Gemma 9B (INT4) on RTX 4060: Monthly Cost & Token Output
Dedicated RTX 4060 hosting for Gemma 9B (INT4) (9B INT4) inference — fixed monthly pricing with unlimited tokens.
Monthly Cost Summary
INT4 quantisation unlocks Gemma 9B on the RTX 4060 — a pairing that is impossible at full precision. By compressing the model to ~5 GB, you gain 3 GB of VRAM headroom and 60.5 tok/s throughput, all for just £49/month. That is 157 million tokens of monthly capacity at £0.31 per million.
| Metric | Value |
|---|---|
| GPU | RTX 4060 (8 GB VRAM) |
| Model | Gemma 9B (INT4) (9B INT4 parameters) |
| Monthly Server Cost | £49/mo |
| Tokens/Second | ~60.5 tok/s |
| Tokens/Day (24h) | ~5,227,200 |
| Tokens/Month | ~156,816,000 |
| Effective Cost per 1M Tokens | £0.3125 |
Budget Hardware, Full Gemma 9B Capability
Quantisation makes premium models accessible on entry-level GPUs. Here is how the economics compare:
| Provider | Cost per 1M Tokens | GigaGPU Savings |
|---|---|---|
| GigaGPU (RTX 4060) | £0.3125 | — |
| Together.ai | $0.20 | Comparable |
| Fireworks | $0.20 | Comparable |
| Google Vertex | $0.30 | Comparable |
Break-Even Analysis
Against Together.ai at $0.20/1M tokens, break-even is roughly 245M tokens/month. At the RTX 4060’s price point, even moderate utilisation can justify dedicated hardware over metered API calls.
Hardware & Configuration Notes
INT4 quantisation compresses Gemma 9B from ~9 GB to approximately 5 GB, making it runnable on the RTX 4060’s 8 GB VRAM with 3 GB to spare. Quality loss is minimal for most production use cases.
- VRAM usage: Gemma 9B (INT4) requires approximately 5 GB VRAM. The RTX 4060 provides 8 GB, leaving 3 GB headroom for KV cache and batching.
- Quantisation: INT4 quantisation reduces Gemma 9B from ~9 GB to ~5 GB VRAM. This makes it possible to run on 8 GB GPUs while retaining strong output quality.
- 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 Gemma 9B (INT4) on RTX 4060
- Budget-friendly chatbot deployments using Gemma 9B
- Prototyping and testing before scaling to larger GPUs
- Small-team internal AI assistants
- Text classification and extraction workloads
- Educational and academic AI applications
Gemma 9B on Budget Hardware: £49/Month
Run quantised Gemma 9B on a dedicated RTX 4060. Flat pricing, full control, no metering.
