* qwen3_tts_talker_only pipeline (single terminal LLM_AR stage, final_output_type "latent") + vllm_omni/deploy/qwen3_tts_talker_only.yaml; a terminal talker publishes its per-step codes.audio rows to the client (omni_client_multimodal_output_keys). * /v1/audio/speech/stream: session.config.output_mode="codec_tokens" streams codec.start (JSON) + binary frames (<IHB seq/n_frames/flags + int16 rows, vllm_omni/entrypoints/openai/codec_stream.py) + codec.done; new input.cancel message aborts an in-flight generation for both codec and PCM sessions (single reader task + session inbox replaces direct socket reads); optional session.config.seed; audio.done gains "cancelled" only when it happened. * serving_speech._generate_codec_chunks aligns the cumulative code tensor to output token ids (drops prefill placeholder/EOS rows) and emits deltas. * TTS adapters: supports_codec_stream / codec_stream_spec (Qwen3-TTS: 16 codebooks, 2048 ids, 12.5 Hz, 24 kHz, decoder qwen3_tts_tokenizer_v2_12hz). * examples/online_serving/text_to_speech/qwen3_tts/edge_decoder_client.py decodes locally with Qwen3TTSTokenizerV2Decoder (ramp schedule, 72-frame context, cancel/reset), codec_parity_check.py and benchmarks/tts/codec_stream_e2e.py compare against the two-stage server. * docs/serving/codec_token_streaming.md; CPU unit tests for the wire format, alignment, session config and handler (frames, unsupported adapter, cancel); L3 e2e tests/e2e/online_serving/test_qwen3_tts_codec_stream.py. Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
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Codec-token streaming (on-device decoding)
For edge deployments the expensive part of a TTS pipeline that must run near the user is the audio decoder, while the autoregressive talker can stay on a server. Codec-token streaming serves the talker only and streams its codec frames to a client that decodes them locally (Qwen3-TTS: 16 codebooks at 12.5 Hz, about 400 B/s of payload before framing).
Server
Deploy the talker-only pipeline:
vllm serve Qwen/Qwen3-TTS-12Hz-0.6B-CustomVoice --omni --port 8001 \
--deploy-config qwen3_tts_talker_only.yaml --trust-remote-code
qwen3_tts_talker_only.yaml selects the registered qwen3_tts_talker_only
pipeline (stage 0 only, final_output_type: latent). The talker publishes its
per-step codes.audio rows to the client (omni_client_multimodal_output_keys),
and the WebSocket handler emits them as binary frames.
Protocol (/v1/audio/speech/stream)
Client → server: the usual session.config with
{"type": "session.config", "output_mode": "codec_tokens", "stream_audio": true,
"response_format": "pcm", "voice": "vivian", "task_type": "CustomVoice"}
then input.text / input.done. input.cancel aborts the in-flight
generation (works for PCM sessions too).
Server → client per utterance:
| message | content |
|---|---|
codec.start (JSON) |
codebooks, codebook_size, frame_rate_hz, sample_rate, decoder_id, header_format |
| binary frames | header <IHB = seq:uint32, n_frames:uint16, flags:uint8, then int16[n_frames × codebooks]; flags EOS=1, SEGMENT_END=2, RESET=4 |
codec.done (JSON) |
total_frames, seq_last, error, cancelled |
session.done |
as for PCM sessions |
Frames are emitted as they are produced (one talker step = one frame); the
chunking policy for the decoder (first small chunk, ramp to 25 frames, 72-frame
left context) is the client's choice. The wire format lives in
vllm_omni/entrypoints/openai/codec_stream.py.
Client
examples/online_serving/text_to_speech/qwen3_tts/edge_decoder_client.py
loads Qwen3TTSTokenizerV2Decoder from the checkpoint's speech_tokenizer/
folder (CPU or CUDA), applies the same chunk schedule and state carry-over as
the server's Code2Wav stage, writes a WAV and reports TTFA, playback-start
latency and RTF. codec_parity_check.py compares the client-decoded audio with
the full two-stage server's output (same tts_local_seed) and reports SNR.
Limits
- Only adapters with
supports_codec_stream = True(Qwen3-TTS today) acceptoutput_mode: codec_tokens; others return anerrormessage. - The talker's per-step output carries the cumulative code tensor, so a long utterance costs O(N²) bytes between engine and API server (about 9 MB for 30 s of audio); the wire stream itself is incremental.
word_timestampsandspeed != 1.0are not available in this mode.