Mirendil releases Fern 0.1, a from-scratch model with up to 10M-token context
Overview
Mirendil releases Fern 0.1, its first model, pretrained from scratch with up to 10M tokens of context, available through hosted early access only.
The company says the window equals about 23 MB of code, roughly 500,000 lines, and that Fern 0.1 received only a short round of post-training. It also says next-token prediction keeps improving as context grows to 10M tokens, but the announcement includes no benchmark results for that claim.
Mirendil's own table shows Fern 0.1 scoring 100% on RULER single-needle retrieval at every length from 32K to 10M tokens. On Terminal Bench 4.0 it scores 6.1%, against 66.4% for Claude Opus 5.5, according to MarkTechPost, which reports the figures from Mirendil's table. No open weights or quantized builds have been announced.
Written by AI from the articles below · updated Oct 27, 9:36 AM ET
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Developments
2 developments
- Oct 27, 8:57 AM ET · 1 articleMirendil releases Fern 0.1, its first coding model with 10M-token contextMarkTechPost: Mirendil releases Fern 0.1, its first model with a 10M-token context window
- Oct 26, 11:05 PM ET · 1 articleMirendil releases Fern, a model pretrained from scratch with up to 10M-token contextmeng shao: Mirendil releases Fern, a model pretrained from scratch with 10M-token context
Article timeline
The articles in this story. Times are ET.
- MarkTechPostNewsMirendil releases Fern 0.1, its first model with a 10M-token context window
AIMirendil has released Fern 0.1, its first AI model, a from-scratch coding model with a context window of up to 10M tokens, available only through early access. On RULER single-needle retrieval it scores 100% at every length from 32K to 10M tokens, but it scores 6.1% on Terminal Bench 4.0 against 66.4% for Claude Opus 5.5 in Mirendil's own table.
meng shao@shao__mengXMirendil releases Fern, a model pretrained from scratch with 10M-token contextAIMirendil releases Fern 0.1, its first model, pretrained from scratch with up to 10M tokens of context. The company says that is about 23 MB of code, roughly 500,000 lines, or several days of agent work held at once. Fern 0.1 received only a short round of post-training, and Mirendil says next-token prediction keeps improving as context grows to 10M.

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