Text-to-speech (TTS) technology has seen rapid advancements, evolving from robotic voices to lifelike AI-generated speech. In 2025, two of the leading open-source models are Nari Dia 1.6B and Sesame CSM 1B.

Both offer impressive capabilities in realistic speech synthesis, but they cater to different use cases and offer distinct strengths.

Overview of the Models

Nari Dia 1.6B

• Developer: Nari Labs
• Parameters: 1.6 billion
• Focus: Expressive, dialogue-driven speech with nonverbal cues
• Language Support: English only
• License: Apache 2.0 (open source)
• Key Strengths: Emotion control, nonverbal sound generation, voice cloning, full offline support

Sesame CSM 1B

• Developer: Sesame AI Labs
• Parameters: 1 billion
• Focus: Real-time, context-aware conversational speech
• Language Support: English (primary)
• License: Open source
• Key Strengths: Low-latency performance, multimodal learning, seamless context integration

Technical Architecture

Key Features and Innovations

Nari Dia 1.6B

• Expressive Dialogue Generation: Optimized for natural back-and-forth exchanges using speaker tags.
• Emotion and Tone Control: Users can guide intonation and style using audio prompts.
• Nonverbal Sound Synthesis: Generates authentic nonverbal cues like laughter or coughing from text.
• Voice Cloning: Supports imitation of speaker characteristics via sample conditioning.
• Offline Operation: Can run locally for maximum privacy and data security.
• Community and Openness: Apache 2.0 licensed with active developer support and open-source code.

Sesame CSM 1B

• Multimodal Input: Processes both text and audio in a unified architecture.
• Conversational Context Awareness: Tracks speaker turns and dialogue flow using context segments.
• Real-Time Output: Engineered for interactive, low-latency applications.
• Flexible Style Transfer: Voice, tone, and flow can be influenced using previous utterances.
• Accessible for Developers: CPU-compatible for lightweight workloads; hosted models on Hugging Face.

Installation and Hardware Requirements

Nari Dia 1.6B

• GPU: NVIDIA GPU with ≥10GB VRAM (e.g., RTX 3070/4070)
• OS: Linux preferred; Windows compatible
• Dependencies: Python 3.8+, PyTorch 2.0+, CUDA 12.6, uv recommended
• Setup: GitHub repo → virtual environment → install deps → run UI or script
• CPU Support: Planned for future
• Demo: Hugging Face ZeroGPU Space available

Sesame CSM 1B

• GPU (Optional): Recommended for real-time; CPU support available
• OS: Linux recommended
• Dependencies: Python 3.10+, PyTorch, torchaudio
• Setup: GitHub repo → virtual environment → install deps → Hugging Face CLI for model access
• Advanced Features: Requires scripting for context segments

Performance and Output Quality

Naturalness and Expressiveness

• Nari Dia 1.6B delivers highly expressive, realistic dialogue, with superior emotional inflection and timing. Outperforms many competitors in natural delivery.
• Sesame CSM 1B shines in fluid, context-driven conversations. Adapts dynamically to conversation history for lifelike exchanges.

Speaker Consistency and Cloning

• Dia 1.6B: Uses audio prompts and random seed control for consistent voices.
• CSM 1B: Maintains speaker identity through context history and previous audio inputs.

Nonverbal Sound Handling

• Dia 1.6B: Generates expressive sounds from written cues like (laughs) or (clears throat).
• CSM 1B: Mimics such sounds only via contextual scripting.

Latency and Interactivity

• Dia 1.6B: Fast generation on GPUs, but lacks CPU optimization for now.
• CSM 1B: Built for low-latency, real-time output, including CPU fallback.

Customization, Privacy, and Ecosystem

Customization

• Dia 1.6B: Fully open, supports fine-tuning for new voices or domains.
• CSM 1B: Modular and adaptable via structured context; less direct for voice cloning.

Privacy and Control

• Dia 1.6B: Ideal for privacy-first environments with local-only processing.
• CSM 1B: Supports local deployment but shines in connected, dynamic settings.

Community Support

• Dia 1.6B: Developer Discord, open demos, and detailed documentation.
• CSM 1B: Hugging Face-hosted models, GitHub discussions, and research-friendly tools.

Use Cases and Applications

Best Use Cases for Nari Dia 1.6B

• Audiobooks, podcasts, YouTube narration
• Conversational AI with expressive delivery
• Voiceover for privacy-sensitive environments
• Offline TTS deployment

Best Use Cases for Sesame CSM 1B

• Real-time AI assistants and customer service bots
• Educational apps and interactive simulations
• Low-latency voice interfaces
• Multimodal speech research and prototyping

Strengths and Weaknesses

Direct Comparison Summary

Which Should You Choose?

Choose Nari Dia 1.6B if:

• You need high-fidelity, emotionally expressive voice output.
• Your content benefits from nonverbal expressions like laughter or sighs.
• You require strict data privacy and offline deployment.
• You have a compatible GPU and plan to fine-tune or experiment.

Choose Sesame CSM 1B if:

• You’re building real-time, interactive speech applications.
• You need dynamic conversational adaptation based on dialogue history.
• You're developing on CPU-constrained devices or prefer fast prototyping.
• You’re exploring multimodal AI or educational simulations.

Final Thoughts

Both Nari Dia 1.6B and Sesame CSM 1B push the boundaries of open-source TTS in 2025. Whether you prioritize realism and privacy (Dia), or real-time adaptability and contextual flow (CSM), each model offers unique advantages.

Experiment with both to find which aligns best with your workflow, audience, and creative vision.