GGUF conversions of MediaTek-Research/Breeze-ASR-25 for use with transcribe.cpp. Ported from upstream commit cffe7cc, pinned 2026-06-29. Validated against the transformers reference at transcribe.cpp commit 3848875 on 2026-06-29. MediaTek Research's Breeze-ASR-25 — a fine-tune of OpenAI Whisper large-v2, converted to GGUF for transcribe.cpp. Optimized for Taiwanese Mandarin (it emits **Traditional Chinese**) and English, with explicit support for Mandarin-English code-switching (intra- and inter-sentential). Trained on ~11,749 hours: 10,000 h synthetic Mandarin (ODC Synth), 1,738 h English (CommonVoice17) and 11 h real code-switch (NTUML2021). Architecturally identical to Whisper large-v2 (encoder-decoder transformer, 30-second windows with chunked long-form decoding); it retains Whisper's 99-language tokenizer, but only Mandarin and English are optimized and validated — other languages remain technically accessible but out of scope.
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View details ↗GGUF conversions of nvidia/canary-180m-flash for use with transcribe.cpp. Ported from upstream commit b12ab41, pinned 2026-05-08. Validated against the NeMo reference at transcribe.cpp commit db53eda on 2026-05-08. Offline multilingual speech-to-text and translation. A multitask AED with a 17-layer FastConformer encoder and a 4-layer Transformer decoder. Supports automatic speech recognition in English, German, Spanish, and French, and bidirectional EN↔{DE, ES, FR} translation. Takes a 16 kHz mono WAV and produces a transcript. Not a streaming model; word/segment timestamps are upstream-experimental and not exposed in the v1 port.
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View details ↗GGUF conversions of nvidia/canary-1b-flash for use with transcribe.cpp. Ported from upstream commit a9a55e0, pinned 2026-05-08. Validated against the NeMo reference at transcribe.cpp commit db53eda on 2026-05-08. Offline multilingual speech-to-text and translation. A multitask AED with a 32-layer FastConformer encoder and a 4-layer Transformer decoder. Supports automatic speech recognition in English, German, Spanish, and French, and bidirectional EN↔{DE, ES, FR} translation. Takes a 16 kHz mono WAV and produces a transcript. Not a streaming model; word/segment timestamps are upstream-experimental and not exposed in the v1 port.
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View details ↗Ported from upstream commit 1698acf, pinned 2026-05-08. Validated against the NeMo reference at transcribe.cpp commit db53eda on 2026-05-08. Offline multilingual speech-to-text and translation. A multitask AED with a 24-layer FastConformer encoder and a 24-layer Transformer decoder — the original canary release. Supports automatic speech recognition in English, German, Spanish, and French, and translation between supported pairs. Takes a 16 kHz mono WAV and produces a transcript. Not a streaming model. **License: CC-BY-NC-4.0 (non-commercial only)** — the only canary variant under a non-commercial license. WER on the full LibriSpeech test-clean split (2,620 utterances), batch size 1, timestamps none. Figures without a commit were published before provenance was recorded.
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View details ↗GGUF conversions of nvidia/canary-1b-v2 for use with transcribe.cpp. Ported from upstream commit 87bc526, pinned 2026-05-08. Validated against the NeMo reference at transcribe.cpp commit db53eda on 2026-05-08. Offline multilingual speech-to-text and translation across 25 European languages. A multitask AED with a 32-layer FastConformer encoder and an 8-layer Transformer decoder. Supports automatic speech recognition for any of the 25 supported languages, plus translation between supported language pairs (per the upstream model card). Takes a 16 kHz mono WAV and produces a transcript. Not a streaming model; word and segment timestamps from the upstream model are not exposed in the v1 port.
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View details ↗GGUF conversions of nvidia/canary-qwen-2.5b for use with transcribe.cpp. Ported from upstream commit b1469e1, pinned 2026-05-15. Validated against the NeMo SALM 2.7.3 reference at transcribe.cpp commit 6f6c699 on 2026-05-16. Offline English speech-to-text. NeMo SALM (Speech-Augmented Language Model): a FastConformer audio encoder (32 layers, `d_model=1024`) feeds audio embeddings into a Qwen3-1.7B causal LM (28 layers, `hidden_size=2048`) via audio-token injection at a sentinel position in the prompt. English only. Takes a 16 kHz mono WAV and produces a transcript via greedy decoding.
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View details ↗GGUF conversions of CohereLabs/cohere-transcribe-03-2026 for use with transcribe.cpp. Ported from upstream commit 76b8b23, pinned 2026-04-16. Validated against the Transformers reference at transcribe.cpp commit bf0d0b7 on 2026-04-18. Offline multilingual speech-to-text covering 14 languages (English, French, German, Spanish, Italian, Portuguese, Dutch, Polish, Greek, Arabic, Japanese, Chinese, Vietnamese, Korean). A Conformer encoder with a Transformer encoder-decoder head (cross-attention, tied token embedding). Takes a 16 kHz mono WAV and produces a transcript. Decoding is autoregressive.
