World Wire

TypeSafe AI has released Jev 1.14 , a new version of its System One decision model. It is live now under the jev-preview alias. It adds 3 experimental ‘danger zone’ features: images, a box type and longer context. For developers, Jev 1.14 pushes a typed decision model toward vision tasks like inspection and localization. TypeSafe shares a note that none of the 3 features are ready for production yet. TL;DR: Jev 1.14 Size: Parameters not disclosed. Context is 64k tokens per request and 32k per question by default, or 262k with an opt-in header. Runs on: TypeSafe’s hosted API only ( POST /v1/systemone ). No open weights. Hardware and quantized variants not disclosed. Performance: Small gains everywhere, largest in multilingual support (TypeSafe’s claim, no public scores). Best: In TypeSafe’s Box test, 4 edge-check questions caught 30 of 36 cut-off crops. Worst: Images and Box are not production-ready, and Box has no “not...

SpaceXAI just released Grok Voice 3.0 . Grok Voice 3.0 is a SpaceXAI speech-to-speech model that listens, reasons, calls tools and speaks. It now ranks first on the Artificial Analysis Speech-to-Speech Index with a score of 86.9. For developers, the endpoint, events and $0.08 per minute price are unchanged from Grok Voice 2.0. TL;DR Runs on: SpaceXAI’s hosted Voice Agent API only. No open weights, no local or quantized variants. Performance: Highest Index score of any model Artificial Analysis currently ranks. Best: 86.9 on the AA Speech-to-Speech Index, ranked #1. Worst: 71.6% on τ-Voice, behind GPT-Live-1 (Astra, medium) at 74.5%. Bottom line: Best: top composite score at 0.81 s time to first audio. Worst: not the leader on agentic task resolution or raw speech reasoning. What is Grok Voice 3.0? Grok Voice 3.0 is SpaceXAI’s flagship realtime voice model, exposed as grok-voice-3.0 on the /v1/realtime WebSocket endpoint . T...

Datalab has released OmniParseBench , an open OCR benchmark for document parsers. It scores parsers with 16,288 yes/no tests on 2,937 pages from 2,343 documents. The pages span 92 languages. The dataset and code are public. It helps engineers answer a sharper question than a leaderboard does: which parser handles documents like mine? Datalab sells a parser, and its own top setting, Datalab accurate, ranks second on the launch leaderboard, behind Gemini 3.8 Flash. Is it deployable? Yes. OmniParseBench is an evaluation harness, not a model. It installs with uv pip install omni-parse-bench, needs Python 3.11+, and scores outputs offline with no API keys. TL;DR Size: 16,288 tests, 2,937 pages, 2,343 documents, 22 suites, 92 languages. Runs on: any machine with Python 3.11+. Scoring needs no network. Vendor runs need each vendor’s API key. Performance: the top 3 reported systems sit within 1.3 headline points. Best: Gemini 3.8 Flash leads at 92.9; Datal...

This week, Fish Audio released Fish Audio Drama 3 . Drama 3 is a text-to-speech model from Fish Audio that takes plain-language acting direction. It is a 35B mixture-of-experts model with about 3B parameters active per token. The weights are on Hugging Face , and the model is also live in the Fish Audio API . For developers, it is a self-hostable option for scripted dialogue, audiobooks and dubbing. TL;DR Size: 35B total parameters, about 3B active per token (8 of 256 experts plus 1 shared). Context length: Not disclosed. Runs on: 1 NVIDIA GPU with at least 48 GB in FP8. No CPU, Apple MPS or AMD ROCm. Official benchmarks use 1 H200. Performance: Fish Audio’s highest-scoring model on Artificial Analysis, but still behind several closed APIs on quality Elo. Best: 95.9% on brands, places and technical terms in Artificial Analysis Pronunciation Robustness. Worst: 86.3% on exact sequences (codes, paths, emails), its weakest pronunciation category. Bot...