Qwen3 TTS Developer Pack Overview#

Included runtime#

The Qwen3 TTS pack contains:

  • Signed Production and functional Release Qwen3 TTS plugins for CUDA, Vulkan, and D3D12.

  • nvigi.tts.qwen.exe command-line sample and nvigi.3d.exe 3D sample.

  • Qwen3 0.6B Base Talker assets (Q4_K_M default and optional Q8_0) and the shared tokenizer/codec (F32) GGUF asset.

  • An opt-in provisioning script that downloads Qwen’s hosted example WAV and creates a reusable voice JSON locally; neither artifact is bundled.

  • Qwen-specific source, public headers, symbols, and HTML documentation.

NVIGI Core/HWI is installed by setup_sample.bat from the public NVIGI Core 1.6.1 runtime. It is not duplicated in the initial package payload.

Model layout#

Item

Location

Purpose

Q4_K_M model

data\nvigi.models\nvigi.plugin.tts.qwen3\{96F1AC08-B98E-41B0-B8E4-D8DC446CF868}

Q4_K_M Talker, F32 codec, and model metadata

Q8_0 model

data\nvigi.models\nvigi.plugin.tts.qwen3\{A7D3620F-ADDB-4200-8EB4-3A5E270846CB}

Q8_0 Talker, F32 codec, and model metadata

Q4_K_M is the default model GUID. Q8_0 is selected with its distinct GUID; it uses more disk/VRAM and can be slower. Each GUID directory is a complete NVIGI model containing one Talker, the shared F32 codec payload, and independent discovery metadata.

Runtime API#

The public API is in include\nvigi_tts_qwen3.h. A host selects one of the CUDA, Vulkan, or D3D12 Qwen plugin IDs, creates an inference instance with the model root, and submits a Qwen prompt data slot.

For voice cloning, provide either:

  • A precomputed JSON decoded into refSpkEmb and optional ICL refCodes, or

  • A source WAV through refAudioPath.

The programming guide describes the exact structures and lifetime rules.

Samples and source#

Sample

Binary

Source

CLI

bin\x64\Release\nvigi.tts.qwen.exe

source\samples\nvigi.tts.qwen\

3D UI

bin\x64\Release\nvigi.3d.exe

source\samples\nvigi.3d\

The 3D sample supports Qwen TTS directly. Full ASR -> GPT -> TTS applications are integration scenarios using a separately provisioned NVIGI Developer SDK.

Seed-TTS English quality and performance#

The following baselines were measured with an NVIDIA GeForce RTX 4090 and driver 610.88. It uses the English Seed-TTS evaluation set, with each request conditioned on its corresponding reference WAV and reference transcript through Qwen Base Mode B voice cloning.

Each run used the shipped Q4_K_M v0 Talker and F32 codec, random sampling (seed = -1), Talker and Code Predictor temperature 0.9, a 768-frame generation limit, and a 40-word chunk limit. The model was loaded once per backend and reused for the full batch.

Quality#

Metric

Result

English macro WER

2.008%

Mean speaker similarity (SIM)

0.6748

Median speaker similarity (SIM)

0.6825

Metric

Result

English macro WER

2.094%

Mean speaker similarity (SIM)

0.6742

Median speaker similarity (SIM)

0.6813

Metric

Result

English macro WER

2.099%

Mean speaker similarity (SIM)

0.6718

Median speaker similarity (SIM)

0.6804

WER uses Whisper Large V3 with the official Seed-TTS English normalization and unweighted per-utterance averaging. SIM is the cosine similarity between the official WavLM-large/ECAPA speaker embeddings of each generated WAV and its reference WAV.

Performance#

Measurement

Mean

Median

P95

Time to first codec frame (TTFA)

164.0 ms

158.8 ms

226.0 ms

Engine-reported full inference

465.4 ms

457.6 ms

635.2 ms

Real-time factor (RTF)

0.112

0.109

0.141

Aggregate throughput was 9.16x real time. The complete Seed-TTS generation pass, including one-time model/framework startup and all requests, took 533.6 seconds.

Measurement

Mean

Median

P95

Time to first codec frame (TTFA)

253.4 ms

238.7 ms

370.3 ms

Engine-reported full inference

812.7 ms

797.8 ms

1,117.2 ms

Real-time factor (RTF)

0.197

0.191

0.248

Aggregate throughput was 5.21x real time. The complete Seed-TTS generation pass, including one-time model/framework startup and all requests, took 948.2 seconds.

Measurement

Mean

Median

P95

Time to first codec frame (TTFA)

180.6 ms

177.0 ms

247.9 ms

Engine-reported full inference

570.8 ms

561.3 ms

779.7 ms

Real-time factor (RTF)

0.137

0.134

0.170

Aggregate throughput was 7.47x real time. The complete Seed-TTS generation pass, including one-time model/framework startup and all requests, took 646.6 seconds.

TTFA is measured to the first generated codec-frame codes, not to the first streamed PCM callback. Per-request inference measurements exclude one-time model loading.

Because seed = -1 selects a new random seed, this is a measured single-run baseline rather than a deterministic performance or quality guarantee. These figures are NVIDIA-measured baselines; the evaluator is not included in this package. The WER and speaker-similarity methodology follows ByteDance’s Seed-TTS evaluator at revision 752f4297f090c46bb1a55a1f7439e5944ddefe8d. Results may vary with hardware, software, model, and sampling conditions.

Documentation#