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OpenMOSS-Team/MOSS-TTS-Realtime, runnable as a backbone + codec_lm + codec stack via stock llama.cpp and codec.cpp.MossTTSRealtimeLocalTransformer depth decoder + 17-channel emission (cb-0 = a text token sampled from the Qwen3 backbone's lm_head; cb-1..16 = 16 RVQ audio codebooks of 1027 entries each). codec.cpp's residual_depth_ar codec_lm runtime handles the depth decoder + audio embed tables + per-AR-step state machine; the backbone runs in llama.cpp as a stock qwen3 arch.codec_lm infrastructure (see tts_remaining_plan.md in codec.cpp).qwen3 arch — 28 layers, hidden 2048, vocab 151936)moss-tts-realtime-<quant>.gguf — produced by codec.cpp's convert-backbone-to-gguf.py prep_moss_tts_realtime, which unwraps language_model.* into the standard Qwen3 layout. tie_word_embeddings=true is inferred from the absence of a standalone lm_head tensor.| File | Size |
|---|---|
moss-tts-realtime-f32.gguf | 4.5 GB |
moss-tts-realtime-f16.gguf | 3.3 GB |
moss-tts-realtime-bf16.gguf | 3.3 GB |
moss-tts-realtime-q8_0.gguf | 1.8 GB |
moss-tts-realtime-q6_k.gguf | 1.4 GB |
moss-tts-realtime-q5_1.gguf | 1.3 GB |
moss-tts-realtime-q5_k_m.gguf | 1.2 GB |
moss-tts-realtime-q5_k_s.gguf | 1.2 GB |
moss-tts-realtime-q5_0.gguf | 1.2 GB |
moss-tts-realtime-q4_1.gguf | 1.1 GB |
moss-tts-realtime-q4_k_m.gguf | 1.1 GB |
moss-tts-realtime-q4_k_s.gguf | 1009 MB |
moss-tts-realtime-q4_0.gguf | 1004 MB |
moss-tts-realtime-q3_k_l.gguf | 955 MB |
moss-tts-realtime-q3_k_m.gguf | 894 MB |
moss-tts-realtime-q3_k_s.gguf | 825 MB |
moss-tts-realtime-q2_k.gguf | 740 MB |
residual_depth_ar adaptor)codec[-<quant>].gguf — full MOSS-Audio-Tokenizer (1.6B, 24 kHz mono) bundled with the codec_lm adaptor: audio embed tables for the 16 RVQ heads, the 17th text_embd (~308 MB at F16), 4-layer depth decoder, and 16 codebooks_head slices. Produced by codec.cpp's convert-to-gguf.py --model-type moss_audio --lm-source OpenMOSS-Team/MOSS-TTS-Realtime.| File | Size |
|---|---|
codec-f32.gguf | 6.1 GB |
codec-f16.gguf | 3.9 GB |
codec-q8_0.gguf | 2.4 GB |
codec-q5_k_m.gguf | 1.8 GB |
codec-q4_k_m.gguf | 1.6 GB |
backbone (Qwen3, embeddings=true) hidden state h
→ caller samples text token via llama_get_logits_ith → text_tok
→ codec_lm_state_set_text_context(state, text_tok)
→ codec_lm_step_begin(state, h)
→ for cb in 0..16: codec_lm_step_logits → sample → codec_lm_step_push_code
→ codec_lm_step_finish → codes[17]
→ codec_lm_compose_audio_embd(codes) → next-step embedding
→ feed to backbone via b.embd; loop until codes[0] == EOS_textcodec_decode to get 24 kHz mono PCM.OpenMOSS-Team/MOSS-TTS-RealtimeOpenMOSS-Team/MOSS-Audio-Tokenizermybigday/codec.cppmybigday/llama.rn (codec_lm AR text-modality path in cpp/rn-tts.cpp)