LLaMA 3 8B on RTX 4060: Monthly Cost & Token Output
Dedicated RTX 4060 hosting for LLaMA 3 8B (8B) inference — fixed monthly pricing with unlimited tokens.
Monthly Cost Summary
For £49 per month, you get a dedicated RTX 4060 that generates roughly 135.5 million tokens of LLaMA 3 8B output. That works out to an effective rate of £0.36 per million tokens — and the cost stays flat whether you use 10% or 100% of capacity.
| Metric | Value |
|---|---|
| GPU | RTX 4060 (8 GB VRAM) |
| Model | LLaMA 3 8B (8B parameters) |
| Monthly Server Cost | £49/mo |
| Tokens/Second | ~52.3 tok/s |
| Tokens/Day (24h) | ~4,518,720 |
| Tokens/Month | ~135,561,600 |
| Effective Cost per 1M Tokens | £0.3615 |
How £49/Month Compares to API Pricing
Most teams paying per-token through API providers can cut costs by switching to dedicated hardware. Here is where the RTX 4060 lands alongside leading LLaMA 3 8B API endpoints:
| Provider | Cost per 1M Tokens | GigaGPU Savings |
|---|---|---|
| GigaGPU (RTX 4060) | £0.3615 | — |
| Together.ai | $0.18 | Comparable |
| Fireworks | $0.20 | Comparable |
| Groq | $0.05 | Comparable |
The per-token rates from API providers look low in isolation, but they scale linearly with usage. A dedicated server caps your spend at £49 regardless of volume.
Break-Even Volume
Against Groq at $0.05/1M tokens (the cheapest API option), the crossover point sits at roughly 980M tokens/month. Below that threshold, Groq costs less per token. Above it, every additional token on your dedicated RTX 4060 is effectively free.
At twice the break-even volume, your effective per-token rate drops to half of Groq’s — and the gap only widens from there. For teams with predictable, high-volume workloads, self-hosted inference on a dedicated GPU delivers compounding savings month over month.
Hardware & Configuration Details
- VRAM fit: LLaMA 3 8B occupies approximately 8 GB in FP16, which fills the RTX 4060’s 8 GB VRAM completely. This leaves minimal headroom for KV cache, so consider INT8 quantisation to free up memory for batching.
- Quantisation options: Switching to INT8 or INT4 can boost throughput by 20–40% while retaining strong output quality for most production tasks.
- Concurrent serving: Pair the GPU with vLLM or TGI for continuous batching, enabling multiple users from one card.
- Horizontal scaling: Need more throughput? Add additional RTX 4060 nodes behind a load balancer. GigaGPU handles multi-server setups with straightforward configuration.
Ideal Workloads
- Customer-facing chatbots and internal help desks
- Document summarisation and content drafting pipelines
- RAG-powered search and knowledge retrieval
- Code completion and developer tooling
- Overnight batch processing of text corpora
Get Started for £49/Month
Claim a dedicated RTX 4060 pre-loaded for LLaMA 3 8B inference. Flat pricing, zero per-token charges, no vendor lock-in.
