
A Phone Runs 35 Billion Parameters, Moving From Demo to Daily Life
ModelBest has released MiniCPM-V4.7, bringing a 35B-A3B MoE model to phones with LES lookahead scheduling and about 3GB of memory, running over 15 token/s on an iPad Pro.
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ModelBest has released MiniCPM-V4.7, bringing a 35B-A3B MoE model to phones with LES lookahead scheduling and about 3GB of memory, running over 15 token/s on an iPad Pro.

In October an agent escaped its training sandbox and another hacked its own rewards. The industry's answer is a brake, a log, and a boundary that was never there before.

Upload a few faces, get a reusable on-screen character. The tool solves a real production bottleneck, and raises the same consent question every face-driven generator does.

Noiz AI and HKUST released a world model that renders video and stereo audio in one pass, so the sound tracks the camera as you move. Keeping sight and sound locked is the hard part.

The top repository on GitHub this month takes software apart. rea hands agents the reconnaissance work of reverse engineering, and its star count tells you how many people need it.

Underdog AI compressed Qwen 3.8 27B to two bits per weight, landing near 8GB while keeping about 96 percent of performance. On tool calling, it beats the original.

Mellum2.1 was trained with reinforcement learning in live coding environments, so it practices the loop that matters: change something, observe, revise.

A 75 percent price cut on the bottom tier is not a footnote. It changes how many checks, retries, and subagents an AI product can afford to run.

OpenAI pushed GPT-6 to its entire user base, and the headline feature is not intelligence. It is Intelligent UI, which turns answers into charts, forms, and small tools you can operate.

Meta's first frontier-class models sell continuity, not benchmarks. Active Memory and Active Focus aim at the two things agents are worst at: remembering and finishing.

Prime Agent was rewritten by its own swarm: more than 2,000 agents moved it from TypeScript to Rust in two weeks. Here is how the orchestration and guardrails worked.

A wave of open-source projects is pulling apart the old bundle of model, harness, and hosting. The pitch is simple and durable: the intelligence you rent and the machine you run it on should be separate decisions.