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Researchers at Stanford University and Lambda Labs, have published the research paper for OpenJarvis, an open-source framework that runs inference, agents, memory, and learning entirely on-device. The open-weight models configured through OpenJarvis land within 3.2 percentage points of the best cloud model on average, at roughly 800× lower marginal API cost per query and roughly […]
Google DeepMind just released Gemma 4 12B, a dense multimodal model that strips out traditional encoders entirely. Vision and audio flow straight into the LLM backbone. The result is a model that runs agentic workflows on a consumer laptop with 16 GB of RAM. It ships under the Apache 2.0 license. Model Overview & Access
NVIDIA AI team have released Cosmos 3. It is a family of omnimodal world models for physical AI. The models combine physical reasoning, world generation, and action generation. All three capabilities live inside one open model. NVIDIA open sourced the checkpoints, training scripts, deployment tools, and datasets. The Cosmos 3 release targets robotics, autonomous vehicles,
In this tutorial, we fine-tune Liquid AI’s LFM2 model through a complete open-source workflow. We start by loading the base LFM2 checkpoint with QLoRA, preparing a chat-style supervised fine-tuning dataset, training a lightweight LoRA adapter using TRL and PEFT, and then merging the adapter back into the model. We also extend the workflow with DPO
Alibaba’s Qwen team has released Qwen3.7-Plus. The model is now available through Alibaba Cloud’s Bailian platform. Bailian is the console international users access as Model Studio. It offers API services to external developers. The release follows Alibaba’s May unveiling of the Qwen3.7 generation. Qwen3.7-Plus Qwen3.7-Plus is a multimodal large language model. The model understands images
JetBrains released Mellum2, open-sourcing the weights under the Apache 2.0 license. The first version of Mellum was a completion-focused 4B dense model. Mellum2 is its successor: a general-purpose model specialized in software engineering. It covers code generation and editing, debugging, multi-step reasoning, tool use and function calling, agentic coding, and conversational programming assistance. JetBrains team
MiniMax officially released MiniMax M3 on June 1, 2026. The model introduces MSA (MiniMax Sparse Attention), a new sparse attention architecture that gives M3 a 1M-token context window. M3 also supports image and video input and desktop computer operation natively. The API is live now. MiniMax M3 is available today via MiniMax Code, the MiniMax
Trajectory’s concurrent multi-LoRA stack reports a 2.81× experiment-throughput gain over single-tenant RL, with all code in the NovaSky-AI/SkyRL GitHub repository. Most language models improve in discontinuous jumps. A team collects data, trains, and ships a new version. This takes months and produces remarkable or catastrophic behavior for users. Trajectory wants to replace that cycle with
Text-to-speech TTS moved fast over the past year. The line between synthetic and human speech narrowed. Latency dropped below 100 milliseconds for some real-time systems. Emotional control became a standard feature rather than a research demo. This guide reviews the models that really matter in 2026. It is written for AI professionals choosing a model
Best Text-to-Speech TTS Models in 2026: A Benchmark-Based Comparison Read More »
Knowledge distillation (KD) transfers “dark knowledge” from a large teacher model to a smaller student. The student learns from the teacher’s full output probability distribution over tokens, not just correct answers. This is done via per-position Kullback–Leibler (KL) divergence over next-token probability distributions. This formulation requires a shared tokenizer. A practitioner committed to Llama-3.2-1B cannot
