Choose the model, checkpoint format, and runtime separately. A model listed here is not automatically supported by every server or export backend.

Start by task

Task	Model family	Important boundary
Context-aware file transcription	Fun-ASR-Nano	The base checkpoint and native vLLM-converted checkpoint are different artifacts.
Broader multilingual file transcription	Fun-ASR-MLT-Nano	Separate checkpoint; do not attribute its language coverage to the base Nano model.
Transcription with emotion and audio-event tags	SenseVoiceSmall	Tags are model outputs, not speaker identity. Speaker-aware pipelines need the documented companion components.
Mandarin transcription with timestamps	Paraformer	Offline and streaming checkpoints have different inference contracts.
Offline text, timestamps and anonymous speakers together	MOSS-Transcribe-Diarize	Third-party OpenMOSS model; no external VAD or speaker model is needed for its unified path. Not known-person identification.

Use the selection guide for workload choices, the SDK contract for parameters and return values, and the deployment matrix for serving options.

Model Usage

Start with the installation guide and Python tutorial. Use an explicit hub and record the resolved checkpoint/revision, FunASR version, device and inference options. Aliases are resolved by the repository mapping; an alias is convenient, but is not an immutable model revision.

from funasr import AutoModel

model = AutoModel(model="paraformer-zh", hub="ms", device="cpu")
result = model.generate(input="meeting.wav")
print(result[0]["text"])

Replace meeting.wav with an existing recording. Download time, warmup and inference are separate measurements. Preserve the raw result when validating timestamps, speaker labels or model-specific tags.

Speech Recognition

Paraformer

SDK alias	Intended use	ModelScope (`hub="ms"`)	Hugging Face (`hub="hf"`)
`paraformer-zh`	Offline Mandarin transcription; ModelScope alias selects SeACo	SeACo checkpoint	Checkpoint
`paraformer-zh-streaming`	Chunked streaming with per-session cache	Checkpoint	Checkpoint
`paraformer-en`	Offline English transcription	Resolve through the hub mapping.	Resolve through the hub mapping.

The legacy Paraformer VAD/punctuation pipeline and paraformer-zh-spk listing describe pipelines, not the paraformer-zh alias target. For explicit composition, use vad_model, punc_model and spk_model as documented in the SDK guide, rather than treating all components as one interchangeable ASR checkpoint.

Pipeline components

Component	Alias	Model cards	What it does not do
Voice activity detection	`fsmn-vad`	ModelScope / HF	Does not transcribe speech or identify a speaker.
Punctuation restoration	`ct-punc`	ModelScope / HF	Does not create acoustic timestamps.
Speaker embeddings	`cam++`	Hub mapping	Does not name known people without a separately designed enrollment/matching system.
Timestamp prediction	`fa-zh`	Hub mapping	Must match the documented input/model path; not universal timestamp support for every recognizer.

See the full ModelScope inventory and Hugging Face inventory for additional checkpoints. These inventories include historical variants; verify each model card before using a checkpoint in a new service.

Third-party Unified Transcription and Diarization

MOSS-Transcribe-Diarize is published by OpenMOSS, not by the FunASR team. Its unified offline output includes text, timestamps and anonymous speaker labels scoped to a recording. It is not a realtime streaming or known-person identification model. Use the MOSS guide for the adapter, native upstream servers, memory requirements and response boundaries.

Model License

The FunASR software license does not grant one license for every model weight. Consult the individual checkpoint's model card/license, publisher, training-data notes and the applicable Model License Agreement. Keep upstream attribution when redistributing models or derived artifacts.

Validation and next steps

Train or fine-tune a supported recipe.
Register a custom model.
Choose native vLLM or split-engine; preserve their distinct artifacts and API contracts.
Deploy GGUF models with llama.cpp; an ONNX export is not a GGUF conversion.
Measure quality and runtime separately, using representative audio and exact versions.