Mistral 7B on RTX 5080: Monthly Cost & Token Output
Dedicated RTX 5080 hosting for Mistral 7B (7B) inference — fixed monthly pricing with unlimited tokens.
Monthly Cost Summary
At 131 tokens per second, the RTX 5080 is a throughput powerhouse for Mistral 7B. That speed means sub-100ms response latency for most queries — fast enough for real-time conversational AI. The monthly bill? £109, covering over 340 million tokens of capacity.
| Metric | Value |
|---|---|
| GPU | RTX 5080 (16 GB VRAM) |
| Model | Mistral 7B (7B parameters) |
| Monthly Server Cost | £109/mo |
| Tokens/Second | ~131.2 tok/s |
| Tokens/Day (24h) | ~11,335,680 |
| Tokens/Month | ~340,070,400 |
| Effective Cost per 1M Tokens | £0.3205 |
Speed Premium or Smart Investment?
The 5080 costs more than the 3090, but the 25% throughput boost can justify the price for latency-sensitive workloads:
| Provider | Cost per 1M Tokens | GigaGPU Savings |
|---|---|---|
| GigaGPU (RTX 5080) | £0.3205 | — |
| Together.ai | $0.20 | Comparable |
| Fireworks | $0.20 | Comparable |
| AWS Bedrock | $0.38 | 16% cheaper |
Break-Even Analysis
Against Together.ai at $0.20/1M tokens, break-even arrives at approximately 545M tokens/month. The 5080’s newer architecture sustains that throughput under concurrent load more gracefully than older GPUs, making the gap between theoretical and practical throughput smaller.
Hardware & Configuration Notes
Mistral 7B consumes ~7 GB of the 5080’s 16 GB VRAM, leaving 9 GB for concurrent request handling. The newer architecture also improves memory bandwidth, benefiting large-batch inference.
- VRAM usage: Mistral 7B requires approximately 7 GB VRAM. The RTX 5080 provides 16 GB, leaving 9 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 5080 nodes behind a load balancer. GigaGPU supports multi-server deployments with simple configuration.
Best Use Cases for Mistral 7B on RTX 5080
- Latency-critical conversational AI products
- Real-time translation and localisation services
- Interactive coding assistants needing instant feedback
- Live product recommendation engines
- Streaming content generation for media platforms
131 tok/s Mistral 7B — £109/Month
Deploy on a dedicated RTX 5080 for the fastest Mistral 7B experience outside the 5090.
