EXAONE 4.0 32B

Name: EXAONE 4.0 32B
Author: LG AI Research

by LG AI Research

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

Released July 2025131K context≈ 98,304 words32B params

EXAONE 4.0 32B is LG AI Research's open-weight model that balances a large 32B parameter count with a generous 131K token context window, making it capable of handling lengthy documents and extended conversations. It focuses on text-to-text tasks and is distributed in the safetensors format, signaling a practical orientation toward deployment. As an open-weight release, it offers transparency and flexibility for teams who want to inspect or fine-tune the model directly.

Capabilities

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

Instruction Following

Moderate

Long Context

EXAONE 4.0 32B

by LG AI Research

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

Released July 2025131K context≈ 98,304 words32B params

EXAONE 4.0 32B is LG AI Research's open-weight model that balances a large 32B parameter count with a generous 131K token context window, making it capable of handling lengthy documents and extended conversations. It focuses on text-to-text tasks and is distributed in the safetensors format, signaling a practical orientation toward deployment. As an open-weight release, it offers transparency and flexibility for teams who want to inspect or fine-tune the model directly.

Capabilities

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

Instruction Following

Moderate

Long Context

Glossary

Context WindowThe maximum number of tokens a model can process in a single conversation or prompt.Fine-TuneA model created by training an existing pre-trained model on new data to specialize it for specific tasks or behaviors.Open-Weight ModelA model whose trained weights are publicly released, allowing anyone to download and run it locally.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-to-TextA framework where all NLP tasks are treated as converting input text into output text, so translation, summarization, and classification use the same model structure.TokenA small unit of text (a word, subword, or punctuation mark) that a language model breaks input into for processing.TransparencyMaking AI system design, behavior, and decision-making processes visible and understandable to users and regulators.

Capabilities

Capabilities

Use Case Fit

Glossary