granite 4.0 micro

Name: granite 4.0 micro
Author: IBM

by IBMGranite

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

Released September 2025131K context≈ 98,304 words

Granite 4.0 Micro is IBM's compact workhorse — small enough to run efficiently on constrained hardware, yet tuned for practical enterprise tasks like classification, summarization, and retrieval-augmented generation. It trades raw reasoning depth for speed and deployability, making it a pragmatic choice when latency and resource budgets matter more than handling complex multi-step problems.

Capabilities

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

Reasoning & Logic

Moderate

Multimodal

granite 4.0 micro

by IBMGranite

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

Released September 2025131K context≈ 98,304 words

Granite 4.0 Micro is IBM's compact workhorse — small enough to run efficiently on constrained hardware, yet tuned for practical enterprise tasks like classification, summarization, and retrieval-augmented generation. It trades raw reasoning depth for speed and deployability, making it a pragmatic choice when latency and resource budgets matter more than handling complex multi-step problems.

Capabilities

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

Reasoning & Logic

Moderate

Multimodal

Glossary

ClassificationA machine learning task where the model assigns input data to predefined categories or labels.LatencyThe time delay between sending a request and receiving the first response token from a model.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.RetrievalThe process of finding and returning relevant documents or information from a database based on a query.Retrieval-AugmentedA technique that enhances AI systems by first searching for relevant information from a database before generating responses, improving accuracy and relevance.Retrieval-Augmented GenerationA technique that allows a model to search and reference external documents or knowledge bases to answer questions more accurately and with citations.

Capabilities

Capabilities

Use Case Fit

Glossary