DeepSeek 7B on RTX 5060 Ti: Monthly Cost & Token Output
Dedicated RTX 5060 Ti hosting for DeepSeek 7B (7B) inference — fixed monthly pricing with unlimited tokens.
194 Million Tokens and Room to Grow
Upgrading from the RTX 5060 to the 5060 Ti doubles your VRAM from 8 GB to 16 GB and bumps throughput to 75 tok/s — all for just £20 more per month. The extra VRAM is not wasted: it gives DeepSeek 7B a generous 9 GB buffer for KV cache and concurrent batching.
| Metric | Value |
|---|---|
| GPU | RTX 5060 Ti (16 GB VRAM) |
| Model | DeepSeek 7B (7B parameters) |
| Monthly Server Cost | £119/mo |
| Tokens/Second | ~75.0 tok/s |
| Tokens/Day (24h) | ~6,480,000 |
| Tokens/Month | ~194,400,000 |
| Effective Cost per 1M Tokens | £0.3549 |
API Bills vs. Fixed Hardware
Running DeepSeek 7B through third-party APIs means paying for every single token. At 194M tokens/month, those per-token charges add up fast:
| Provider | Cost per 1M Tokens | GigaGPU Savings |
|---|---|---|
| GigaGPU (RTX 5060 Ti) | £0.3549 | — |
| Together.ai | $0.20 | Comparable |
| Fireworks | $0.20 | Comparable |
| DeepInfra | $0.13 | Comparable |
At full utilisation on DeepInfra, you would spend roughly $25/month on tokens alone — but lose control over latency, uptime, and data handling. The £119 GigaGPU rate buys you all of that plus unlimited headroom.
When Does Self-Hosting Win?
Compared to DeepInfra at $0.13/1M tokens, the crossover lands at roughly 530.8M tokens/month. Past that point, you save more with every additional token processed.
But cost is only part of the story. Dedicated hardware means your prompts and outputs never leave your server — a non-negotiable requirement for teams handling sensitive data. Model your exact scenario to see the full picture.
Technical Setup
- Comfortable fit: DeepSeek 7B needs ~7 GB VRAM, leaving 9 GB free on the 5060 Ti for deep KV caches and batched serving.
- Quantisation: FP16 is the default. INT8/INT4 can push throughput past 100 tok/s with minimal quality trade-off.
- Serving framework: Deploy with vLLM or TGI for continuous batching and OpenAI-format API compatibility.
- Scaling: Bolt on additional 5060 Ti nodes for horizontal scaling as your user base expands.
Strong Use Cases
- Multi-user chatbots with batched serving
- Retrieval-augmented generation for knowledge management
- Content moderation and classification pipelines
- Developer-facing code-assist APIs
- Overnight batch processing of large text collections
16 GB VRAM, £119/Month, Zero Metering
Upgrade to an RTX 5060 Ti for DeepSeek 7B with room to breathe. Pre-configured and ready to deploy.
