LFM2.5 1.2B Base

Open WeightModel weights are publicly available — can be downloaded and self-hosted

Released November 2025128K context≈ 96,000 words1.2B params

A compact base model that punches above its weight class for its parameter count, LFM2.5 1.2B Base reflects LiquidAI's architecture experimentation beyond standard transformer designs. As a base model, it has no instruction-following or chat tuning — it completes text rather than answering questions, making it a raw foundation for fine-tuning rather than direct use. Its 128K context window is unusually generous for a model this small.

Capabilities

Capability scores are AI-generated based on model documentation, benchmarks, and technical specifications. Learn more

Long Context

Moderate

Tool Use

LFM2.5 1.2B Base

Open WeightModel weights are publicly available — can be downloaded and self-hosted

Released November 2025128K context≈ 96,000 words1.2B params

A compact base model that punches above its weight class for its parameter count, LFM2.5 1.2B Base reflects LiquidAI's architecture experimentation beyond standard transformer designs. As a base model, it has no instruction-following or chat tuning — it completes text rather than answering questions, making it a raw foundation for fine-tuning rather than direct use. Its 128K context window is unusually generous for a model this small.

Capabilities

Capability scores are AI-generated based on model documentation, benchmarks, and technical specifications. Learn more

Long Context

Moderate

Tool Use

Glossary

ArchitectureThe underlying structural design of a neural network that defines how data flows through layers and components.Base ModelA pretrained model that completes text patterns but hasn't been trained to follow instructions, serving as a starting point for customization through fine-tuning.Context WindowThe maximum number of tokens a model can process in a single conversation or prompt.Fine-TuningThe process of further training a pre-trained model on new data to adapt it for specific tasks or domains.Instruction-FollowingThe ability of a model to understand and execute specific tasks or commands given in natural language prompts.Parameter CountThe total number of adjustable weights in a model; more parameters generally mean more capacity to learn, but also require more computing power.TransformerThe dominant neural network architecture for language models, using self-attention to process sequences.

Capabilities

Capabilities

Use Case Fit

Glossary