FLM 2 52B Instruct 2407

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

Released November 20232K context≈ 1,536 words52B params

FLM 2 52B Instruct 2407 is a large open-weight model from CofeAI that produces embeddings from text input rather than generating conversational responses — a distinction worth noting for developers expecting a chat-style interface. At 52 billion parameters, it brings substantial capacity to embedding tasks, though its 2048-token context window is relatively constrained for a model of this size. It ships in PyTorch format, making it straightforward to integrate into standard ML pipelines.

Capabilities

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

Tool Use

Moderate

Creative Writing

FLM 2 52B Instruct 2407

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

Released November 20232K context≈ 1,536 words52B params

FLM 2 52B Instruct 2407 is a large open-weight model from CofeAI that produces embeddings from text input rather than generating conversational responses — a distinction worth noting for developers expecting a chat-style interface. At 52 billion parameters, it brings substantial capacity to embedding tasks, though its 2048-token context window is relatively constrained for a model of this size. It ships in PyTorch format, making it straightforward to integrate into standard ML pipelines.

Capabilities

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

Tool Use

Moderate

Creative Writing

Glossary

Context WindowThe maximum number of tokens a model can process in a single conversation or prompt.EmbeddingA dense numerical vector that represents a word, sentence, or concept in a high-dimensional space.EmbeddingsNumerical representations of text that capture semantic meaning, allowing the model to measure similarity between different words or phrases.Open-Weight ModelA model whose trained weights are publicly released, allowing anyone to download and run it locally.ParametersThe learned numerical values in a model — more parameters generally means more capacity but higher compute cost.PyTorchA popular open-source framework for building and training neural networks, used to define how models are structured and executed.PyTorch FormatA model saved in PyTorch's native format, allowing it to be loaded and run using the PyTorch deep learning framework.TokenA small unit of text (a word, subword, or punctuation mark) that a language model breaks input into for processing.

Capabilities

Capabilities

Use Case Fit

Glossary