Articles Tagged “Open Weight LLM”
8 articles found
Moonshot's Kimi K2.7 Code Arrives as an Efficient Open-Weight Coding Model
Moonshot AI's open-weight Kimi K2.7 Code launched June 12 with a 1T-parameter MoE design, a 256K context window, and roughly 30% lower reasoning-token use.
DiffusionGemma Generates Text 4x Faster With Open Diffusion-Based Decoding
Google DeepMind released DiffusionGemma, an open 26B model that generates text via parallel diffusion decoding, reaching up to 2,000 tokens per second and running locally.
MiniMax M3 Open-Weight Model Lands With 1M Context and Native Multimodal
MiniMax published the open weights and technical report for M3, an open-weight model pairing a 1M-token context window with native image and video understanding.
NVIDIA Nemotron 3 Ultra: A 550B Open Model Built for Long-Running AI Agents
NVIDIA released Nemotron 3 Ultra on June 4, 2026 — a fully open 550B-parameter reasoning model topping US open-model benchmarks and tuned for long-running AI agents.
NVIDIA Nemotron 3 Ultra: Its Most Capable Open-Weight LLM Lands at Computex 2026
NVIDIA's Nemotron 3 Ultra debuts at Computex 2026: a 550B sparse Mixture-of-Experts open-weight LLM topping the US Intelligence Index at 48, with open datasets.
Mistral Medium 3.5 Lands as a 128B Open-Weight Coder With Cloud Vibe Remote Agents
Mistral AI shipped Medium 3.5 on April 29, 2026 — a 128B-parameter dense multimodal model with a 256K context window, modified-MIT open weights, and a new Vibe remote agent runtime that hits 77.6% on SWE-Bench Verified.
Kimi K2.6 Is Here: Open-Weight Model That Tops Every Frontier AI on HLE
Moonshot AI ships Kimi K2.6 today — a 1T-parameter open-weight model that tops every closed frontier AI on HLE benchmarks, with 300-agent swarms available now on Ollama.
Qwen3.6 Arrives on Ollama: Run a 35B Agentic Coding AI Locally With 256K Context
Alibaba's Qwen3.6 is now on Ollama — a 35B open-weight model with 256K context, vision support, and thinking preservation built for agentic coding workflows you can run on your own hardware.