LLM AtlasLLM AtlasSearch models

Liquid AI

LFM2-8B-A1B

Overall 55Open weightopen-weight

Liquid AI's 8.3B/1.5B-active MoE hybrid model with 12T training tokens. 24 layers (18 conv + 6 attn). 47.9K downloads on HuggingFace.

Last verified: 2026-03-29Confidence: HighSources: 4
texttool-useopen-source
Input price
Not applicable
Output price
Not applicable
Context window
32,768
Max output
16,384
Release date
2025-11-28
Access
open-weight, self-hosted
License
LFM Open License v1.0
Last verified
2026-03-29

Capability profile

Radar view of the model's practical strengths. This chart is backed by textual summaries below for crawlability.

Benchmark summary

Compact MoE model optimized for edge and consumer deployment.

No benchmark series is attached to this model yet. Source links and product metadata are available below.

Strengths

  • • Runs on consumer hardware
  • • Fast inference
  • • Open license
  • • 12T training tokens

Trade-offs

  • • 32K context
  • • Not for coding
  • • Smaller model quality

Crawlable benchmark analysis

LFM2-8B-A1B is positioned as an edge-optimized moe model with published scores that emphasize its practical fit for buyers evaluating the entry.

Published scores highlight reasoning 52/100, coding 40/100, enterprise readiness 62/100, vision 10/100, speed 96/100, and safety 62/100.

Pricing is not applicable for this self-hosted or open-weight entry. With a context window of 32,768 tokens, it supports large-document analysis and retrieval workflows.

Benchmark coverage is still limited for this entry, so this section focuses on published metadata and deployment fit.

Sources

Provider and distribution links used to verify this model record.

Last verified: 2026-03-29

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