The model that didn't exist, so you made it yourself

Meta releases its first frontier model, Muse Wonder

Meta's Superintelligence Lab released a pair of new state-of-the-art models on Monday, Muse Wonder and Muse Wonder Full, the company's first attempt at a frontier model.

Also reported by The Verge and Wired AI

Odyssey-3 is a new generative world model that you can try for free

Odyssey is making its world model Odyssey-3 available as a public research preview. The 14-billion-parameter model generates interactive environments from text prompts in real time and can reportedly control robots, drones, and even GTA V. Odyssey claims top scores on physics benchmarks, though the methodology behind those results has limits. The article Odyssey-3 is a new generative world model that you can try for free appeared first on The Decoder.

The maker of non-text AI model Jev valued at $7.5B just weeks after launch

What has users and large corporations so excited about Jev is TypeSafe’s claim that it works significantly faster and uses far fewer tokens than LLMs.

OpenAI Decisions API Hits Public Beta With 10x Faster Typed Answers

OpenAI has released the Decisions API in public beta. It turns text and images into typed answers your code can branch on. OpenAI team states the OpenAI Decisions API runs about 10x faster than the Responses API. It targets a common pattern: prompt an LLM, then parse its text into a label. TL;DR Size: GPT-6 Luna parameter count is not disclosed. Its model card lists a 1,050,000-token context window. Runs on: OpenAI-hosted API only, via POST /v1/decisions. No open weights, no self-host

Meet the Underdog Saluki 27B: A 2-bit Qwen3.8-27B That Beats the Original at Tool Calling

Underdog, the on-device assistant from Conway Research, has released Saluki 27B under Apache 2.0. Underdog Saluki 27B is a 2-bit GGUF of Qwen3.8-27B that fits in 7.89 GB. The full BF16 model needs 54 GB. Underdog tuned the compression to protect tool calling, the skill that turns a chat model into an agent. For developers, that means a 27B-class agent model that runs in stock llama.cpp. TL;DR Size: 27B dense parameters. 7.89 GB GGUF versus 54 GB for BF16. Runs on: stock llama.cpp and

JetBrains Releases Mellum2.1: A 12B MoE Open Model for Coding Agents

JetBrains has released Mellum2.1, an open model built for coding agents and fast sub-agents. Mellum2.1 is a 12B mixture-of-experts thinking model from JetBrains that activates 2.5B parameters per token. It ships under Apache 2.0 on Hugging Face. The architecture is unchanged from Mellum2. The upgrade comes almost entirely from reinforcement learning (RL) in real software environments. The result is a small, self-hostable model that explores a repository, edits files, and checks its own changes.