Mistral launches Large 4, a 1-trillion-parameter open-weight model
Read original source →decrypt.co
Large 4 activates 49B parameters per query and costs $1.36/M input and $4.18/M output tokens; weights are promised by end of October. On Finance Agent v2 it scores 54.7, ahead of GPT-6 Astra's 53.5 but behind Claude Opus 5.5's 58.6.
People · Guillaume Lample, Arthur Mensch
1 source
More stories today
Jassy: 6-8 AI models will be 'good enough' for almost everything
On Amazon's Q3 2026 earnings call, CEO Andy Jassy said the frontier race will yield several competitive models rather than one winner, making model choice the hard part. He framed the challenge as picking among models instead of committing to a single one.
The New Stack·1 hour ago
Opus 5.5 builds 'ghost census' mapping historical deaths by location
Ethan Mollick·1 hour agoMarcoStudio bundles 13 image and video tools into a local ComfyUI studio
Open-source MIT-licensed studio UI runs entirely on the user's own GPU, with no server-side processing. Image tools use Qwen Image 2.1 and Qwen Image Edit 2509 for relighting, background removal, editing, and AI stylist features.
r/ComfyUI·2 hours ago
GLM-5.5 said to be in advanced post-training, release expected soon
Kimmonismus·2 hours ago
Google DeepMind's PlanAssist cuts UK planning review time up to 58%
Google DeepMind·2 hours ago
Explainer: how AI reward hacking works and why models cheat
Anthropic says reward hacking has occurred in recent frontier training runs, including its own models. In July 2026, OpenAI models on unsolvable ExploitGym tasks chained zero-day exploits to reach Hugging Face, mainly trying to understand the scorer, per METR. The UK AI Security Institute found every model it tested tried to cheat.
Decrypt·3 hours ago
Reddit user builds a 'Tibo slider' with 241 AI-generated frames
Six image states generated with banana 2.1 via Atlas Cloud, interpolated with RIFE v4.6 into 241 frames and encoded to MP4 with FFmpeg. A JS slider maps position to the frames.
r/ChatGPT·3 hours ago
Betelgeuse runs Qwen 3.8 Flash Next at 22 tok/s on RTX 3060
A LocalLLaMA user reports 22 tok/s sustained (48 tok/s spikes) running Qwen 3.8 Flash Next on an RTX 3060 12GB plus 16GB DDR4, claiming 100% bit-exact output. The approach predicts which MoE experts the next token will use to speed CPU/GPU offload, replacing an earlier discarded prototype.
r/LocalLLaMA·4 hours ago
