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LatestIBM4.1-2b
IBMSpeech → Text

IBM Releases 2B Granite Model for Multilingual Speech

The new two-billion-parameter model offers transcription capabilities for at least five major languages under a permissive Apache 2.0 license.

Apr 16, 2026
NotableApache 2.0
Granite Speech 4.1 2B

IBM has entered the open-source speech recognition arena with Granite Speech 4.1, a new two-billion-parameter model. Released under the permissive Apache 2.0 license, the model is designed for automatic speech recognition (ASR), also known as speech-to-text, and is available for developers to download and integrate freely.

This release provides a strong foundation for building multilingual voice applications. The model was trained to handle transcription for several languages, broadening its utility for global development teams.

Multilingual Capabilities

While details on the full training data are pending, the model explicitly supports high-quality transcription for at least five languages:

  • English
  • French
  • German
  • Italian
  • Spanish

The open availability of a capable ASR model from a major enterprise tech company like IBM is a notable development. It provides a commercially viable alternative to proprietary APIs and adds another powerful option alongside existing open-source models. Developers can access the full model weights and usage instructions on its Hugging Face repository.

Sources

  • ibm-granite/granite-speech-4.1-2b

    Hugging Face

    Visit
OlderQwen Releases 35B Multimodal Mixture-of-Experts ModelQwen · Alibaba · Vision-Language · 7 months agoNewerResemble AI Releases Dramabox Voice Cloning TTS ModelResemble AI · Text → Speech · 7 months ago

Get the model

Hugging Face

Specs

Parameters2B
Sample rate16 kHz
LanguagesEnglish, French, German
Size4.6 GB
PrecisionBF16
ArchitectureGraniteSpeechForConditionalGeneration
LicenseAPACHE-2.0
Downloads180.2K
Likes168

Can you run it?

Runs on just about anything.

  • BF16 (as published)

    8 GB GPU (RTX 4060) · 16 GB laptop or Mac

    5.6 GB
  • FP8

    Any modern laptop · 8 GB RAM

    3.3 GB
Your machine

Based on Hugging Face weights metadata. Assumes an 8K context and ~1 GB runtime overhead; actual needs vary. How we estimate


Modalities

Speech → Text

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