MODEL DIRECTORY

MODEL DIRECTORY

IBM Granite

IBM Granite

Granite 4.1 is an Apache 2.0 enterprise model family spanning compact 3B, 8B, and 30B text checkpoints plus a separate vision specialist. Its governance and modularity are stronger than its general intelligence score.

CURRENT MODEL SNAPSHOT

Provider: IBM
Current anchor: Granite 4.1, with 30B as the reference text variant
Lifecycle: Current
Weights: Open-weight under Apache 2.0
Reviewed: 21 July 2026

Abstract blue and purple gradient

Granite 4.1 treats models as enterprise components

IBM released Granite 4.1 on 29 April 2026. The text family includes dense 3B, 8B, and 30B checkpoints with up to a 512,000-token context window in IBM’s family specification, stronger instruction following and tool use, and support for 12 major languages. IBM says the 8B model can match or exceed the earlier 32B MoE model on selected tasks.

Granite Vision 4.1 is a separate specialist for documents and tables. It should not be conflated with the text checkpoints. This modularity is deliberate: choose a small model for a defined task, route visual documents to the vision model, and reserve larger systems for exceptions.

Weights are available under Apache 2.0. IBM’s broader Granite program emphasizes documentation, enterprise provenance, and governance, giving risk teams more material to inspect than many similarly sized releases.

The independent score is low; the enterprise thesis is narrower

Artificial Analysis reports an Intelligence Index score of 9 for Granite 4.1 30B in the evaluated non-reasoning configuration. It also notes concise generation across its suite. The current evaluated endpoint reports about a 130K context limit, while IBM’s family materials describe variants supporting up to 512K; record the exact deployment rather than treating those values as interchangeable.

A score of 9 means Granite 4.1 30B should not be positioned as a frontier general reasoning model. Its value is targeted instruction following, tool use, compact deployment, open licensing, and enterprise governance. IBM has highlighted Granite’s performance in the Foundation Model Transparency Index and its AI management-system work, but certification or transparency claims must be tied to the exact product and scope documented—not inherited automatically by every 4.1 artifact.

  • Use Granite where the task is bounded and operational control matters.

  • Do not turn family-level context or governance claims into endpoint-level guarantees.

  • Routing and task-specific fine-tuning can be more rational than demanding one compact model solve every problem.

The enterprise case: governed, modular, and intentionally non-frontier

Granite is a credible choice for classification, extraction, retrieval, controlled tool use, and private deployment where auditability and a modest footprint matter. It is a poor default for open-ended complex reasoning that consistently benefits from frontier capability.

How we would evaluate it

Define a bounded task with a typed output, known abstention conditions, and a premium-model escalation path. Test the 8B and 30B checkpoints on accuracy, unsupported claims, throughput, memory, review effort, and escalation quality. For vision, run a separate document test against Granite Vision 4.1.

Evidence used

Beam AI support status

Under evaluation. This record does not confirm support for every Granite checkpoint, vision model, runtime, or governance claim.

Use case 1

Governed extraction pipeline

Extract typed fields from controlled business documents with abstention and source references. Measure accuracy, omissions, unsupported values, throughput, and reviewer correction across 8B and 30B.

Use case 2

Private RAG component

Use Granite for source-grounded answers inside a private environment with a premium-model escalation path. Score citation support, refusal quality, latency, memory, and total accepted-answer cost.

Use case 3

Bounded tool workflow

Give Granite a small approved tool set and strict schemas. Insert permission failures and ambiguous requests, then measure correct action, abstention, recovery, logs, and escalation quality.

Use case 4

Vision document specialist

Evaluate Granite Vision 4.1 separately on tables, forms, and scanned documents. Track extraction, reading order, numerical accuracy, uncertainty, latency, and reviewer time.

Related LLMs

Curated alternatives to compare before selecting a model family.

ChatGPT

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ChatGPT

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DeepSeek

DeepSeek’s current V4 family provides Pro and Flash API models with thinking and non-thinking modes, a documented one-million-token context window, and compatible API interfaces.

DeepSeek

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Perplexity

Perplexity’s Sonar API family combines language models with web search and citations. The core enterprise decision is whether provider-managed retrieval and source handling fit the workflow.

Perplexity

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Gemini

Google’s Gemini family covers production and preview models for multimodal, reasoning, audio, media, and tool-oriented workloads. Model stage and endpoint stability are central to an enterprise selection.

Gemini

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Claude

Anthropic’s Claude family spans frontier reasoning, coding, vision, and faster production models. The practical choice is a specific pinned model ID on the Claude API or a supported cloud platform.

Claude

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Llama

Meta’s Llama 4 family provides open-weight, natively multimodal models. Scout emphasizes very long context and efficient deployment; Maverick targets stronger general multimodal capability.

Llama

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Start Today

Build AI agents with the right model

See how Beam can orchestrate governed AI workflows across the model family that fits your requirements.

Start Today

Build AI agents with the right model

See how Beam can orchestrate governed AI workflows across the model family that fits your requirements.

Start Today

Build AI agents with the right model

See how Beam can orchestrate governed AI workflows across the model family that fits your requirements.

FAQs

Frequently Asked Questions

Model selection, deployment, governance, and Beam support questions answered.

What is the current IBM Granite family?

Granite 4.1 includes 3B, 8B, and 30B text models plus a separate Granite Vision 4.1 specialist. Use the exact checkpoint and modality in every claim.

How strong is Granite 4.1 independently?

Artificial Analysis reports a score of 9 for the evaluated Granite 4.1 30B non-reasoning endpoint. That is not frontier reasoning performance; Granite’s case is bounded enterprise work, openness, efficiency, and governance.

Does Granite 4.1 support 512K context?

IBM describes family variants with up to 512K context, while an independently evaluated endpoint reports about 130K. Confirm the exact checkpoint and serving configuration rather than assuming the family maximum.

Is IBM Granite open-weight?

Yes. IBM publishes Granite weights under Apache 2.0. Verify the repository, model card, notices, dependencies, checksum, and any separately scoped governance or certification claim.

Does Beam support Granite 4.1 in production?

Beam support is currently Under evaluation. No blanket claim applies across every checkpoint, vision model, runtime, or deployment environment.