IBM • LLM
Granite-4.0-H-Micro is a 3B parameter from the Granite 4 family of models. These models are the latest in a series of models released by IBM. They are fine-tuned for long...
Context Window
131K tokens
Input Price/1M
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Output Price/1M
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Parameters
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Granite 4.0 Micro results on the main AI model evaluation benchmarks. Higher scores indicate better performance.
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| Terminal-Bench Hard | 2.0 | 100.0 | — |
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| LiveCodeBench | 18.0 | 100.0 | Artificial Analysis official API |
| SciCode | 12.0 | 100.0 | — |
| AA Coding Index | 5.0 | 100.0 | Artificial Analysis official API |
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| MMLU-Pro | 45.0 | 100.0 | — |
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| AA-LCR | 4.0 | 100.0 | — |
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| AA Math Index | 6.0 | 100.0 | Artificial Analysis official API |
| AIME 2025 | 6.0 | 100.0 | Artificial Analysis official API |
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| AA Intelligence Index | 7.7 | 100.0 | Artificial Analysis official API |
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| MMLU Pro | 44.7 | 100.0 | Artificial Analysis official API |
| GPQA Diamond | 34.0 | 100.0 | Artificial Analysis official API |
| IFBench | 25.0 | 100.0 | — |
| HLE | 5.0 | 100.0 | — |
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| Tau²-Bench | 13.0 | 100.0 | — |
Granite 4.0 Micro is an AI model developed by IBM, classified as a large language model (LLM). It focuses on text processing and natural language generation. As an open source model, it is available for download, customization, and on-premises deployment. With a context window of 131K tokens, it is suitable for processing long documents such as contracts, books, and complete codebases.
Granite 4.0 Micro does not have public per-token pricing available at this time. Some models offer access via enterprise plans or research programs. Check IBM's official website for up-to-date availability and pricing.
Granite 4.0 Micro was evaluated on 14 different benchmarks, covering categories like Agentic, Coding, Knowledge, Long Context, Math, overall, Reasoning, Tool Use. Results show moderate performance across available evaluations.
It's important to note that benchmarks measure specific aspects and don't capture the full user experience. Factors like instruction adherence, behavior in long conversations, and real-world task quality vary significantly between models and aren't always reflected in standard scores.
Granite 4.0 Micro is suitable for a wide range of AI applications: long document analysis (contracts, legal proceedings, codebases), text generation, summarization, translation, and general assistance.
In the 2026 AI model ecosystem, Granite 4.0 Micro competes directly with similarly capable models. IBM competes in this segment against OpenAI, Anthropic, Google, and Meta. The choice between models depends on the specific use case, budget, latency requirements, and need for features like multimodality and tool calling.
For a detailed side-by-side comparison, use our comparison tool or check the overall model ranking.
Granite-4.0-H-Micro is a 3B parameter from the Granite 4 family of models. These models are the latest in a series of models released by IBM. They are fine-tuned for long...
Granite 4.0 Micro does not have public per-token pricing available at this time. Check IBM's official website for up-to-date information.
In available benchmarks, Granite 4.0 Micro scored: Terminal-Bench Hard: 2/100, LiveCodeBench: 18/100, SciCode: 12/100. See the full table above for a detailed comparison.
Yes, Granite 4.0 Micro is an open source model. You can deploy it on-premises, customize it via fine-tuning, and maintain full control over your data. Check the official repository for the specific license.
Granite 4.0 Micro excels at general-purpose language tasks. With its large context window, it handles long documents, codebases, and extended conversations.
Last updated: June 01, 2026 • View methodology →