Qwen 7B on RTX 4060 Ti: Monthly Cost & Token Output
Dedicated RTX 4060 Ti hosting for Qwen 7B (7B) inference — fixed monthly pricing with unlimited tokens.
Monthly Cost Summary
For teams that need Qwen 7B with room to grow, the RTX 4060 Ti doubles the VRAM to 16 GB while boosting throughput to 73.5 tok/s. The £69/month price covers over 190 million tokens — and the 9 GB of spare VRAM means you can serve multiple concurrent users comfortably.
| Metric | Value |
|---|---|
| GPU | RTX 4060 Ti (16 GB VRAM) |
| Model | Qwen 7B (7B parameters) |
| Monthly Server Cost | £69/mo |
| Tokens/Second | ~73.5 tok/s |
| Tokens/Day (24h) | ~6,350,400 |
| Tokens/Month | ~190,512,000 |
| Effective Cost per 1M Tokens | £0.3622 |
How £69/Month Compares to Pay-Per-Token
The extra VRAM on the 4060 Ti enables better batching performance, which improves effective throughput under real-world concurrent load:
| Provider | Cost per 1M Tokens | GigaGPU Savings |
|---|---|---|
| GigaGPU (RTX 4060 Ti) | £0.3622 | — |
| Together.ai | $0.20 | Comparable |
| Fireworks | $0.20 | Comparable |
| DeepInfra | $0.13 | Comparable |
Break-Even Analysis
Compared to DeepInfra at $0.13/1M tokens, the crossover is approximately 530.8M tokens/month. Below that, DeepInfra costs less per token. Above it, every token on your dedicated server is effectively free — and you keep full control over data privacy and model configuration.
Hardware & Configuration Notes
With 9 GB of free VRAM after loading Qwen 7B, the 4060 Ti can handle generous KV caches for multi-turn conversations — an important factor for chatbot deployments where context length matters.
- VRAM usage: Qwen 7B requires approximately 7 GB VRAM. The RTX 4060 Ti 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 4060 Ti nodes behind a load balancer. GigaGPU supports multi-server deployments with simple configuration.
Best Use Cases for Qwen 7B on RTX 4060 Ti
- Production chatbots with extended conversation context
- Multilingual customer service automation
- Enterprise search with retrieval-augmented generation
- Automated content localisation
- Parallel text analysis across multiple languages
190M Tokens, £69, Zero Surprises
Get a dedicated RTX 4060 Ti for Qwen 7B. Pre-configured and ready to deploy.