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View details ↗Ported from upstream commit 0a8193c, pinned 2026-07-07. Validated against the Transformers reference at transcribe.cpp commit d89ecb7 on 2026-07-07. Offline Arabic speech-to-text, including dialectal Arabic and Arabic-English code-switching, with English as a secondary language. An Arabic-focused adaptation of the Cohere Transcribe 03-2026 architecture: a Conformer encoder with a Transformer encoder-decoder head (cross-attention, tied token embedding). Takes a 16 kHz mono WAV and a language flag (`-l ar` or `-l en`) and produces a transcript. Decoding is autoregressive. WER on the full FLEURS ar split (428 utterances), batch size 8, timestamps none. Figures without a commit were published before provenance was recorded.
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View details ↗基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗GGUF conversions of FunAudioLLM/Fun-ASR-MLT-Nano-2512 for use with transcribe.cpp. Ported from upstream commit cf67a93, pinned 2026-05-06. Validated against the FunASR reference at transcribe.cpp commit f094d28 on 2026-05-06. Offline speech-to-text covering 31 languages, with focused optimization on East and Southeast Asian languages: Chinese, English, Cantonese, Japanese, Korean, Vietnamese, Indonesian, Thai, Malay, Filipino, plus Arabic, Hindi, and 19 European languages (Bulgarian, Croatian, Czech, Danish, Dutch, Estonian, Finnish, Greek, Hungarian, Irish, Latvian, Lithuanian, Maltese, Polish, Portuguese, Romanian, Slovak, Slovenian, Swedish). Same architecture as Fun-ASR-Nano-2512 (~800M trainable parameters: frozen SenseVoiceEncoderSmall + 2-layer audio adaptor + bundled Qwen3-0.6B LLM); trained on a smaller multilingual corpus ("hundreds of thousands of hours" per the model card, vs Nano's "tens of millions"). Takes a 16 kHz mono WAV and emits text. Not streaming, no translation, no timestamps. ITN (inverse text normalization) is on by default, matching upstream, for readable casing, punctuation, and digits; pass `--no-itn` for spoken-form output.
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View details ↗Ported from upstream commit a7088d6, pinned 2026-05-06. Validated against the FunASR reference at transcribe.cpp commit f094d28 on 2026-05-06. Offline speech-to-text in Chinese, English, and Japanese, plus 7 Chinese dialects (Wu, Cantonese, Min, Hakka, Gan, Xiang, Jin) and 26 regional Mandarin accents. ~800M trainable parameters wrapping a frozen SenseVoiceEncoderSmall (50 SAN-M main blocks + 20 transformer blocks), a 2-layer audio adaptor (512 → 1024), and a bundled Qwen3-0.6B LLM (28 layers, 16/8 GQA, BF16) that produces the transcript autoregressively. Takes a 16 kHz mono WAV and emits text. Not a streaming model, no translation, no built-in long-form chunking, no timestamps. ITN (inverse text normalization) is off by default, since with it on English can come back all caps; pass `--itn` for digits and punctuation, which helps Chinese. WER on the full LibriSpeech test-clean split (2,620 utterances). Figures without a commit were published before provenance was recorded.
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View details ↗Ported from upstream commit 15ef3b5, pinned 2026-05-12. Validated against the gigaam author package reference at transcribe.cpp commit 0fff13f8 on 2026-10-15. Offline Russian speech-to-text with greedy CTC decoding. 16-layer Conformer encoder with a 1×1 Conv1d CTC head. Output is lowercased Russian, no punctuation; 33-entry character vocabulary. WER on the full FLEURS ru split (775 utterances), batch sizes 1 and 8, timestamps none. Figures without a commit were published before provenance was recorded.
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View details ↗GGUF conversions of ai-sage/GigaAM-v3 for use with transcribe.cpp. Ported from upstream commit cec030b, pinned 2026-05-12. Validated against the gigaam author package reference at transcribe.cpp commit 0fff13f8 on 2026-10-15. Offline Russian speech-to-text with greedy CTC decoding. 16-layer Conformer encoder with a 1×1 Conv1d CTC head. Output is cased Russian with punctuation, decoded from a 256-piece SentencePiece tokenizer.
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View details ↗GGUF conversions of ai-sage/GigaAM-v3 for use with transcribe.cpp. Ported from upstream commit ec1dc1f, pinned 2026-05-12. Validated against the gigaam author package reference at transcribe.cpp commit 0fff13f8 on 2026-10-15. Offline Russian speech-to-text with greedy RNN-T decoding. 16-layer Conformer encoder paired with an RNN-T transducer head. Output is cased Russian with punctuation, decoded from a 1024-piece SentencePiece tokenizer. Not a streaming model and does not translate. Audio past the 25 s training window is encoded in overlapping windows.
