Mistral 7B on RTX 3090: Monthly Cost & Token Output
Dedicated RTX 3090 hosting for Mistral 7B (7B) inference — fixed monthly pricing with unlimited tokens.
Monthly Cost Summary
Running Mistral 7B through AWS Bedrock at $0.38/1M tokens? An RTX 3090 on GigaGPU delivers the same model at £0.327/1M — 14% cheaper, and the price stays flat regardless of traffic spikes. Over a year, the savings on a £89/month server versus Bedrock can total hundreds of pounds.
| Metric | Value |
|---|---|
| GPU | RTX 3090 (24 GB VRAM) |
| Model | Mistral 7B (7B parameters) |
| Monthly Server Cost | £89/mo |
| Tokens/Second | ~105.0 tok/s |
| Tokens/Day (24h) | ~9,072,000 |
| Tokens/Month | ~272,160,000 |
| Effective Cost per 1M Tokens | £0.327 |
GigaGPU vs. API Provider Economics
Mistral 7B is offered by multiple API platforms. The RTX 3090 delivers competitive per-token pricing with 17 GB of spare VRAM:
| Provider | Cost per 1M Tokens | GigaGPU Savings |
|---|---|---|
| GigaGPU (RTX 3090) | £0.327 | — |
| Together.ai | $0.20 | Comparable |
| Fireworks | $0.20 | Comparable |
| AWS Bedrock | $0.38 | 14% cheaper |
Break-Even Analysis
Compared to Together.ai at $0.20/1M tokens, the break-even sits at roughly 445M tokens/month. The RTX 3090’s generous 17 GB of free VRAM enables aggressive batching that can push real-world throughput far above the 105 tok/s baseline.
Hardware & Configuration Notes
With 24 GB VRAM total and only 7 GB consumed by Mistral 7B, the RTX 3090 leaves 17 GB free — enough for deep KV caches supporting dozens of concurrent users, or even co-hosting a smaller secondary model.
- VRAM usage: Mistral 7B requires approximately 7 GB VRAM. The RTX 3090 provides 24 GB, leaving 17 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 3090 nodes behind a load balancer. GigaGPU supports multi-server deployments with simple configuration.
Best Use Cases for Mistral 7B on RTX 3090
- High-concurrency customer support platforms
- Real-time content moderation pipelines
- Enterprise RAG with multi-document retrieval
- Automated report and memo generation
- Bulk text analysis and entity extraction
272M Tokens/Month, Zero Metering
Get a dedicated RTX 3090 for Mistral 7B. 105 tok/s, 24 GB VRAM, £89/month flat.
