Best Dedicated GPU Servers for TTS (Text-to-Speech)

GPUMart offers a range of dedicated GPU server plans tailored to meet the diverse needs of AI developers and businesses. In this blog post, we'll explore the best dedicated GPU servers for ChatTTS and highlight four standout plans available on GPUMart.

Preface

In the rapidly evolving field of conversational AI, Text-to-Speech (TTS) technology plays a pivotal role. Whether you're developing a customer service bot, enhancing accessibility features, or creating interactive voice applications, having a robust and efficient TTS system is crucial. However, achieving high-quality, real-time speech synthesis requires substantial computational power, making dedicated GPU servers an invaluable resource.

GPUMart offers a range of dedicated GPU server plans tailored to meet the diverse needs of AI developers and businesses. In this blog post, we'll explore the best dedicated GPU servers for ChatTTS and highlight four standout plans available on GPUMart.

Why TTS Need a Dedicated GPU Server?

Text-to-Speech systems rely on deep learning models that process text inputs and generate natural-sounding speech. These models, such as Tacotron 2, WaveNet, and FastSpeech, demand significant computational resources to train and deploy effectively. Dedicated GPU servers provide the necessary power and efficiency to handle these intensive tasks.

Why Choose GPUMart?

GPUMart is a trusted provider of high-performance GPU servers, offering flexible plans that cater to a wide range of applications. Here are some key reasons to consider GPUMart for your TTS needs:

1. High-Performance GPUs: GPUMart offers servers equipped with the latest NVIDIA GPUs, ensuring top-notch performance for your TTS models.

2. Scalability: Whether you're a small startup or a large enterprise, GPUMart provides scalable solutions to match your growth.

3. Competitive Pricing: GPUMart's pricing plans are designed to offer the best value for your investment.

4. Reliable Support: With 24/7 customer support, you can rely on GPUMart to assist you with any technical issues or inquiries.

Best Dedicated GPU Servers for TTS ChatTTS

The GPU requirements for Text-to-Speech (TTS) depend on several factors, including the specific TTS model being used, the desired real-time performance, and the complexity of the generated audio. Here are some general guidelines:

1. GTX 1650/1650 and RTX 2060 for Entry-Level Requirements

These GPUs can handle simpler TTS models, suitable for non-real-time applications or less demanding use cases. For a 30-second audio clip, at least 4GB of GPU memory is required.

Batch processing of TTS can be done with lower-end GPUs since latency isn't a concern. For real-time synthesis, more powerful GPUs are needed to ensure smooth and immediate audio generation.

Basic GPU - GTX 1650

  • 64GB RAM
  • Eight-Core Xeon E5-2667v3report
  • 120GB + 960GB SSD
  • 100Mbps-1Gbpsreport
  • OS: Windows / Linux
  • GPU: Nvidia GeForce GTX 1650
  • Microarchitecture: Turing
  • Max GPUs: 1
  • CUDA Cores: 896
  • GPU Memory: 4GB GDDR5
  • FP32 Performance: 3.0 TFLOPSreport
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99.00/mo

Basic GPU - GTX 1660

  • 64GB RAM
  • Dual 10-Core Xeon E5-2660v2report
  • 120GB + 960GB SSD
  • 100Mbps-1Gbpsreport
  • OS: Windows / Linux
  • GPU: Nvidia GeForce GTX 1660
  • Microarchitecture: Turing
  • Max GPUs: 1
  • CUDA Cores: 1408
  • GPU Memory: 6GB GDDR6
  • FP32 Performance: 5.0 TFLOPSreport
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139.00/mo

Professional GPU - RTX 2060

  • 128GB RAM
  • Dual 10-Core E5-2660v2report
  • 120GB + 960GB SSD
  • 100Mbps-1Gbpsreport
  • OS: Windows / Linux
  • GPU: Nvidia GeForce RTX 2060
  • Microarchitecture: Ampere
  • Max GPUs: 2report
  • CUDA Cores: 1920
  • Tensor Cores: 240
  • GPU Memory: 6GB GDDR6
  • FP32 Performance: 6.5 TFLOPSreport
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159.00/mo
2. RTX 4060/3060 Ti and Tesla P100 for Mid-Range Requirements

For most mid-range TTS applications, the RTX 4060 or 3060 Ti should be sufficient and more economical, but if you anticipate needing the additional memory and computational power, the Tesla P100 is a robust choice.

