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Thinking Machines Lab has moved its Tinker training API into general availability and added 3 major capabilities, support for the Kimi K2 Thinking reasoning model, OpenAI compatible sampling, and image input through Qwen3-VL vision language models. For AI engineers, this turns Tinker into a practical way to fine tune frontier models without building distributed training […]
OpenAI team has released their openai/circuit-sparsity model on Hugging Face and the openai/circuit_sparsity toolkit on GitHub. The release packages the models and circuits from the paper ‘Weight-sparse transformers have interpretable circuits‘. https://arxiv.org/pdf/2511.13653 What is a weight sparse transformer? The models are GPT-2 style decoder only transformers trained on Python code. Sparsity is not added after
Mistral AI has introduced Devstral 2, a next generation coding model family for software engineering agents, together with Mistral Vibe CLI, an open source command line coding assistant that runs inside the terminal or IDEs that support the Agent Communication Protocol. https://mistral.ai/news/devstral-2-vibe-cli Devstral 2 and Devstral Small 2, model sizes, context and benchmarks Devstral 2
Zhipu AI has open sourced the GLM-4.6V series as a pair of vision language models that treat images, video and tools as first class inputs for agents, not as afterthoughts bolted on top of text. Model lineup and context length The series has 2 models. GLM-4.6V is a 106B parameter foundation model for cloud and
Jina AI has released Jina-VLM, a 2.4B parameter vision language model that targets multilingual visual question answering and document understanding on constrained hardware. The model couples a SigLIP2 vision encoder with a Qwen3 language backbone and uses an attention pooling connector to reduce visual tokens while preserving spatial structure. Among open 2B scale VLMs, it
How do you keep RAG systems accurate and efficient when every query tries to stuff thousands of tokens into the context window and the retriever and generator are still optimized as 2 separate, disconnected systems? A team of researchers from Apple and University of Edinburgh released CLaRa, Continuous Latent Reasoning, (CLaRa-7B-Base, CLaRa-7B-Instruct and CLaRa-7B-E2E) a
NVIDIA announced today a significant expansion of its strategic collaboration with Mistral AI. This partnership coincides with the release of the new Mistral 3 frontier open model family, marking a pivotal moment where hardware acceleration and open-source model architecture have converged to redefine performance benchmarks. This collaboration is a massive leap in inference speed: the
How do you get GPT-5-level reasoning on real long-context, tool-using workloads without paying the quadratic attention and GPU cost that usually makes those systems impractical? DeepSeek research introduces DeepSeek-V3.2 and DeepSeek-V3.2-Speciale. They are reasoning-first models built for agents and targets high quality reasoning, long context and agent workflows, with open weights and production APIs. The
The AI coding landscape just got a massive shake-up. If you’ve been relying on Claude 3.5 Sonnet or GPT-4o for your dev workflows, you know the pain: great performance often comes with a bill that makes your wallet weep, or latency that breaks your flow.This article provides a technical overview of MiniMax-M2, focusing on its
MiniMax-M2: Technical Deep Dive into Interleaved Thinking for Agentic Coding Workflows Read More »
How do you keep synthetic data fresh and diverse for modern AI models without turning a single orchestration pipeline into the bottleneck? Meta AI researchers introduce Matrix, a decentralized framework where both control and data flow are serialized into messages that move through distributed queues. As LLM training increasingly relies on synthetic conversations, tool traces
