Qwen 7B on RTX 5080: Monthly Cost & Token Output
Dedicated RTX 5080 hosting for Qwen 7B (7B) inference — fixed monthly pricing with unlimited tokens.
Monthly Cost Summary
When latency matters as much as cost, the RTX 5080 delivers. At 122.5 tok/s, Qwen 7B responses feel instantaneous to end users. The £109 monthly bill covers 317 million tokens — more than enough for a busy production deployment with margin to spare for traffic surges.
| Metric | Value |
|---|---|
| GPU | RTX 5080 (16 GB VRAM) |
| Model | Qwen 7B (7B parameters) |
| Monthly Server Cost | £109/mo |
| Tokens/Second | ~122.5 tok/s |
| Tokens/Day (24h) | ~10,584,000 |
| Tokens/Month | ~317,520,000 |
| Effective Cost per 1M Tokens | £0.3433 |
Latest-Gen Speed at a Fixed Price
The RTX 5080’s newer architecture provides a measurable speed advantage over the 3090. Here is how it compares to API pricing:
| Provider | Cost per 1M Tokens | GigaGPU Savings |
|---|---|---|
| GigaGPU (RTX 5080) | £0.3433 | — |
| Together.ai | $0.20 | Comparable |
| Fireworks | $0.20 | Comparable |
| DeepInfra | $0.13 | Comparable |
Break-Even Analysis
Against DeepInfra at $0.13/1M tokens, the break-even is approximately 838.5M tokens/month. The 5080’s higher memory bandwidth and faster compute mean it handles concurrent load more efficiently, narrowing the gap between theoretical and actual break-even in production.
Hardware & Configuration Notes
Qwen 7B occupies ~7 GB of the 5080’s 16 GB VRAM. The remaining 9 GB supports substantial KV caches and concurrent batch processing — a strong balance between cost and performance.
- VRAM usage: Qwen 7B requires approximately 7 GB VRAM. The RTX 5080 provides 16 GB, leaving 9 GB headroom for KV cache and batching.
- Quantisation: Running in FP16 by default. INT8 or INT4 quantisation can reduce VRAM usage and increase throughput by 20–40% with minimal quality loss for most use cases.
- Batching: With continuous batching enabled (e.g., vLLM or TGI), you can serve multiple concurrent users from a single GPU, increasing effective throughput significantly.
- Scaling: Need more throughput? Add additional RTX 5080 nodes behind a load balancer. GigaGPU supports multi-server deployments with simple configuration.
Best Use Cases for Qwen 7B on RTX 5080
- Latency-sensitive multilingual AI products
- Real-time customer interaction across language barriers
- Interactive knowledge retrieval systems
- Parallel content generation for global audiences
- Medium-to-high traffic API backends for LLM applications
Qwen 7B at 122.5 tok/s — £109/Month
Claim a dedicated RTX 5080 for fast, flat-rate Qwen 7B inference.
