Skip to content
← Models
Open weightsLiquid AI/10 trustMetrics-checked

LFM2.5-Encoder-350M

Open-weight bidirectional encoder converted from the LFM2.5 decoder, 8K context on CPU.

Visit official page →

About

LFM2.5-Encoder-350M is an open-weight bidirectional encoder released by Liquid AI in mid-2026, converted from the LFM2.5-350M decoder backbone rather than trained from scratch. The team replaced causal attention with bidirectional masking and applied masked-language-modeling training, producing an 8,192-token-context encoder aimed at edge, regulated, and high-volume pipeline settings.

Liquid AI positions the encoder family for understanding and classification workloads: long documents, zero-shot routing, policy linting, and PII detection across 16 languages, all runnable on CPU-only hardware. Both encoder variants ship under the LFM Open License v1.0 with Hugging Face checkpoints; fine-tuning is required for task-specific use.

Specs

Context window

Pricing

Free quota

API access

Weights

Open weights

Released

July 29, 2026

Benchmarks

Provider-reported unless a source says otherwise. Benchmarks are marketing-adjacent by nature — treat them as directional.

Use cases

embeddingsdocument-classificationpii-detectionsemantic-searchnlp

Trust score — 7/10

/10 trustMetrics-checked

Scored 7/10 (metrics tier, metrics-v1). Evidence: Verified via vendor site/docs/GitHub and reputable coverage, wave 106; Trending score 66/100 from researcher assessment.

Sources