granite 3.1 2b instruct

Name: granite 3.1 2b instruct
Author: IBM

by IBM

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

Released December 2024131K context≈ 98,304 words

A compact, efficient text model that punches above its weight for its size. IBM Granite's 2B parameter model handles instruction-following tasks with a surprisingly large 128K context window, making it capable of processing long documents despite its small footprint. It trades raw reasoning depth for speed and accessibility, fitting well into resource-constrained environments.

Capabilities

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

Multimodal

Moderate

Tool Use

granite 3.1 2b instruct

by IBM

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

Released December 2024131K context≈ 98,304 words

A compact, efficient text model that punches above its weight for its size. IBM Granite's 2B parameter model handles instruction-following tasks with a surprisingly large 128K context window, making it capable of processing long documents despite its small footprint. It trades raw reasoning depth for speed and accessibility, fitting well into resource-constrained environments.

Capabilities

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

Multimodal

Moderate

Tool Use

Glossary

AccessibilityDesigning technology so people with disabilities can use it effectively.Context WindowThe maximum number of tokens a model can process in a single conversation or prompt.Instruction-FollowingThe ability of a model to understand and execute specific tasks or commands given in natural language prompts.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.ReasoningThe model's ability to work through multi-step logical problems and provide justified answers rather than just pattern-matching.Reasoning DepthA model's ability to perform complex multi-step logical thinking and problem-solving; typically increases with model size.Resource-ConstrainedHardware with limited memory, processing power, or battery life, requiring models to be optimized for efficiency.Text ModelA language model that processes and generates only text, without support for images, audio, or other media types.

Capabilities

Capabilities

Use Case Fit

Glossary