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View details ↗Ported from upstream commit c7f128b, pinned 2026-05-12. Validated against the gigaam author package reference at transcribe.cpp commit 0fff13f8 on 2026-10-15. Offline Russian speech-to-text with greedy RNN-T decoding. Same 16-layer Conformer encoder as the e2e variant, fine-tuned to emit lowercased Russian with no punctuation; 33-entry character vocabulary. WER on the full FLEURS ru split (775 utterances), batch sizes 1 and 8, timestamps none. Figures without a commit were published before provenance was recorded.
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View details ↗Ported from upstream commit bd87ab8, pinned 2026-05-17. Validated against the Transformers reference at transcribe.cpp commit 275332d on 2026-05-17. Offline multilingual speech-to-text. IBM Granite Speech 4.0-1b is an audio-LLM: a Conformer encoder with block-local Shaw attention, a BLIP-2 Q-Former projector, and the Granite-4.0-1b-base LLM as an autoregressive decoder. Takes a 16 kHz mono WAV and produces a transcript; the LLM half is what writes the text. Transcribes English, French, German, Spanish, Portuguese, and Japanese. Translates between English and each of those five other languages in either direction (en ↔ fr, en ↔ de, en ↔ es, en ↔ pt, en ↔ ja) — always via English, no direct fr↔de etc. WER on the full LibriSpeech test-clean split (2,620 utterances), batch size 1, timestamps none. Figures without a commit were published before provenance was recorded.
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View details ↗GGUF conversions of ibm-granite/granite-speech-4.1-2b for use with transcribe.cpp. Ported from upstream commit 8f4bb5f, pinned 2026-05-17. Validated against the Transformers reference at transcribe.cpp commit 275332d on 2026-05-17. Offline multilingual speech-to-text. IBM Granite Speech 4.1-2b is an audio-LLM with the same architecture as 4.0-1b (Conformer encoder with block-local Shaw attention, BLIP-2 Q-Former projector, Granite-4.0-1b-base autoregressive LLM decoder) and improved punctuation and casing over 4.0-1b. Takes a 16 kHz mono WAV and produces a transcript. Transcribes English, French, German, Spanish, Portuguese, and Japanese. Translates between English and each of those five other languages in either direction (en ↔ fr, en ↔ de, en ↔ es, en ↔ pt, en ↔ ja) — always via English, no direct fr↔de etc.
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View details ↗GGUF conversions of ibm-granite/granite-speech-4.1-2b-nar for use with transcribe.cpp. Ported from upstream commit 99a4df9, pinned 2026-05-24. Validated against the Transformers reference at transcribe.cpp commit c53af2c on 2026-05-24. Offline multilingual speech-to-text in a single non-autoregressive editor pass. IBM Granite Speech 4.1-2b NAR shares the Conformer audio encoder with the AR Granite-Speech family but pairs it with a custom MLP-with- attention projector and the Granite-4.0-1b LLM used as a bidirectional editor (causal mask disabled). One forward pass produces logits over the full transcript; CTC decode yields the final text. No token-by-token loop. Takes a 16 kHz mono WAV and produces a transcript. English plus French, German, Spanish, and Portuguese; ASR only (no translation, no timestamps).
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View details ↗Ported from upstream commit edd3bf5, pinned 2026-05-17. Validated against the Transformers reference at transcribe.cpp commit 275332d on 2026-05-17. Offline multilingual speech-to-text with word-level timestamps. IBM Granite Speech 4.1-2b-plus is the timestamp-and-diarization variant of the Granite-Speech family. Same architecture as the base 4.1-2b (Conformer encoder, BLIP-2 Q-Former projector, Granite-4.0-1b autoregressive LLM decoder) with two changes: the encoder concatenates mid-layer (idx 3) and final-layer hidden states (`cat_hidden_layers=[3]`, doubling the projector K/V input from 1024 to 2048), and the LM token embeddings are tied with the lm_head. Takes a 16 kHz mono WAV and produces a transcript, with `--timestamps word` returning structured per-word timestamps (parsed from the model's `[T:N]` centisecond markers), or `--diarize` returning structured speaker-attributed turns from its separate SAA prompt. Those two prompt tasks cannot be combined. Transcribes English, French, German, Spanish, and Portuguese (no Japanese on this variant). This variant is transcription-only: unlike the base granite-speech-4.1-2b, it does not perform speech translation. WER on the full LibriSpeech test-clean split (2,620 utterances), batch size 1, timestamps none. Figures without a commit were published before provenance was recorded.
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View details ↗基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗Ported from upstream commit 0253049, pinned 2026-10-05. Validated against the SpeechBrain reference at transcribe.cpp commit aa4d0f47 on 2026-10-08. Spoken language identification over 107 languages: SpeechBrain's ECAPA-TDNN trained on VoxLingua107. NOT a transcription model: a run returns the model's language labels ranked by probability, optionally restricted to a caller-chosen set. Takes 16 kHz mono WAV; scores up to the first 30 s of a clip. Top-1 accuracy on FLEURS multilingual (3,000 utterances), scored on cpu. Measured at transcribe.cpp `cf62265a` on 2026-10-08.
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View details ↗基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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Input Audio→ Output Text
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View details ↗基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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