Mirendil Releases Fern 0.1 with 10M Token Code Context
Mirendil has released its first model, Fern 0.1, designed to handle a 10 million token context window (approx. 500k lines of code). While it achieves perfect single-needle retrieval, it lags significantly behind Claude Opus 5.5 in multi-hop reasoning and terminal benchmarks, currently available only via early access.
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▲ Marktechpost AI · 2026-10-27 13
▲ Mirendil just released Fern 0.1, its first model, and it can hold 10M tokens of code in one context window.
The key idea is that context is a second way to spend compute. Fern was pretrained from scratch with architecture, training and serving built for 10M tokens. That is about 23 MB of code, roughly half a million lines.
On Mirendil's own repos, loss keeps falling as the window grows: 0.246 bits per byte at 32K bytes down to 0.155 at 23M bytes. RULER single-needle retrieval stays at 100% from 32K to 10M tokens. It is a trade-off though: multi-hop HotpotQA drops to 45% at 10M, and Fern 0.1 scores 6.1% on Terminal Bench 4.0 versus 66.4% for Claude Opus 5.5.
Fern sits on Mirendil-Base, a 0.1 to 0.5T model that 1 researcher built with agents in 3.5 months for under $10M. Access is early access only for now......
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