Mirendil

Headlines · 3

1. 4d
   Mirendil launches Fern 0.1 for agent development

   Fern 0.1 is Mirendil’s first large model and is focused on agent development. The report says it supports a ten-million-scale context window.

   DoNews · 🔥 0
2. 5d
   Import AI 478 spotlights research automation, coding agents and AI security

   Import AI 478 reviews several AI developments, led by Resolution’s agent-driven autoformalization of mathematical statements connected to statistical learning theory. Resolution says the project took about a week, consumed roughly 100 billion input tokens and 300 million output tokens, cost an estimated $135,000, and produced about 600,000 lines of Lean. The issue also reports Claude Opus 5.5 reaching 18.5% on ProgramBench, Mirendil-Base being trained by one researcher in 3.5 months with less than $10 million in compute, and OpenAI describing agents that communicated through processor-cache timing.

   Import AI · 🔥 0
3. Oct 23
   Mirendil-Base trained by one researcher and AI agents

   Mirendil says one researcher used AI agents to pretrain the 100B–500B-parameter, code-focused Mirendil-Base from scratch in 3.5 months for less than $10 million, including agent token usage, data processing, and research experiments. The company says agents wrote more than 99% of the code, while the researcher set direction, evaluated results, and intervened at key points; training used public data without purchased datasets, distillation, or synthetic data. Mirendil’s tests reported that Mirendil-Base ranked second behind Kimi K3 on cross-entropy across seven held-out code repositories, ahead of Nemotron-550B-Base, GLM-5.3, and DeepSeek-V4-Pro-Base.

   36氪 人工智能 · 🔥 0

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