Hugging Face Models on Foundry Managed Compute
At Build 2026, Microsoft announced Foundry Managed Compute and a Hugging Face model collection, with weekly updates to open-weight models and one-click deployment to Foundry's managed GPU platform.
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All topicsOpen models, frameworks and repositories: weight releases, community projects that take off, and open versus closed.
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41–60 of 67Jul 7
LeRobot v0.6.0: Imagine, Evaluate, Improve
Hugging Face released LeRobot v0.6.0, introducing world model policies VLA-JEPA, FastWAM and LingBot-VA, new VLAs GR00T N1.7, MolmoAct2, EO-1, EVO1 and Multitask DiT, and a unified reward model API with Robometer and TOPReward for the robotics learning loop.
Run AI workloads on any cloud, store on Hugging Face: zero-egress storage with SkyPilot
Hugging Face and SkyPilot released an integration allowing a Hugging Face Bucket or any model, dataset or Space repository to be mounted into SkyPilot tasks with an hf:// URL and an existing HF_TOKEN, running across more than 20 clouds, Kubernetes, Slurm and local environments.
Jul 2
Leanstral 1.5: Proof Abundance for All
Mistral released Leanstral 1.5 under Apache-2.0, with 119B total and 6B active parameters and major formal verification improvements. It achieves 100% on miniF2F, solves 587 of 672 PutnamBench problems, and sets current best results of 87% on FATE-H and 34% on FATE-X.
Jul 1
Hugging Face and Cerebras bring Gemma 4 to real-time voice AI
Hugging Face and Cerebras jointly demonstrated a real-time speech-to-speech pipeline, accelerating Gemma 4 31B inference with Cerebras and combining Nvidia Parakeet speech recognition with Alibaba Qwen3TTS synthesis.
Jun 11
DiffusionGemma: 4x faster text generation
Google DeepMind released experimental open-source model DiffusionGemma, generating text blocks in parallel through text diffusion and achieving up to 4 times faster inference on dedicated GPUs.
Jun 9
Introducing Gemma 4 12B: a unified, encoder-free multimodal model
Google DeepMind released Gemma 4 12B, a multimodal model for local laptop use between the edge-focused E4B and 26B MoE. Its unified encoder-free architecture feeds visual and audio inputs directly into the LLM backbone.
Jun 4
The next chapter in flood resilience: Open sourcing Google’s hydrology framework
Google Research open-sourced its hydrological modelling framework on GitHub under Apache 2.0, enabling national weather and hydrology agencies to integrate AI flood forecasting. The Python package uses PyTorch and an LSTM architecture, can train or fine-tune on Caravan data, and includes interactive tutorial notebooks and videos.
May 28
Introducing Search Toolkit
Mistral AI released the public preview of Search Toolkit, a composable framework for production search pipelines in AI applications. It unifies ingestion, retrieval and evaluation through shared interfaces, is open-source and deploys in cloud, local or edge environments.
May 22
Remote agents in Vibe. Powered by Mistral Medium 3.5.
Mistral released Mistral Medium 3.5, its first 128B dense model combining instruction following, reasoning and coding. Its weights are available under a modified MIT licence, with a 256k context window and self-hosting possible on a minimum of four GPUs.
May 17
Gemini for Science: AI experiments and tools for a new era of discovery
Google DeepMind released Gemini for Science, launching three experimental tools on Google Labs: Hypothesis Generation based on Co-Scientist.
Apr 3
Gemma 4: Byte for byte, the most capable open models
Google DeepMind released the open-source Gemma 4 family in four sizes—E2B, E4B, 26B MoE and 31B Dense—under Apache 2.0.
Mar 24
Speaking of Voxtral
Mistral AI released its first text-to-speech model, Voxtral TTS, with 4B parameters and support for nine languages: English, French, German, Spanish, Dutch, Portuguese, Italian, Hindi and Arabic. It is available through the API and Mistral Studio at $0.016 per 1k characters.
Mar 17
Introducing Mistral Small 4
Mistral AI released Mistral Small 4, the next major version in the series and its first model to combine Magistral reasoning, Pixtral multimodal capabilities and Devstral agentic coding in one model, under Apache 2.0.
Leanstral: Open-Source foundation for trustworthy vibe-coding
Mistral AI released Leanstral, the first open-source coding agent for Lean 4, using a sparse architecture with 6B active parameters. Its weights are available under Apache 2.0, and it is integrated into Mistral vibe and the free labs-leanstral-2603 API endpoint.
Mar 11
Rails testing on autopilot: Building an agent that writes what developers won't
Mistral built an autonomous agent on its open-source coding assistant Vibe to read Rails source files, generate or improve RSpec tests and run within CI/CD without human intervention.
Mar 7
WAXAL: A large-scale open resource for African language speech technology
Google Research released WAXAL, a large open speech dataset initially covering 27 sub-Saharan African languages spoken by more than 100 million people, under CC-BY-4.0.
Feb 5
Voxtral transcribes at the speed of sound.
Mistral released Voxtral Transcribe 2, comprising Voxtral Mini Transcribe V2 for batch transcription and Voxtral Realtime for real-time use.
Dec 9
Introducing: Devstral 2 and Mistral Vibe CLI.
Mistral AI released the next-generation Devstral 2 coding family, including 123B Devstral 2 under a modified MIT licence and 24B Devstral Small 2 under Apache 2.0, both open-source.
Dec 3
Introducing Mistral 3
Mistral released the Mistral 3 family, comprising 14B, 8B and 3B small dense models and its strongest yet Mistral Large 3, a sparse MoE with 41B active and 675B total parameters. All are open-source under Apache 2.0.