granite-speech-4.1

About

What granite-speech-4.1 is

Granite-Speech-4.1-2B Model Summary: Granite Speech 4.1 2B is a compact and efficient speech-language model, specifically designed for multilingual automatic speech recognition (ASR) and bidirectional automatic speech translation (AST) for English, French, German, Spanish, Portuguese and Japanese. The model was trained on 174,000 hours of audio from public corpora for ASR and AST as well as synthetic datasets tailored to support Japanese ASR, keyword-biased ASR and speech translation. Granite Speech 4.1 2B was trained by modality aligning an intermediate checkpoint of granite-4.0-1b-base to speech on publicly available open source corpora containing audio inputs and text targets. Compared to its predecessor granite-4.0-1b-speech, this model has the same parameter count (the new naming convention reflects actual instead of base LLM size) and provides additional capabilities and improvements: Higher transcription accuracy for multilingual ASR due to a novel dual-head CTC encoder with both graphemic and BPE outputs and frame importance sampling to focus on informative parts of the audio Punctuation and truecasing for ASR and AST in all languages (including German noun capitalization) with a simple prompt change Better keyword list biasing capability for enhanced recognition of names, acronyms and technical jargon Two additional model variants explore different capabilities and inference optimization: granite-speech-4.1-2b-plus adds speaker-attributed ASR and word-level time stamps granite-speech-4.1-2b-nar introduces a novel non-autoregressive architecture for higher throughput Evaluations: We evaluated granite-speech-4.1-2b alongside other speech-language models in the less than 8b parameter range as well as dedicated ASR and AST systems on standard benchmarks. The evaluation spanned multiple public benchmarks, with particular emphasis on English ASR tasks while also including multilingual ASR and AST for X-En and En-X translations. Performance on the Open ASR leaderboard (as of April 2026): We evaluated the model’s keyword list biasing (KWB) capability by comparing performance with and without KWB applied at inference time. We report the F1 scores of transcribed

Summarised from the published model card. Read the full card on the HuggingFace links below.

Specifications

What it is

How it works

How audio & music work

Variants

Sizes & precisions

Open weights ship in several sizes and precisions. One page, all the variants — pick the one that fits your GPU. VRAM figures are estimates from model size.

Using it via the API

Call it like any OpenAI endpoint

Once AxForge deploys granite-speech-4-1 for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (granite-speech-4-1 below is illustrative; you get the exact model name on deployment.)

$ curl -sS https://api.axforge.ai/v1/audio/transcriptions \
  -H "Authorization: Bearer $AXFORGE_API_KEY" \
  -F model="granite-speech-4-1" -F file=@audio.mp3

Details

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Papers

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Open weights

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