Phi-3 on RTX 4060: Monthly Cost & Token Output
Dedicated RTX 4060 hosting for Phi-3 (3.8B) inference — fixed monthly pricing with unlimited tokens.
Monthly Cost Summary
Phi-3 punches well above its weight at just 3.8 billion parameters. On a £49/month RTX 4060, it runs at 77 tok/s — nearly 200 million tokens of monthly capacity. With an effective cost of £0.25 per million tokens, this is one of the lowest cost-per-token setups available on any platform.
| Metric | Value |
|---|---|
| GPU | RTX 4060 (8 GB VRAM) |
| Model | Phi-3 (3.8B parameters) |
| Monthly Server Cost | £49/mo |
| Tokens/Second | ~77.0 tok/s |
| Tokens/Day (24h) | ~6,652,800 |
| Tokens/Month | ~199,584,000 |
| Effective Cost per 1M Tokens | £0.2455 |
Tiny Model, Tiny Cost
Phi-3’s small footprint means it runs efficiently on budget hardware. Here is how dedicated hosting compares to API alternatives:
| Provider | Cost per 1M Tokens | GigaGPU Savings |
|---|---|---|
| GigaGPU (RTX 4060) | £0.2455 | — |
| Together.ai | $0.10 | Comparable |
| Fireworks | $0.20 | Comparable |
| Azure OpenAI | $0.26 | 6% cheaper |
Break-Even Analysis
Compared to Together.ai at $0.10/1M tokens, break-even lands at approximately 490M tokens/month. Phi-3’s compact size allows high throughput even on entry-level GPUs, making break-even achievable for medium-volume production workloads.
Hardware & Configuration Notes
Phi-3 needs only ~4 GB VRAM, leaving a comfortable 4 GB on the RTX 4060 for KV cache and batched serving. This makes it one of the few models that fits on 8 GB GPUs with genuine room to breathe.
- VRAM usage: Phi-3 requires approximately 4 GB VRAM. The RTX 4060 provides 8 GB, leaving 4 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 nodes behind a load balancer. GigaGPU supports multi-server deployments with simple configuration.
Best Use Cases for Phi-3 on RTX 4060
- Lightweight internal chatbots for small teams
- Edge-like inference on budget GPU hardware
- Quick-turnaround text summarisation
- Simple Q&A and FAQ automation
- Cost-efficient batch processing at scale
Phi-3 from £49/Month
Run Microsoft’s compact powerhouse on a dedicated RTX 4060. Flat rate, unlimited tokens.
