Granite 4.1: IBM's 8B Model Matching 32B MoE
IBM has released Granite 4.1, a family of open-source dense language models available in 3B, 8B, and 30B parameter sizes, designed for enterprise use and trained on 15 trillion tokens. The 8B model notably matches or outperforms IBM's previous 32B Mixture-of-Experts model across several benchmarks, attributed to improved training techniques and data quality. This performance gain highlights a shift from scaling model size to optimizing training pipelines and data curation.
- ▪Granite 4.1 is a family of open-source, dense language models available in 3B, 8B, and 30B parameter sizes, released by IBM under the Apache 2.0 license.
- ▪The 8B model outperforms IBM's prior 32B MoE model on benchmarks including ArenaHard, BFCL V3, and GSM8K, despite having fewer parameters.
- ▪All models were trained on 15 trillion tokens using a five-phase training process emphasizing high-quality data, with increasing focus on math, code, and instruction tuning.
- ▪Granite 4.1 supports up to 512K context length for the 8B and 30B models, achieved through phased context extension during training.
- ▪The models avoid Mixture-of-Experts (MoE) architectures and extended reasoning chains, prioritizing predictable latency and cost for enterprise deployment.
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