LLM Reference

Granite Models by IBM Research

10 models2023–2024Up to 8k ctxFrom $0.185/1M input

About

The Granite family of large language models, developed by IBM, is tailored for enterprise applications. These open-source models are available under the Apache 2.0 license and highlight performance, safety, and cost-efficiency. The latest iteration, Granite 3.0, marks a significant upgrade, being trained on over 12 trillion tokens in 12 languages and 116 programming languages. Offering a variety of model sizes and specializations, including the safety-focused Granite Guardian and latency-optimized Mixture-of-Experts (MoE) models, they brim with versatility. These models can handle tasks such as summarization, text classification, and code generation. They're accessible across platforms like Hugging Face, IBM watsonx, and Google Cloud's Vertex AI. IBM ensures transparency and responsible AI utilization through comprehensive documentation and benchmarks, underscoring their commitment to open-source innovation 123.

Current Variants

Use-when guidance is derived from seed capabilities, context, release, and replacement fields.

10 in view
Granite 3BCurrent

Use when the workload needs 3B parameters.

2024-103B parameters
Granite 7BCurrent

Use when the workload needs 7B parameters.

2024-107B parameters

Use when the workload needs 34B parameters.

2024-1034B parameters

Use when the workload needs 8k context and 13B parameters.

2023-118k context13B parameters

Use when the workload needs 8k context and 20B parameters.

2023-118k context20B parameters

Use when the workload needs 4k context and 8B parameters.

2023-114k context8B parameters

Use when the workload needs 8k context and 13B parameters.

2023-118k context13B parameters

Use when the workload needs 8k context and 7B parameters.

2023-118k context7B parameters

Use when the workload needs 8k context and 13B parameters.

2023-118k context13B parameters

Use when the workload needs 8k context and 13B parameters.

2023-118k context13B parameters

Release Timeline

2 release groups
2024-10
3 current
Granite 34B
34B parameters
Current
Granite 3B
3B parameters
Current
Granite 7B
7B parameters
Current
2023-11
7 current
Granite 13B
8k context13B parameters
Current
Granite 13B Chat
8k context13B parameters
Current
Granite 20B Multilingual
8k context20B parameters
Current
Granite 7B Lab
8k context7B parameters
Current
Granite 8B Japanese
4k context8B parameters
Current
IBM Granite 13B Chat v1
8k context13B parameters
Current
IBM Granite 13B Instruct v1
8k context13B parameters
Current

Specifications(10 models)

Granite model specifications comparison
ModelReleasedContextParameters
Granite 3B2024-103B
Granite 7B2024-107B
Granite 34B2024-1034B
Granite 13B Chat2023-118k13B
Granite 20B Multilingual2023-118k20B
Granite 8B Japanese2023-114k8B
Granite 13B2023-118k13B
Granite 7B Lab2023-118k7B
IBM Granite 13B Instruct v12023-118k13B
IBM Granite 13B Chat v12023-118k13B

Available From(1 provider)

Pricing

Granite model pricing by provider
ModelProviderInput / 1MOutput / 1MType
IBM Granite 13B Instruct v1IBM watsonx$0.185$0.185Serverless
IBM Granite 13B Chat v1IBM watsonx$0.185$0.185Serverless
Granite 20B MultilingualIBM watsonx$0.6$0.6Serverless
Granite 13B ChatIBM watsonx$0.6$0.6Serverless
Granite 13BIBM watsonx$0.6$0.6Serverless
Granite 8B JapaneseIBM watsonx$0.6$0.6Serverless
Granite 7B LabIBM watsonx$0.6$0.6Serverless

Frequently Asked Questions

What is Granite used for?
Granite is used for coding. The family description and listed model capabilities point to those workloads as the best fit.
How does Granite compare to Granite 4?
Granite by IBM Research is strongest where you need coding, while Granite 4 by IBM Research is the closest related family to check for audio. Granite has 10 listed variants and reaches up to 8k context, while Granite 4 reaches up to 131k context, so compare the specs and pricing tables before choosing a production model.
Which Granite model should I use?
For the lowest listed input price, start with IBM Granite 13B Instruct v1 through IBM watsonx at $0.185/1M input tokens. For the most capable/latest local choice, evaluate IBM Granite 13B Instruct v1 with 8k context.

Models(10)