The RTX 3060 Ti generally has 8GB of GDDR6 memory, which is suitable for many mid-range TTS models. The RTX 4060 is expected to have similar memory capacities, making it capable of handling reasonably large TTS models. The Tesla P100 comes with up to 16GB of HBM2 memory, which is significantly higher than the memory available on the RTX 3060 Ti/4060.

Advanced GPU - RTX 3060 Ti

  • 128GB RAM
  • Dual 12-Core E5-2697v2report
  • 240GB SSD + 2TB SSD
  • 100Mbps-1Gbpsreport
  • OS: Windows / Linux
  • GPU: GeForce RTX 3060 Ti
  • Microarchitecture: Ampere
  • Max GPUs: 2report
  • CUDA Cores: 4864
  • Tensor Cores: 152
  • GPU Memory: 8GB GDDR6
  • FP32 Performance: 16.2 TFLOPSreport
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179.00/mo
Summer Sale

Basic GPU - RTX 4060

  • 64GB RAM
  • Eight-Core E5-2690report
  • 120GB SSD + 960GB SSD
  • 100Mbps-1Gbpsreport
  • OS: Windows / Linux
  • GPU: Nvidia GeForece RTX 4060
  • Microarchitecture: Ada Lovelace
  • Max GPUs: 2report
  • CUDA Cores: 3072
  • Tensor Cores: 96
  • GPU Memory: 8GB GDDR6
  • FP32 Performance: 15.11 TFLOPSreport
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Save 42% (Was $179.00)
104.3/mo

Professional GPU - P100

  • 128GB RAM
  • Dual 10-Core E5-2660v2report
  • 120GB + 960GB SSD
  • 100Mbps-1Gbpsreport
  • OS: Windows / Linux
  • GPU: Nvidia Tesla P100
  • Microarchitecture: Pascal
  • Max GPUs: 2report
  • CUDA Cores: 3584
  • Tensor Cores: 640
  • GPU Memory: 16 GB HBM2
  • FP32 Performance: 9.5 TFLOPSreport
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159.00/mo
3. RTX A4000/A5000 and Tesla V100 for High-End Requirements

High-end GPUs are required for the most demanding models and use cases where real-time performance is critical. These GPUs provide ample memory and processing power to handle high-quality, low-latency TTS.

For high-end requirements of Text-to-Speech (TTS) AI, the RTX A4000/A5000 and Tesla V100 GPUs are excellent choices. The RTX A4000 and A5000 are part of NVIDIA's professional-grade Ampere architecture GPUs, designed for high-performance tasks. The Tesla V100 is a top-tier data center GPU based on the Volta architecture, designed specifically for high-performance computing and AI.

Advanced GPU - A4000

  • 128GB RAM
  • Dual 12-Core E5-2697v2report
  • 240GB SSD + 2TB SSD
  • 100Mbps-1Gbpsreport
  • OS: Windows / Linux
  • GPU: Nvidia Quadro RTX A4000
  • Microarchitecture: Ampere
  • Max GPUs: 2report
  • CUDA Cores: 6144
  • Tensor Cores: 192
  • GPU Memory: 16GB GDDR6
  • FP32 Performance: 19.2 TFLOPSreport
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209.00/mo
Summer Sale

Advanced GPU - A5000

  • 128GB RAM
  • Dual 12-Core E5-2697v2report
  • 240GB SSD + 2TB SSD
  • 100Mbps-1Gbpsreport
  • OS: Windows / Linux
  • GPU: Nvidia Quadro RTX A5000
  • Microarchitecture: Ampere
  • Max GPUs: 2report
  • CUDA Cores: 8192
  • Tensor Cores: 256
  • GPU Memory: 24GB GDDR6
  • FP32 Performance: 27.8 TFLOPSreport
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Save 31% (Was $349.00)
242.1/mo

Advanced GPU - V100

  • 128GB RAM
  • Dual 12-Core E5-2690v3report
  • 240GB SSD + 2TB SSD
  • 100Mbps-1Gbpsreport
  • OS: Windows / Linux
  • GPU: Nvidia V100
  • Microarchitecture: Volta
  • Max GPUs: 1
  • CUDA Cores: 5,120
  • Tensor Cores: 640
  • GPU Memory: 16GB HBM2
  • FP32 Performance: 14 TFLOPSreport
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229.00/mo
4. RTX 4090/A6000 and A100 for Enterprise-Level Requirements

For enterprise-level requirements of Text-to-Speech (TTS) AI, the RTX 4090, RTX A6000, and A100 GPUs are top-tier options. These GPUs are designed for data centers and enterprise-level applications where large-scale TTS deployment and high efficiency are needed.

