Before you deploy Coqui TTS on a dedicated GPU server, you need to know exactly how much VRAM each variant consumes at different precisions. This guide gives you the real numbers — measured on GigaGPU dedicated servers — so you can match your model to the right hardware without guessing.
VRAM by Variant and Precision
Each row shows the minimum VRAM needed to load the model weights. Add 10-20% headroom for KV cache, activations, and batch processing.
| Variant | FP16 VRAM | INT8 VRAM | INT4 VRAM |
|---|---|---|---|
| XTTS-v2 (1.7B) | 3.4 GB | 2 GB | 1.2 GB |
| VITS | 1.2 GB | 800 MB | 500 MB |
| YourTTS | 1.5 GB | 1 GB | 700 MB |
| Tortoise | 5 GB | 3 GB | 2 GB |
Which GigaGPU Server Fits Coqui TTS?
Based on the VRAM table above, here’s how Coqui TTS maps to our GPU lineup:
| GPU | VRAM | Verdict |
|---|---|---|
| RTX 3050 | 6 GB | Only smallest variant (INT4) |
| RTX 4060 | 8 GB | Small variants, INT4/INT8 |
| RTX 4060 Ti 16GB | 16 GB | Mid variants FP16, larger at INT4 |
| RTX 3090 | 24 GB | Most variants FP16 with headroom |
| RTX 5090 | 32 GB | All standard variants FP16 |
| RTX 6000 Pro | 96 GB | Even the largest variants with room for batching |
Context Length Impact
VRAM requirements scale with context length. A 32K context adds roughly 2-4 GB of KV cache on top of base weights. For 128K contexts on large variants, you may need to move up a GPU tier or use quantised KV cache. See our context length VRAM guide for details.
Deployment Recommendations
For production deployments:
- Development & prototyping: Use INT4 on the smallest GPU that fits — minimise cost while you iterate.
- Production inference: Use FP16 on a GPU with at least 20% headroom. This avoids OOM under batch load.
- High-throughput serving: Step up to a larger GPU to batch more requests simultaneously.
Our best GPU for LLM inference guide walks through the full decision matrix across every workload type.
Deploy Coqui TTS on a Dedicated GPU Server
Fixed monthly pricing, full root access, UK datacenter. Pick the GPU that matches your Coqui TTS variant.
Browse GPU ServersFor cost analysis, use our LLM cost calculator or check cost per million tokens by GPU.
