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diff --git a/makima/src/tts/qwen3/config.rs b/makima/src/tts/qwen3/config.rs
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+++ b/makima/src/tts/qwen3/config.rs
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+//! Qwen3-TTS model configuration.
+//!
+//! Parses config.json from the HuggingFace model repository to configure
+//! the language model, code predictor, and speech tokenizer.
+
+use serde::Deserialize;
+
+use crate::tts::TtsError;
+
+/// Top-level configuration for Qwen3-TTS-12Hz-0.6B-Base.
+#[derive(Debug, Clone, Deserialize)]
+pub struct Qwen3TtsConfig {
+    /// Language model (talker) configuration.
+    #[serde(default = "Qwen3LmConfig::default")]
+    pub lm: Qwen3LmConfig,
+
+    /// Code predictor (multi-token prediction) configuration.
+    #[serde(default = "CodePredictorConfig::default")]
+    pub code_predictor: CodePredictorConfig,
+
+    /// Speech tokenizer configuration.
+    #[serde(default = "SpeechTokenizerConfig::default")]
+    pub speech_tokenizer: SpeechTokenizerConfig,
+}
+
+impl Default for Qwen3TtsConfig {
+    fn default() -> Self {
+        Self {
+            lm: Qwen3LmConfig::default(),
+            code_predictor: CodePredictorConfig::default(),
+            speech_tokenizer: SpeechTokenizerConfig::default(),
+        }
+    }
+}
+
+impl Qwen3TtsConfig {
+    /// Load from a config.json file path.
+    pub fn from_json_path(path: &std::path::Path) -> Result<Self, TtsError> {
+        let content = std::fs::read_to_string(path)
+            .map_err(|e| TtsError::Config(format!("failed to read config: {e}")))?;
+        Self::from_json_str(&content)
+    }
+
+    /// Load from a JSON string.
+    pub fn from_json_str(json: &str) -> Result<Self, TtsError> {
+        // Try to parse the full HuggingFace config.json format first
+        if let Ok(hf_config) = serde_json::from_str::<HfConfig>(json) {
+            return Ok(Self::from_hf_config(&hf_config));
+        }
+        // Fall back to direct deserialization
+        serde_json::from_str(json)
+            .map_err(|e| TtsError::Config(format!("failed to parse config: {e}")))
+    }
+
+    /// Convert from HuggingFace's config.json format.
+    fn from_hf_config(hf: &HfConfig) -> Self {
+        Self {
+            lm: Qwen3LmConfig {
+                hidden_size: hf.hidden_size.unwrap_or(1024),
+                num_hidden_layers: hf.num_hidden_layers.unwrap_or(28),
+                num_attention_heads: hf.num_attention_heads.unwrap_or(16),
+                num_key_value_heads: hf.num_key_value_heads.unwrap_or(8),
+                intermediate_size: hf.intermediate_size.unwrap_or(3072),
+                head_dim: hf.head_dim.unwrap_or(128),
+                vocab_size: hf.vocab_size.unwrap_or(151_936),
+                max_position_embeddings: hf.max_position_embeddings.unwrap_or(32_768),
+                rms_norm_eps: hf.rms_norm_eps.unwrap_or(1e-6),
+                rope_theta: hf.rope_theta.unwrap_or(1_000_000.0),
+                use_sliding_window: hf.use_sliding_window.unwrap_or(false),
+                sliding_window: hf.sliding_window,
+                hidden_act: hf.hidden_act.clone().unwrap_or_else(|| "silu".to_string()),
+            },
+            code_predictor: CodePredictorConfig {
+                hidden_size: hf.code_predictor_hidden_size.unwrap_or(1024),
+                num_layers: hf.code_predictor_num_layers.unwrap_or(5),
+                num_attention_heads: hf
+                    .code_predictor_num_attention_heads
+                    .unwrap_or(16),
+                num_code_groups: hf.num_code_groups.unwrap_or(16),
+                codebook_vocab_size: hf.codebook_vocab_size.unwrap_or(2048),
+                rms_norm_eps: hf.rms_norm_eps.unwrap_or(1e-6),
+            },
+            speech_tokenizer: SpeechTokenizerConfig::default(),
+        }
+    }
+}
+
+/// Language model configuration (28-layer Qwen3 transformer).
+#[derive(Debug, Clone, Deserialize)]
+pub struct Qwen3LmConfig {
+    /// Hidden dimension of transformer layers.
+    pub hidden_size: usize,
+    /// Number of transformer layers.
+    pub num_hidden_layers: usize,
+    /// Number of attention heads.
+    pub num_attention_heads: usize,
+    /// Number of key-value heads (GQA).
+    pub num_key_value_heads: usize,
+    /// Feed-forward intermediate size.
+    pub intermediate_size: usize,
+    /// Dimension per attention head.
+    pub head_dim: usize,
+    /// Text vocabulary size.
+    pub vocab_size: usize,
+    /// Maximum sequence length for RoPE.
+    pub max_position_embeddings: usize,
+    /// RMS normalization epsilon.
+    pub rms_norm_eps: f64,
+    /// RoPE theta parameter.
+    pub rope_theta: f64,
+    /// Whether to use sliding window attention.
+    pub use_sliding_window: bool,
+    /// Sliding window size (if enabled).
+    pub sliding_window: Option<usize>,
+    /// Activation function name.
