--- title: "dc_tts vs Kokoro-FastAPI" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/kyubyong-dc-tts-vs-remsky-kokoro-fastapi" tools: ["kyubyong-dc-tts", "remsky-kokoro-fastapi"] --- # dc_tts vs Kokoro-FastAPI *GraphCanon updated Jul 30, 2026* ## Verdict Pick dc_tts if dc_tts is a text-to-speech model based on TensorFlow and requires specific version dependencies; pick Kokoro-FastAPI if kokoro-FastAPI is a Dockerized wrapper for the Kokoro-82M text-to-speech model using FastAPI. It supports multi-language capability and provides prebuilt images for various hardware types. [dc_tts](https://github.com/Kyubyong/dc_tts) reports 1.2k GitHub stars, 360 forks, and 68 open issues, last pushed Apr 14, 2023. [Kokoro-FastAPI](https://github.com/remsky/Kokoro-FastAPI) has 5.3k stars, 858 forks, and 109 open issues, last pushed Jul 21, 2026. Figures are from public GitHub metadata via [dc_tts's repository](https://github.com/Kyubyong/dc_tts) and [Kokoro-FastAPI's repository](https://github.com/remsky/Kokoro-FastAPI). | | [dc_tts](/tools/kyubyong-dc-tts.md) | [Kokoro-FastAPI](/tools/remsky-kokoro-fastapi.md) | | --- | --- | --- | | Tagline | A TensorFlow Implementation of DC-TTS | Dockerized FastAPI wrapper for Kokoro-82M text-to-speech model | | Stars | 1,156 | 5,265 | | Forks | 360 | 858 | | Open issues | 68 | 109 | | Language | Python | Python | | Adopt for | dc_tts is a text-to-speech model based on TensorFlow and requires specific version dependencies. | Kokoro-FastAPI is a Dockerized wrapper for the Kokoro-82M text-to-speech model using FastAPI. It supports multi-language capability and provides prebuilt images for various hardware types. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | Apache-2.0 | | Categories | Speech & Audio | Speech & Audio | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [dc_tts](/tools/kyubyong-dc-tts.md) | [Kokoro-FastAPI](/tools/remsky-kokoro-fastapi.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Active (82%) | | Days since push | 1203d | 8d | | Open issues (now) | 68 | 109 | | Full report | [trust report](/tools/kyubyong-dc-tts/trust.md) | [trust report](/tools/remsky-kokoro-fastapi/trust.md) | ## Decision facts: dc_tts - **Requirements:** Depends on TensorFlow >=1.3 and has compatibility issues with updated APIs for `tf.contrib.layers.layer_norm`.; Requires Python packages like NumPy, librosa, tqdm, matplotlib, and scipy. - **Adopt for:** dc_tts is a text-to-speech model based on TensorFlow and requires specific version dependencies. ## Decision facts: Kokoro-FastAPI - **Requirements:** Min 4 GB RAM; Requires Docker; Hardware-specific Docker images are provided for CUDA, ROCm (experimental), and CPU support.; Users without supported GPUs can still utilize the service via a CPU image. - **Adopt for:** Kokoro-FastAPI is a Dockerized wrapper for the Kokoro-82M text-to-speech model using FastAPI. It supports multi-language capability and provides prebuilt images for various hardware types. ## Choose when ### Choose dc_tts if… - Requirements: Depends on TensorFlow >=1.3 and has compatibility issues with updated APIs for `tf.contrib.layers.layer_norm`.; Requires Python packages like NumPy, librosa, tqdm, matplotlib, and scipy.. - Tags unique to dc_tts: speech, speech-to-text, tensorflow, tts. - dc_tts is a text-to-speech model based on TensorFlow and requires specific version dependencies. ### Choose Kokoro-FastAPI if… - Requirements: Min 4 GB RAM; Requires Docker; Hardware-specific Docker images are provided for CUDA, ROCm (experimental), and CPU support.; Users without supported GPUs can still utilize the service via a CPU image.. - Tags unique to Kokoro-FastAPI: docker, fastapi, kokoro tts, multi-gpu