Ported from upstream commit a07b19e, pinned 2026-05-10. Validated against the NeMo reference at transcribe.cpp commit 42528dd on 2026-05-10. Offline English speech-to-text with greedy RNN-T decoding. A FastConformer-XL encoder with an RNN-T transducer decoder. Output is lowercase, no punctuation. Not a streaming model and does not translate. 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.
Input Audio→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗GGUF conversions of nvidia/parakeet-tdt-0.6b-v2 for use with transcribe.cpp. Ported from upstream commit 1b149a3, pinned 2026-04-15. Validated against the NeMo reference at transcribe.cpp commit bf0d0b7 on 2026-04-18. Offline English speech-to-text. A Conformer encoder with a TDT/RNNT transducer decoder. Takes a 16 kHz mono WAV and produces a transcript with optional token-level timestamps. Not a streaming model; no multilingual capability (see v3 for that).
Input Audio→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗GGUF conversions of nvidia/parakeet-tdt-0.6b-v3 for use with transcribe.cpp. Ported from upstream commit 6d590f7, pinned 2026-04-16. Validated against the NeMo reference at transcribe.cpp commit bf0d0b7 on 2026-04-18. Offline multilingual speech-to-text covering 25 European languages. A Conformer encoder with a TDT/RNNT transducer decoder. Takes a 16 kHz mono WAV and produces a transcript with optional token-level timestamps. Not a streaming model and does not translate.
Input Audio→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗GGUF conversions of nvidia/parakeet-tdt-1.1b for use with transcribe.cpp. Ported from upstream commit 53276c6, pinned 2026-05-10. Validated against the NeMo reference at transcribe.cpp commit 42528dd on 2026-05-10. Offline English speech-to-text. A FastConformer-XL encoder with a TDT/RNNT transducer decoder. Takes a 16 kHz mono WAV and produces a transcript with optional token-level timestamps. Not a streaming model and does not translate.
Input Audio→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗Ported from upstream commit 675e786, pinned 2026-05-10. Validated against the NeMo reference at transcribe.cpp commit 42528dd on 2026-05-10. Offline English speech-to-text with punctuation and capitalization. A FastConformer-XL encoder with a TDT/RNNT transducer decoder (the auxiliary CTC head from the upstream hybrid checkpoint is dropped at convert time). Not a streaming model and does not translate. 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.
Input Audio→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗Ported from upstream commit 431a349, pinned 2026-05-10. Validated against the NeMo reference at transcribe.cpp commit 42528dd on 2026-05-10. Offline English speech-to-text with punctuation and capitalization. A FastConformer encoder with a TDT/RNNT transducer decoder (the auxiliary CTC head from the upstream hybrid checkpoint is dropped at convert time). Not a streaming model and does not translate. 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.
Input Audio→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗GGUF conversions of moondream/parakeet-ultra for use with transcribe.cpp. Ported from upstream commit 73175eb, pinned 2026-10-04. Validated against the kestrel 0.9.1 (Photon) reference at transcribe.cpp commit 08f9e6f0 on 2026-10-05. Moondream's post-trained parakeet-tdt-0.6b-v3. Offline multilingual speech-to-text over the same 25 European languages, with lower error rates than v3 on English and on every FLEURS language we measured. A FastConformer encoder with a TDT transducer decoder, plus a small voice-activity head that the model uses to cut long recordings at pauses into segments of at most 30 seconds. Takes 16 kHz mono WAV and produces a punctuated, cased transcript with optional token-level timestamps. A drop-in replacement for v3: same size, languages and API. Not a streaming model and does not translate.
Input Audio→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗GGUF conversions of nvidia/parakeet-unified-en-0.6b for use with transcribe.cpp. Ported from upstream commit d4ac992, pinned 2026-05-10. Validated against the NeMo reference at transcribe.cpp commit 42528dd on 2026-05-10. English speech-to-text with punctuation and capitalization. A FastConformer encoder with an RNN-T transducer decoder, trained as a 'unified' streaming/offline model. This port runs the model in both offline and buffered streaming modes.
Input Audio→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗GGUF conversions of Qwen/Qwen3-ASR-0.6B for use with transcribe.cpp. Ported from upstream commit 5eb1441, pinned 2026-04-19. Validated against the qwen_asr 0.0.6 reference at transcribe.cpp commit 3f61df7 on 2026-04-20. Offline multilingual speech-to-text. An 18-layer bidirectional audio encoder feeds a 28-layer Qwen3 causal LM with audio-token injection (fused audio+text sequence, no cross-attention). Auto-detects the audio's language across 30 languages and emits the transcript in that language. Takes a 16 kHz mono WAV and produces a transcript.