+    pub hidden_act: String,
+}
+
+impl Default for Qwen3LmConfig {
+    fn default() -> Self {
+        Self {
+            hidden_size: 1024,
+            num_hidden_layers: 28,
+            num_attention_heads: 16,
+            num_key_value_heads: 8,
+            intermediate_size: 3072,
+            head_dim: 128,
+            vocab_size: 151_936,
+            max_position_embeddings: 32_768,
+            rms_norm_eps: 1e-6,
+            rope_theta: 1_000_000.0,
+            use_sliding_window: false,
+            sliding_window: None,
+            hidden_act: "silu".to_string(),
+        }
+    }
+}
+
+impl Qwen3LmConfig {
+    /// Number of key-value head groups for GQA.
+    pub fn num_kv_groups(&self) -> usize {
+        self.num_attention_heads / self.num_key_value_heads
+    }
+}
+
+/// Code predictor (multi-token prediction) configuration.
+#[derive(Debug, Clone, Deserialize)]
+pub struct CodePredictorConfig {
+    /// Hidden size (matches LM hidden size).
+    pub hidden_size: usize,
+    /// Number of predictor transformer layers.
+    pub num_layers: usize,
+    /// Number of attention heads.
+    pub num_attention_heads: usize,
+    /// Number of codebook groups (residual codebooks).
+    pub num_code_groups: usize,
+    /// Vocabulary size per codebook.
+    pub codebook_vocab_size: usize,
+    /// RMS norm epsilon.
+    pub rms_norm_eps: f64,
+}
+
+impl Default for CodePredictorConfig {
+    fn default() -> Self {
+        Self {
+            hidden_size: 1024,
+            num_layers: 5,
+            num_attention_heads: 16,
+            num_code_groups: 16,
+            codebook_vocab_size: 2048,
+            rms_norm_eps: 1e-6,
+        }
+    }
+}
+
+/// Speech tokenizer (ConvNet codec) configuration.
+#[derive(Debug, Clone, Deserialize)]
+pub struct SpeechTokenizerConfig {
+    /// Number of RVQ codebooks.
+    pub num_codebooks: usize,
+    /// Codebook embedding dimension.
+    pub codebook_dim: usize,
+    /// Codebook vocabulary size per layer.
+    pub codebook_size: usize,
+    /// Encoder/decoder hidden channels.
+    pub hidden_channels: usize,
+    /// Output sample rate.
+    pub sample_rate: u32,
+    /// Token frame rate (Hz).
+    pub frame_rate: f32,
+    /// HuggingFace model ID for the speech tokenizer.
+    pub model_id: String,
+}
+
+impl Default for SpeechTokenizerConfig {
+    fn default() -> Self {
+        Self {
+            num_codebooks: 16,
+            codebook_dim: 256,
+            codebook_size: 2048,
+            hidden_channels: 512,
+            sample_rate: 24_000,
+            frame_rate: 12.5,
+            model_id: "Qwen/Qwen3-TTS-Tokenizer-12Hz".to_string(),
+        }
+    }
+}
+
+/// HuggingFace config.json format (partial, fields we need).
+#[derive(Debug, Deserialize)]
+struct HfConfig {
+    hidden_size: Option<usize>,
+    num_hidden_layers: Option<usize>,
+    num_attention_heads: Option<usize>,
+    num_key_value_heads: Option<usize>,
+    intermediate_size: Option<usize>,
+    head_dim: Option<usize>,
+    vocab_size: Option<usize>,
+    max_position_embeddings: Option<usize>,
+    rms_norm_eps: Option<f64>,
+    rope_theta: Option<f64>,
+    use_sliding_window: Option<bool>,
+    sliding_window: Option<usize>,
+    hidden_act: Option<String>,
+    // Code predictor specific fields
+    code_predictor_hidden_size: Option<usize>,
+    code_predictor_num_layers: Option<usize>,
+    code_predictor_num_attention_heads: Option<usize>,
+    num_code_groups: Option<usize>,
+    codebook_vocab_size: Option<usize>,
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+
+    #[test]
+    fn test_default_config() {
+        let config = Qwen3TtsConfig::default();
+        assert_eq!(config.lm.hidden_size, 1024);
+        assert_eq!(config.lm.num_hidden_layers, 28);
+        assert_eq!(config.lm.num_attention_heads, 16);
+        assert_eq!(config.lm.num_key_value_heads, 8);
+        assert_eq!(config.lm.head_dim, 128);
+        assert_eq!(config.lm.num_kv_groups(), 2);
+        assert_eq!(config.code_predictor.num_layers, 5);
+        assert_eq!(config.code_predictor.num_code_groups, 16);
+        assert_eq!(config.speech_tokenizer.num_codebooks, 16);
+    }
+
+    #[test]
+    fn test_config_from_json() {
+        let json = r#"{
+            "hidden_size": 1024,
+            "num_hidden_layers": 28,
+            "num_attention_heads": 16,
+            "num_key_value_heads": 8,
+            "intermediate_size": 3072,
+            "vocab_size": 151936,
+            "max_position_embeddings": 32768,
+            "rms_norm_eps": 1e-6,
+            "rope_theta": 1000000.0,
+            "hidden_act": "silu"
+        }"#;
+
+        let config = Qwen3TtsConfig::from_json_str(json).unwrap();
+        assert_eq!(config.lm.hidden_size, 1024);
+        assert_eq!(config.lm.num_hidden_layers, 28);
+        assert_eq!(config.lm.vocab_size, 151_936);
+    }
+}