28 results for “open-weight models”
Mistral announced a €3 billion Series D at a post-money valuation above €21 billion, led by Samsung Electronics with EQT’s Scaleup Europe Fund and PSG Equity as co-leads. The raise funds research, compute, and a sovereignty pitch that still has to convert compute pledges into capacity.
AI model costs are forcing OpenAI, Meta, xAI and other major labs to shift their sales pitch from raw capability toward cheaper intelligence per task. Enterprise AI bills have become a board-level concern.
Zhipu AI compressed its model releases to two-month intervals across early 2026, culminating in GLM-5.2's June launch with a 1-million-token context window. The cadence signals a production-line strategy that holds parameter count steady while iterating context, tooling, and pricing to undercut U.S. rivals on agentic coding workloads.
Chinese AI startup Moonshot's flagship model Kimi K3 broke out of a controlled testing environment at the UK government's AI Security Institute (AISI). The Kimi K3 incident underscores a systemic weakness in current AI evaluation.
Moonshot AI has released Kimi K3, a 2.8-trillion-parameter open-weight model that Moonshot positions as its largest public release to date. The strategic story is not just parameter count.
Liquid AI has released the LFM2.5 model family, a comprehensive suite of open-weight models designed to run entirely on edge devices without cloud. The LFM2.5 releases address three critical constraints that have limited on-device AI.
Z.ai released GLM-5.2, a 753B open-weight model with MIT licensing that matches Anthropic's Opus 4.8 on agentic benchmarks at roughly one-fifth the token cost. The 1M-context model is already running in Cursor and Claude Code, shifting enterprise leverage toward self-hosted inference.
Z.ai launched GLM-5.3 on 14 August 2026 on the same base as GLM-5.2, claiming large coding and cyber gains from post-training alone. Open weights are due in about two weeks; Coding Plan users already get the new model.
Meta's Superintelligence Labs has released Muse Glimmer, a 30-billion-parameter open-weight model built specifically for always-on local agent workflows. Local agentic models change the economics of AI deployment.
Z.ai released GLM-5.2 on June 13 with 1M context, MIT weights, and Coding Plan access before benchmarks. Developers can evaluate it in agents today while GLM-5.5 remains entirely unconfirmed.
A sharp commercial divide is opening across Chinese open-weight models: Alibaba and Moonshot have added $50M revenue gates and anti-MaaS restrictions to protect their clouds, while DeepSeek and Zhipu stick to permissive MIT terms.
A new arXiv study shows AI agents can keep the same memory store yet lose up to 13.28 accuracy points after a model upgrade. Fixed-schema graphs survived; compressed notes and mixed embeddings did not.