Input Audio→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗GGUF conversions of Qwen/Qwen3-ASR-1.7B for use with transcribe.cpp. Ported from upstream commit 7278e1e, pinned 2026-04-19. Validated against the qwen_asr 0.0.6 reference at transcribe.cpp commit 3f61df7 on 2026-04-20. Offline multilingual speech-to-text. Same audio-LLM architecture as the 0.6B variant (bidirectional audio encoder feeding a Qwen3 causal LM with audio-token injection), wider: encoder `d_model=1024` (16 heads), LM `hidden_size=2048`, `intermediate_size=6144`. Auto-detects the audio's language across 30 languages and emits the transcript in that language. Takes a 16 kHz mono WAV and produces a transcript.
Input Audio→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗GGUF conversions of FunAudioLLM/SenseVoiceSmall for use with transcribe.cpp. Ported from upstream commit 3eb3b4e, pinned 2026-05-06. Validated against the FunASR reference at transcribe.cpp commit f094d28 on 2026-05-06. Offline multilingual speech-to-text in Chinese, Cantonese, English, Japanese, and Korean. A SAN-M encoder with a single CTC head over a 25,055-token SentencePiece vocabulary. Takes a 16 kHz mono WAV (capped at 30 seconds per call, per upstream's direct-inference contract) and produces a transcript. Not a streaming model, no translation, no built-in long-form chunking. The same CTC head also emits language-ID, simple emotion labels, audio-event tags, and inverse-text-normalization control tags. These tags are hidden unless `--raw-tokens` is passed. ITN is on by default for readable casing, punctuation, and digits; pass `--no-itn` for upstream's spoken-form output.
Input Audio→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗Ported from upstream commit 5cd7945, pinned 2026-10-09. Validated against the silero-vad 6.2.3 (TorchScript, CPU, F32) reference at transcribe.cpp commit 2674b95d on 2026-10-10. Voice activity detection by the Silero Team. Not a transcription model: the VAD role produces per-frame speech probabilities (offline or streaming) and offline speech segments. CPU is the default backend for reference fidelity. transcribe.cpp also loads whisper.cpp's `ggml-silero-v5.1.2.bin` / `v6.2.0.bin`. From the C API, use the VAD role (`include/transcribe/vad.h`): offline segments with `transcribe_vad_run`, live per-frame probabilities with `transcribe_vad_stream_feed`.
Input Audio→ Output Not verified
Price not verifiedCheck multimodal and channel pricing separately
View details ↗GGUF conversions of mistralai/Voxtral-Mini-3B-2507 for use with transcribe.cpp. Ported from upstream commit 3060fe3, pinned 2026-06-06. Validated against the Transformers reference at transcribe.cpp commit 483c122 on 2026-06-06. Offline audio-LLM speech-to-text and speech translation. A Whisper-large-v3 bidirectional audio encoder feeds a 4-frame-group projector (375 audio tokens per 30 s chunk) into a Ministral-3B causal LM (30 layers, GQA 32/8, NEOX RoPE, SwiGLU) via audio-token injection. Takes a 16 kHz mono WAV and produces a transcript via greedy decoding; speech translation runs through the mistral-common instruct template. The smaller sibling of Voxtral Small 24B — same encoder, projector, log-mel frontend, and tekken tokenizer, with a 3B decoder in place of Mistral-Small-24B.
Input Audio→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗GGUF conversions of mistralai/Voxtral-Mini-4B-Realtime-2602 for use with transcribe.cpp. Ported from upstream commit 2769294, pinned 2026-06-06. Validated against the Transformers reference at transcribe.cpp commit 483c122 on 2026-06-06. Streaming audio-LLM speech-to-text. A ~970M causal audio encoder (left-pad causal conv stem + 32-layer sliding-window RoPE transformer) feeds a 4-frame-group projector whose audio embeddings are added onto a ~3.4B Ministral decoder (26 layers, GQA 32/8, NEOX RoPE) with delay-token latency conditioning, emitting one text token per 80 ms audio slot (12.5 Hz). Takes a 16 kHz mono WAV and supports both incremental streaming (configurable latency/quality via --stream-chunk-ms and --stream-voxtral-delay) and offline transcription using an accuracy-first 2400 ms delay. Architecturally distinct from the offline Voxtral 2507 family — own arch, streaming frontend, causal encoder, additive audio fusion.
