeek has indicated that open-source model weights and a full API are forthcoming. The model is currently accessible via chat.deepseek.com.