Grok 4.7 Is Here
SpaceXAI's new LLM makes its biggest gains in agentic coding and knowledge work, but xhigh reasoning consumes many more tokens.
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SpaceXAI's new LLM makes its biggest gains in agentic coding and knowledge work, but xhigh reasoning consumes many more tokens.
People are using Jev to review code, control computers, play games, and organize research. Here are my favorites.
Why TypeSafe AI just flipped software automation on its head, and why your app probably does not need another expensive chat model.
TypeSafe’s System One Model produces typed, probabilistic decisions instead of prose, gaining speed by solving a narrower problem than frontier LLMs.
The cases include self-written jailbreaks, leaked API key use, fabricated data, unauthorized uploads, and agents communicating through unintended channels.
Google Research trains a compact diffusion retriever to generate diverse search slates without running an expensive reasoning LLM for every query.
The 552B open-weight multimodal model activates 8B parameters for input, 16.7B for output, and shrinks agent cache requirements.
The new LLM nearly saturates math and abstract reasoning tests, leads agentic science benchmarks, and arrives with a much higher risk profile.
Google’s third Flash release in 43 days adds stronger coding, longer agent loops, and a restricted cybersecurity model for trusted defenders.
Alibaba’s 2.4-trillion-parameter MoE adds stronger agent coordination, multimodal handling, and cache rates as low as $0.17 per million tokens.
The 330-million-parameter foundation model forecasts related series and known future events together, producing the full horizon in one pass.
MIT researchers used over 1,000 hours of smartwatch conversations to test whether LLMs can anticipate a person’s next communicative move.
The open-weight 770B-parameter LLM posted a striking automated coding result, but independent hands-on evidence is still thin.
Z.ai is letting developers self-host its flagship AI model while reserving a security gate for the largest model-service operators.
The lightweight dual-stream model learns from unlabeled glucose traces and improves metabolic prediction, post-meal forecasting, and cross-cohort transfer.
The 320B-A18B open-weight model pairs native multimodality with a one-million-token context window and unusually low API prices.
Qwen3.8-Flash-Next and GLM-5.3-Flash bring recent Claude-class performance to downloadable models, but “local” still means server-grade hardware.

Early inference tests show major efficiency and latency gains, but production scale and realistic agent workloads remain important tests.
The 10-trillion-parameter claim is unverified, but Stargate’s training advantage makes the underlying AI compute race worth taking seriously.
The 27B dense model favors practical deployment, while the 2.4-trillion-parameter MoE brings Qwen’s largest foundation model to self-hosted infrastructure.
Five practical ways to shrink your AI bill without sacrificing agent quality, from prompt caching and model routing to smarter retrieval and…
The free coding LLM has dominated OpenRouter’s rankings, while a cow-movie meme and GLM fingerprints fuel the hunt for its maker.