Input Audio→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗GGUF conversions of mistralai/Voxtral-Small-24B-2507 for use with transcribe.cpp. Ported from upstream commit da5b424, pinned 2026-06-05. Validated against the Transformers reference at transcribe.cpp commit dac22fa on 2026-06-05. Offline audio-LLM speech-to-text and speech translation. A Whisper-large-v3 bidirectional audio encoder feeds a 4-frame-group projector (375 audio tokens per 30 s chunk) into a Mistral-Small-24B causal LM (40 layers, GQA 32/8, NEOX RoPE, SwiGLU) via audio-token injection. Takes a 16 kHz mono WAV and produces a transcript via greedy decoding. The larger sibling of Voxtral Mini 3B — same encoder, projector, frontend, and tokenizer, with a scaled-up decoder.
Input Audio→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗Ported from upstream commit 911407f, pinned 2026-04-25. Validated against the transformers reference at transcribe.cpp commit 0a26478 on 2026-09-13. OpenAI Whisper base.en — converted to GGUF for transcribe.cpp. English-only; faster than the multilingual model at the same size. Encoder-decoder transformer; 30-second windows with chunked long-form decoding. 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.
Input Audio→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗Ported from upstream commit e37978b, pinned 2026-04-25. Validated against the transformers reference at transcribe.cpp commit 0a26478 on 2026-09-13. OpenAI Whisper base — converted to GGUF for transcribe.cpp. Multilingual transcription, language detection, and speech translation (audio in any supported language → English text). Encoder-decoder transformer; 30-second windows with chunked long-form decoding. 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.
Input Audio→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗GGUF conversions of openai/whisper-large for use with transcribe.cpp. Ported from upstream commit 4ef9b41, pinned 2026-04-25. Validated against the transformers reference at transcribe.cpp commit 0a26478 on 2026-09-13. OpenAI Whisper large — converted to GGUF for transcribe.cpp. Multilingual transcription, language detection, and speech translation (audio in any supported language → English text). Encoder-decoder transformer; 30-second windows with chunked long-form decoding.
Input Audio→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗GGUF conversions of openai/whisper-large-v2 for use with transcribe.cpp. Ported from upstream commit ae46427, pinned 2026-04-25. Validated against the transformers reference at transcribe.cpp commit 0a26478 on 2026-09-13. OpenAI Whisper large-v2 — converted to GGUF for transcribe.cpp. Multilingual transcription, language detection, and speech translation (audio in any supported language → English text). Encoder-decoder transformer; 30-second windows with chunked long-form decoding.
Input Audio→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗GGUF conversions of openai/whisper-large-v3 for use with transcribe.cpp. Ported from upstream commit 06f233f, pinned 2026-04-25. Validated against the transformers reference at transcribe.cpp commit 0a26478 on 2026-09-13. OpenAI Whisper large-v3 — converted to GGUF for transcribe.cpp. Multilingual transcription, language detection, and speech translation (audio in any supported language → English text). v3 family adds Cantonese (yue) and uses a 128-bin mel input. Encoder-decoder transformer; 30-second windows with chunked long-form decoding.
Input Audio→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗GGUF conversions of openai/whisper-large-v3-turbo for use with transcribe.cpp. Ported from upstream commit 41f01f3, pinned 2026-04-25. Validated against the transformers reference at transcribe.cpp commit 0a26478 on 2026-09-13. OpenAI Whisper large-v3-turbo — converted to GGUF for transcribe.cpp. Multilingual transcription and language detection; unlike the full large-v3 model, this turbo variant does not support speech translation. The v3 family adds Cantonese (yue) and uses a 128-bin mel input. Encoder-decoder transformer; 30-second windows with chunked long-form decoding.
Input Audio→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗Ported from upstream commit 2e98eb6, pinned 2026-04-25. Validated against the transformers reference at transcribe.cpp commit 0a26478 on 2026-09-13. OpenAI Whisper medium.en — converted to GGUF for transcribe.cpp. English-only; faster than the multilingual model at the same size. Encoder-decoder transformer; 30-second windows with chunked long-form decoding. 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.
Input Audio→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗GGUF conversions of openai/whisper-medium for use with transcribe.cpp. Ported from upstream commit abdf7c3, pinned 2026-04-25. Validated against the transformers reference at transcribe.cpp commit 0a26478 on 2026-09-13. OpenAI Whisper medium — converted to GGUF for transcribe.cpp. Multilingual transcription, language detection, and speech translation (audio in any supported language → English text). Encoder-decoder transformer; 30-second windows with chunked long-form decoding.
Input Audio→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗Ported from upstream commit e872752, pinned 2026-04-25. Validated against the transformers reference at transcribe.cpp commit 0a26478 on 2026-09-13. OpenAI Whisper small.en — converted to GGUF for transcribe.cpp. English-only; faster than the multilingual model at the same size. Encoder-decoder transformer; 30-second windows with chunked long-form decoding. 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.
Input Audio→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