We’re excited to share Granite 4.0 1B Speech, the latest addition to IBM’s Granite Speech collection. Designed for enterprise applications on resource-constrained devices, Granite 4.0 1B Speech is a compact speech language model built for multilingual automatic speech recognition (ASR) and two-way speech translation (AST). With only half the parameters of its predecessor, granite-speech-3.3-2b, this model offers higher English transcription accuracy, faster inference with speculative decoding, and expanded language support covering English, French, German, Spanish, Portuguese, and Japanese. Two new features in this release are Japanese ASR support and keyword list bias to improve name and acronym recognition, both of which are frequently requested features by the community. Granite 4.0 1B Speech was also recently ranked #1 on the OpenASR leaderboard, highlighting its superior performance among open speech recognition systems.
Despite its small size, Granite 4.0 1B Speech achieves very competitive results on standard English ASR benchmarks. Performance is measured using word error rate (WER) (percentage of words incorrectly transcribed), with lower scores indicating higher accuracy. As shown in Graph 1, Granite 4.0 1B Speech achieves strong WER across multiple datasets while using far fewer parameters than many comparable models.
Chart 1: granite-4.0-1B-speech delivers competitively low WER, or strong ASR accuracy, across many benchmarks despite its small size.
Like all Granite models, Granite 4.0 1B Speech is released under the Apache 2.0 license with native support in transformers and vLLM. We evaluated our model across a variety of standard ASR and AST benchmarks across English, multilingual, and translation tasks and found that it performed as well as or better than models with significantly larger numbers of parameters. Complete evaluation results, architecture details, training data, and use cases are provided on the model card. Recommended in combination with Granite Guardian for production environments that require additional risk detection.
Try it now and let us know what you think.
