omi-health/omi-med-stt-v1-gguf

Model

Omi Med STT v1 GGUF

1

2 commits

2 linked in READMEs

updated Sep 3, 2026

See the code

README

Omi Med STT v1 GGUF

GGUF export of Omi Med STT v1 for Linux and Windows CPU use through the omi-med-stt CLI.

This is the portability path. If you have Apple Silicon, use the MLX q8 repo. If you have an NVIDIA GPU, use the canonical NeMo checkpoint.

Quickstart

pip install -U omi-med-stt
omi-med-stt install-cpp --cpp-backend cpu
omi-med-stt audio.wav --runtime cpp

Files

FileStatus
omi-med-stt-v1-q8_0.ggufDefault CPU artifact, benchmarked
omi-med-stt-v1-f16.ggufProvided for conversion/experimentation; not independently benchmarked

Evaluation

The public weights are unchanged. These September 2026 results come from the current documented runtime recipes on the same frozen 1,513-clip, 7.18-hour medical benchmark and scorer. No dictionary, custom vocabulary, contextual bias, reference-aware selection, or transcript correction was used.

Runtime artifactPlatformWERM-WERDrug M-WERMedical recall
NeMo canonicalNVIDIA CUDA (L4, BF16)6.54%2.23%4.75%97.77%
MLX q8Apple Silicon (M4 Max)6.65%2.12%4.52%97.88%
GGUF q8_0Linux/Windows CPU7.10%2.16%4.30%97.84%

The CPU path is the portable fallback. It recorded the lowest occurrence-based medical and drug error counts in this draw, but paired tests do not establish it as clinically better than GPU or MLX. Use CUDA for the best WER and throughput, or MLX q8 on Apple Silicon.

The previous model-card figures were produced by an older runtime/scorer path. The numbers above supersede them as runtime results; the GGUF weights did not change.

Compatibility

These files are not llama.cpp text-model GGUF files. They require a Parakeet ASR runtime. The supported path is:

omi-med-stt audio.wav --runtime cpp

The CLI installs the patched parakeet.cpp runtime needed for Omi Med STT v1.

Safety

Omi Med STT v1 is speech-to-text only. It is not a diagnostic, triage, prescribing, or clinical decision model, and it is not clinically validated. Transcripts must be reviewed before any clinical use.

automatic-speech-recognition
gguf
medical
omi-med-stt
parakeet
parakeet.cpp

omi-health/omi-med-stt-v1-gguf

Model

Omi Med STT v1 GGUF

1

2 commits

2 linked in READMEs

updated Sep 3, 2026

See the code

README

Omi Med STT v1 GGUF

GGUF export of Omi Med STT v1 for Linux and Windows CPU use through the omi-med-stt CLI.

This is the portability path. If you have Apple Silicon, use the MLX q8 repo. If you have an NVIDIA GPU, use the canonical NeMo checkpoint.

Quickstart

pip install -U omi-med-stt
omi-med-stt install-cpp --cpp-backend cpu
omi-med-stt audio.wav --runtime cpp

Files

FileStatus
omi-med-stt-v1-q8_0.ggufDefault CPU artifact, benchmarked
omi-med-stt-v1-f16.ggufProvided for conversion/experimentation; not independently benchmarked

Evaluation

The public weights are unchanged. These September 2026 results come from the current documented runtime recipes on the same frozen 1,513-clip, 7.18-hour medical benchmark and scorer. No dictionary, custom vocabulary, contextual bias, reference-aware selection, or transcript correction was used.

Runtime artifactPlatformWERM-WERDrug M-WERMedical recall
NeMo canonicalNVIDIA CUDA (L4, BF16)6.54%2.23%4.75%97.77%
MLX q8Apple Silicon (M4 Max)6.65%2.12%4.52%97.88%
GGUF q8_0Linux/Windows CPU7.10%2.16%4.30%97.84%

The CPU path is the portable fallback. It recorded the lowest occurrence-based medical and drug error counts in this draw, but paired tests do not establish it as clinically better than GPU or MLX. Use CUDA for the best WER and throughput, or MLX q8 on Apple Silicon.

The previous model-card figures were produced by an older runtime/scorer path. The numbers above supersede them as runtime results; the GGUF weights did not change.

Compatibility

These files are not llama.cpp text-model GGUF files. They require a Parakeet ASR runtime. The supported path is:

omi-med-stt audio.wav --runtime cpp

The CLI installs the patched parakeet.cpp runtime needed for Omi Med STT v1.

Safety

Omi Med STT v1 is speech-to-text only. It is not a diagnostic, triage, prescribing, or clinical decision model, and it is not clinically validated. Transcripts must be reviewed before any clinical use.

automatic-speech-recognition
gguf
medical
omi-med-stt
parakeet
parakeet.cpp