The amount of GPU memory is crucial for larger models and longer audio sequences. Ensuring your GPU has sufficient VRAM is important for seamless processing. For the 4090 GPU, it can generate audio corresponding to approximately 7 semantic tokens per second. The Real-Time Factor (RTF) is around 0.3.

Enterprise GPU - RTX 4090

  • 256GB RAM
  • Dual 18-Core E5-2697v4report
  • 240GB SSD + 2TB NVMe + 8TB SATA
  • 100Mbps-1Gbpsreport
  • OS: Windows / Linux
  • GPU: GeForce RTX 4090
  • Microarchitecture: Ada Lovelace
  • Max GPUs: 1
  • CUDA Cores: 16,384
  • Tensor Cores: 512
  • GPU Memory: 24 GB GDDR6X
  • FP32 Performance: 82.6 TFLOPSreport
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409.00/mo

Enterprise GPU - RTX A6000

  • 256GB RAM
  • Dual 18-Core E5-2697v4report
  • 240GB SSD + 2TB NVMe + 8TB SATA
  • 100Mbps-1Gbpsreport
  • OS: Windows / Linux
  • GPU: Nvidia Quadro RTX A6000
  • Microarchitecture: Ampere
  • Max GPUs: 1
  • CUDA Cores: 10,752
  • Tensor Cores: 336
  • GPU Memory: 48GB GDDR6
  • FP32 Performance: 38.71 TFLOPSreport
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409.00/mo
New Arrival

Enterprise GPU - A100

  • 256GB RAM
  • Dual 18-Core E5-2697v4report
  • 240GB SSD + 2TB NVMe + 8TB SATA
  • 100Mbps-1Gbpsreport
  • OS: Windows / Linux
  • GPU: Nvidia A100
  • Microarchitecture: Ampere
  • Max GPUs: 1
  • CUDA Cores: 6912
  • Tensor Cores: 432
  • GPU Memory: 40GB HBM2e
  • FP32 Performance: 19.5 TFLOPSreport
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639.00/mo

Conclusion

In conclusion, GPUMart's dedicated GPU servers are an excellent choice for running ChatTTS applications. The four plans highlighted - Basic GPU - RTX 4060, Advanced GPU - V100, Advanced GPU - A4000, and Enterprise GPU - RTX 4090 - offer a range of performance options to suit different TTS requirements. By leveraging the power of NVIDIA GPUs, these servers provide the necessary performance and scalability for efficient TTS processing.

Additional - FAQs of Text To Speech

What is Text-to-Speech?

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Text-to-speech (TTS) is a type of assistive technology that reads digital text aloud. It's sometimes called “read aloud” technology. TTS can take words on a computer or other digital device and convert them into audio. This AI voice generator is used to communicate with users when reading a screen is either not possible or inconvenient.

What's Real-Time Factor(RTF)?

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Real-time factor (RTF) – The real-time factor (RTF) of a device measures how fast the embedded speech model can process audio input. It's the ratio of the processing time to the audio length. For example, if a device processes a 1-minute audio file in 30 seconds, the RTF is 0.5.

What's ChatTTS?

expand_more
ChatTTS is a text-to-speech model designed specifically for dialogue scenario such as LLM assistant. It is trained with 100,000+ hours composed of chinese and english. ChatTTS is optimized for dialogue-based tasks, enabling natural and expressive speech synthesis. It supports multiple speakers, facilitating interactive conversations.

What kind of GPU is good for TTS AI?

expand_more
Choosing a GPU for Text-to-Speech (TTS) AI involves considering factors like performance, memory, power consumption, and cost. The choice of GPU depends on the scale and complexity of your TTS AI applications:

· Entry-Level to Mid-Range: RTX 3060 Ti / RTX 4060 are suitable for smaller projects and development.
· Mid-Range to High-End: RTX 4090 and RTX A5000 offer robust performance for larger and more complex tasks.
· High-End to Enterprise: RTX A6000 and A100 are ideal for the most demanding and large-scale applications.

For most enterprise-level TTS AI tasks, the RTX A6000 provides a balance of high performance and large memory capacity, making it an excellent choice. For ultimate performance, especially in data center environments, the A100 is unmatched.