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LFM2.5
Compact tier
Tool calling

LFM2.5 230M

Tiny edge agent floor — 230M hybrid that still does tool use.

by Liquid AI

LFM2.5 group

Overview

LFM2.5 is Liquid AI's hybrid conv+attention family for edge and agentic workloads. The 230M tier is the smallest instruct checkpoint — distilled for tool use and data extraction under tight memory budgets.

LFM2.5 230M trains on your agent's own traces with LoRA adapters or full finetuning, is benchmarked against your production model before any traffic moves, and serves through the same OpenAI-compatible API as every Overmind model. The final weights are yours to download and run anywhere.

Good for

  • On-device and edge tool-calling loops
  • High-volume data extraction at minimal serve cost
  • First experiment on the LFM2.5 ladder

More in LFM2.5

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Specs & cost

Cost to trainfrom $0.50
Cost to run (1M tok)from $2.50
GroupLFM2.5
FamilyLiquid AI
Parameters230M
TierCompact
Context window32K
Max training context32K
Tool callingYes
Methods—
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Training docs

On Overmind

  1. 01 Train on your data

    LoRA or full finetuning on a training-intent dataset from your agent's traces. Overmind recommends tiers from your data stats; you can edit every setting.

  2. 02 Benchmark vs production

    Each finished model is scored on your eval set with your rubric against the model your agent runs today. The headline is the baseline delta per metric.

  3. 03 Serve and own the weights

    Succeeded runs deploy automatically to Inference through the same OpenAI-compatible API. The final weights are yours to download and run anywhere.