JiRackUltra 1b

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

Released August 2026131K context≈ 98,304 words

A compact, open-weight model from CMSManhattan with a notably large context window for its size — 131K tokens is generous for a 1B parameter model. It handles text-in, text-out tasks and is available in both GGUF and safetensors formats, making it accessible for local deployment. Details about its specific strengths or intended use cases are limited beyond these structural characteristics.

Capabilities

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

Long Context

Moderate

Reasoning & Logic

Basic

Multilingual

Use Case Fit

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

JiRackUltra 1b

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

Released August 2026131K context≈ 98,304 words

A compact, open-weight model from CMSManhattan with a notably large context window for its size — 131K tokens is generous for a 1B parameter model. It handles text-in, text-out tasks and is available in both GGUF and safetensors formats, making it accessible for local deployment. Details about its specific strengths or intended use cases are limited beyond these structural characteristics.

Capabilities

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

Long Context

Moderate

Reasoning & Logic

Basic

Multilingual

Use Case Fit

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

Glossary

Context WindowThe maximum number of tokens a model can process in a single conversation or prompt.GGUFA file format for quantized models designed for efficient CPU and GPU inference with llama.cpp.Local DeploymentRunning a model directly on your own computer or server instead of sending requests to a remote service.Open-Weight ModelA model whose trained weights are publicly released, allowing anyone to download and run it locally.Parameter ModelA neural network described by the number of learnable weights it contains; more parameters generally mean greater capacity to learn complex patterns, but also require more computational resources.SafetensorsA safe, fast file format for storing model weights, designed to prevent code execution vulnerabilities.Text-In, Text-OutA model that accepts text as input and produces text as output, without support for images, audio, or other data types.TokensThe basic units of text that a language model processes, typically representing words or word fragments.