Building a talking AI agent on a budget? The RTX 5080 (16 GB VRAM) handles both LLM generation and speech synthesis concurrently with room to spare — if you use INT4 quantisation for the LLM. We tested LLaMA 3 8B (INT4) alongside Coqui XTTS-v2 on a GigaGPU dedicated server to measure the real cost of co-hosting these two workloads.
Models tested: LLaMA 3 8B + Coqui XTTS-v2
Dual-Model Throughput
| Component | Metric | Solo | Concurrent |
|---|---|---|---|
| LLaMA 3 8B (INT4) | Tokens/sec | 82 | 59.0 |
| Coqui XTTS-v2 | Real-time factor | 0.12 | 0.144 |
| Coqui XTTS-v2 | Synthesis speed | 8.3x | 6.9x |
All models loaded simultaneously in GPU memory. Throughput figures reflect concurrent operation with shared VRAM and compute.
VRAM Balance
| Component | VRAM |
|---|---|
| Combined model weights | 8.9 GB |
| Total RTX 5080 VRAM | 16 GB |
| Free headroom | ~7.1 GB |
INT4 quantisation makes this pairing work beautifully on 16 GB. Both models occupy under 9 GB, leaving over 7 GB free. That surplus lets you extend the LLM’s context window, buffer longer TTS synthesis jobs, or — if you are feeling ambitious — add a Whisper model to create a complete voice pipeline on one card.
Monthly Expense
| Cost Metric | Value |
|---|---|
| Server cost (single GPU) | £0.95/hr (£189/mo) |
| Equivalent separate GPUs | £1.90/hr |
| Savings vs separate servers | 50% |
The 5080 actually delivers faster concurrent TTS than the 3090 (6.9x vs 4.6x real-time) thanks to Blackwell’s improved shader throughput. For £189/mo you get a single-box solution for text-to-speech applications backed by an LLM. That is hard to beat for startups building voice-enabled products. See all benchmarks for the full picture.
Where This Shines
The LLM + TTS combination on the 5080 targets a specific niche: applications where the LLM crafts a text response and XTTS immediately speaks it. Think customer-facing voice bots for e-commerce, audiobook narration tools that dynamically adjust tone, or accessibility interfaces that convert any LLM output to speech in real time. The 6.9x synthesis speed means listeners never wait for audio — it renders faster than they can hear it.
Quick deploy:
docker compose up -d # llama.cpp + xtts-streaming-server containers with --gpus allSee our LLM hosting guide, Coqui TTS hosting guide, and all benchmark results. Related benchmarks: LLaMA 3 8B on RTX 5080, Coqui XTTS-v2 on RTX 5080.
Deploy LLM + TTS Pipeline on RTX 5080
Order this exact configuration. UK datacenter, full root access.
Order RTX 5080 Server
