lucid v1 nemo

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

Released April 2025131K context≈ 98,304 words

Lucid v1 Nemo is a text-in, text-out open-weight model from DreamGen built on the Mistral NeMo architecture, offering a generous 131k token context window. Its open-weight nature means developers can inspect, fine-tune, and self-host it directly. Specific capability details beyond its architecture and context length are limited in available documentation.

Capabilities

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

Long Context

Moderate

Multilingual

Moderate

Creative Writing

Use Case Fit

Fit scores are AI-generated based on model capabilities, intended use, and technical specifications. Learn more

lucid v1 nemo

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

Released April 2025131K context≈ 98,304 words

Lucid v1 Nemo is a text-in, text-out open-weight model from DreamGen built on the Mistral NeMo architecture, offering a generous 131k token context window. Its open-weight nature means developers can inspect, fine-tune, and self-host it directly. Specific capability details beyond its architecture and context length are limited in available documentation.

Capabilities

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

Long Context

Moderate

Multilingual

Moderate

Creative Writing

Use Case Fit

Fit scores are AI-generated based on model capabilities, intended use, and technical specifications. Learn more

Glossary

ArchitectureThe underlying structural design of a neural network that defines how data flows through layers and components.Context LengthThe maximum amount of previous text a model can consider when generating its next output; longer context allows the model to maintain coherence over longer passages.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.Self-HostRunning a model on your own servers or computers instead of using a cloud service, giving you full control and privacy.Text-In, Text-OutA model that accepts text as input and produces text as output, without support for images, audio, or other data types.TokenA small unit of text (a word, subword, or punctuation mark) that a language model breaks input into for processing.