Index-Translate-Omni 9B

Built on the Index-Translate family, with multilingual text translation, terminology and formatting constraints, image translation, speech recognition, and bidirectional Chinese–English speech translation.

Text Translation

Model FLORES COMET22 ↑ WMT24++ COMET22 ↑ WMT26 Judge ↑ MEME ↑
Index-Translate 2B 0.8655 0.8489 60.26 0.6443
Index-Translate-Omni 2B 0.8655 0.8489 60.26 0.6443
Index-Translate 9B 0.8789 0.8601 75.35 0.7387
Index-Translate-Omni 9B 0.8789 0.8601 75.35 0.7387
Index-Translate 35BA3B (preview) 0.8794 0.8586 76.76 0.7405
Index-Translate-Omni 35BA3B 0.8795 0.8593 78.01 0.7405

Instruction Following

Model instTrans Quality / IFscore ↑ instTrans_minor Quality / IFscore ↑ / Off-target ↓ IFMTBench XCOMET-XXL / IFscore ↑
Index-Translate 2B 0.5391 / 0.7569 0.3050 / 0.6586 / 3.97% 0.7712 / 0.7584
Index-Translate-Omni 2B 0.5391 / 0.7569 0.3050 / 0.6586 / 3.97% 0.7712 / 0.7584
Index-Translate 9B 0.6771 / 0.8209 0.5222 / 0.7725 / 3.47% 0.7957 / 0.8760
Index-Translate-Omni 9B 0.6771 / 0.8209 0.5222 / 0.7725 / 3.47% 0.7957 / 0.8760
Index-Translate 35BA3B (preview) 0.6901 / 0.8336 0.5151 / 0.7715 / 4.05% 0.7926 / 0.8991
Index-Translate-Omni 35BA3B 0.6867 / 0.8371 0.5163 / 0.7843 / 3.62% 0.7934 / 0.9070

Original Index-Translate figures come from the published benchmarks. The original 35BA3B reference is the published preview checkpoint.

Speech

CER is a percentage (lower is better). BLEU and chrF2 are higher-is-better. Translation cells show BLEU / chrF2 / target CER.

Model Chinese ASR CER ↓ English ASR CER ↓ English β†’ Chinese Chinese β†’ English
Index-Translate-Omni 2B 13.8113 34.2560 36.982 / 30.357 / 43.3452 30.747 / 51.152 / 48.0670
Index-Translate-Omni 9B 17.8917 14.4097 43.507 / 36.312 / 41.3767 34.656 / 55.376 / 46.3720
Index-Translate-Omni 35BA3B 18.6803 15.0850 42.081 / 35.836 / 49.2490 36.404 / 57.323 / 45.1546

35BA3B uses a separate frontend for Chinese ASR; English ASR and speech translation use the native profile. Evaluation sample counts differ across model sizes.

Image Translation

COMET22 Γ— 100 (higher is better). Each Omni model is compared with its Qwen3.5 baseline on paired evaluated subsets.

Model MMTIT ↑ FLORES-rendered ↑ Vistra ↑
Qwen3.5-2B 52.164 50.187 55.326
Index-Translate-Omni 2B 65.809 53.612 65.596
Qwen3.5-9B 73.814 67.804 68.963
Index-Translate-Omni 9B 77.604 68.438 71.815
Qwen3.5-35B-A3B 75.602 70.005 71.067
Index-Translate-Omni 35BA3B 77.011 69.891 71.482

35BA3B reuses the verified image scores for the same weights. Results cover the evaluated subsets; the original failure and UNKNOWN scoring rules are retained.

Usage

See the native inference guide.

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