llm jp 4 8b thinking

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

Released March 202666K context≈ 49,152 words8b params

A compact Japanese-language model with an explicit reasoning step built in — it works through problems before committing to an answer, which tends to improve reliability on multi-step tasks. At 8B parameters it sits in the lightweight tier, so it runs on modest hardware, though that size ceiling means it can struggle with highly complex or knowledge-intensive queries. Its open-weight Apache 2.0 release makes it straightforward to inspect, fine-tune, or deploy locally.

Capabilities

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

Reasoning & Logic

Strong

Multilingual

llm jp 4 8b thinking

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

Released March 202666K context≈ 49,152 words8b params

A compact Japanese-language model with an explicit reasoning step built in — it works through problems before committing to an answer, which tends to improve reliability on multi-step tasks. At 8B parameters it sits in the lightweight tier, so it runs on modest hardware, though that size ceiling means it can struggle with highly complex or knowledge-intensive queries. Its open-weight Apache 2.0 release makes it straightforward to inspect, fine-tune, or deploy locally.

Capabilities

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

Reasoning & Logic

Strong

Multilingual

Glossary

Fine-TuneA model created by training an existing pre-trained model on new data to specialize it for specific tasks or behaviors.Language ModelAn AI model trained to predict and generate text by learning patterns from large amounts of written data.Multi-Step TasksProblems or workflows that require a model to perform multiple sequential operations or reasoning steps to reach a final answer.ParametersThe learned numerical values in a model — more parameters generally means more capacity but higher compute cost.ReasoningThe model's ability to work through multi-step logical problems and provide justified answers rather than just pattern-matching.Reasoning StepAn explicit intermediate thinking phase where the model works through a problem before generating its final answer, improving accuracy on complex tasks.

Capabilities

Capabilities

Use Case Fit

Glossary