support. - You require a solution that can auto-download models and run natively on Apple Silicon (MPS) with support via UV. ## When NOT to use dc_tts - Last GitHub push was 1229 days ago (dormant maintenance, Apr 14, 2023). Validate activity before betting a new project on dc_tts. ## When NOT to use Kokoro-FastAPI - If your hardware is not supported by the provided Docker images, for example, if you do not have a compatible NVIDIA, AMD GPU or CPU setup. - You are looking for non-Dockerized solutions. Kokoro-FastAPI focuses on containerization and might not fit environments that strictly avoid containers. ## Common questions ### What is the difference between dc_tts and Kokoro-FastAPI? dc_tts: A TensorFlow Implementation of DC-TTS. Kokoro-FastAPI: Dockerized FastAPI wrapper for Kokoro-82M text-to-speech model. See the comparison table for live GitHub stats and shared categories. ### When should I choose dc_tts over Kokoro-FastAPI? Choose dc_tts over Kokoro-FastAPI when Requirements: Depends on TensorFlow >=1.3 and has compatibility issues with updated APIs for `tf.contrib.layers.layer_norm`.; Requires Python packages like NumPy, librosa, tqdm, matplotlib, and scipy.; Tags unique to dc_tts: speech, speech-to-text, tensorflow, tts; dc_tts is a text-to-speech model based on TensorFlow and requires specific version dependencies. ### When should I choose Kokoro-FastAPI over dc_tts? Choose Kokoro-FastAPI over dc_tts when Requirements: Min 4 GB RAM; Requires Docker; Hardware-specific Docker images are provided for CUDA, ROCm (experimental), and CPU support.; Users without supported GPUs can still utilize the service via a CPU image.; Tags unique to Kokoro-FastAPI: docker, fastapi, kokoro tts, multi-gpu support; You require a solution that can auto-download models and run natively on Apple Silicon (MPS) with support via UV. ### When should I avoid dc_tts? Last GitHub push was 1229 days ago (dormant maintenance, Apr 14, 2023). Validate activity before betting a new project on dc_tts. ### When should I avoid Kokoro-FastAPI? If your hardware is not supported by the provided Docker images, for example, if you do not have a compatible NVIDIA, AMD GPU or CPU setup. You are looking for non-Dockerized solutions. Kokoro-FastAPI focuses on containerization and might not fit environments that strictly avoid containers. ### Is dc_tts or Kokoro-FastAPI more popular on GitHub? Kokoro-FastAPI has more GitHub stars (5,265 vs 1,156). Stars measure visibility, not whether either tool fits your constraints. ### Are dc_tts and Kokoro-FastAPI open source? Yes - both are open-source projects on GitHub (dc_tts: Apache-2.0, Kokoro-FastAPI: Apache-2.0). ### Where can I find alternatives to dc_tts or Kokoro-FastAPI? GraphCanon lists graph-backed alternatives at [dc_tts alternatives](/tools/kyubyong-dc-tts/alternatives) and [Kokoro-FastAPI alternatives](/tools/remsky-kokoro-fastapi/alternatives) ([dc_tts markdown twin](/tools/kyubyong-dc-tts/alternatives.md), [Kokoro-FastAPI markdown twin](/tools/remsky-kokoro-fastapi/alternatives.md)), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at [this comparison](/compare/kyubyong-dc-tts-vs-remsky-kokoro-fastapi.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, dc_tts or Kokoro-FastAPI? dc_tts: Dormant. Kokoro-FastAPI: Active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for dc_tts and Kokoro-FastAPI? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [dc_tts trust report](/tools/kyubyong-dc-tts/trust); [Kokoro-FastAPI trust report](/tools/remsky-kokoro-fastapi/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=kyubyong-dc-tts`](/api/graphcanon/graph?tool=kyubyong-dc-tts) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_