LFM2.5 2.6B DSpark

Name: LFM2.5 2.6B DSpark
Author: Liquid AI

by Liquid AILFM2.5

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

Released August 2026128K context≈ 96,000 words

A compact text model from LiquidAI's LFM2.5 family, punching at a small parameter count with a notably large 128k context window. Its liquid foundation architecture distinguishes it from standard transformer designs, though specific capability details for this DSpark variant are limited. It handles text-in, text-out tasks with open weights available in safetensors format.

Capabilities

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

Long Context

Strong

Instruction Following

LFM2.5 2.6B DSpark

by Liquid AILFM2.5

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

Released August 2026128K context≈ 96,000 words

A compact text model from LiquidAI's LFM2.5 family, punching at a small parameter count with a notably large 128k context window. Its liquid foundation architecture distinguishes it from standard transformer designs, though specific capability details for this DSpark variant are limited. It handles text-in, text-out tasks with open weights available in safetensors format.

Capabilities

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

Long Context

Strong

Instruction Following

Glossary

ArchitectureThe underlying structural design of a neural network that defines how data flows through layers and components.Context WindowThe maximum number of tokens a model can process in a single conversation or prompt.Liquid Foundation ArchitectureA neural network design that differs from standard transformers by using continuous, adaptive mechanisms instead of fixed attention patterns to process information.Parameter CountThe total number of adjustable weights in a model; more parameters generally mean more capacity to learn, but also require more computing power.SafetensorsA safe, fast file format for storing model weights, designed to prevent code execution vulnerabilities.Safetensors FormatA secure and efficient file format for storing model weights that prioritizes safety and speed when loading models.Text ModelA language model that processes and generates only text, without support for images, audio, or other media types.Text-In, Text-OutA model that accepts text as input and produces text as output, without support for images, audio, or other data types.TransformerThe dominant neural network architecture for language models, using self-attention to process sequences.WeightsThe numerical parameters inside a neural network that determine how it processes input and generates output.

Capabilities

Capabilities

Use Case Fit

Glossary