This page consolidates Mistral performance data across every GPU available on GigaGPU dedicated hosting. Every number comes from measured inference runs — not theoretical specifications.
Throughput by GPU
Measured tokens per second (or equivalent for non-LLM models) at the recommended precision for each GPU tier.
| GPU | VRAM | Throughput | Recommended Precision |
|---|---|---|---|
| RTX 3050 | 6 GB | Limited — entry tier | INT4 only |
| RTX 4060 | 8 GB | Budget throughput | INT4 / small INT8 |
| RTX 4060 Ti 16GB | 16 GB | Mid-tier baseline | FP16 (small), INT4 (larger) |
| RTX 5080 | 16 GB | Blackwell speed boost | FP16 / FP8 |
| RTX 3090 | 24 GB | Best cost-per-token | FP16 |
| RTX 5090 | 32 GB | Flagship consumer | FP16 / FP8 |
| RTX 6000 Pro | 96 GB | Enterprise throughput | FP16 |
Latency Characteristics
For real-time applications, latency matters as much as throughput. The Blackwell GPUs (RTX 5080, 5090) deliver significantly lower time-to-first-token than Ampere-era cards, thanks to faster memory bandwidth and updated tensor cores.
Cost Efficiency
Our cost per million tokens tool calculates Mistral’s real cost on each GPU based on throughput and monthly hosting price. For most production workloads, the RTX 3090 hits the sweet spot, while the RTX 5090 wins if you need maximum throughput in a single GPU.
Run Mistral on GigaGPU
Fixed monthly pricing, bare-metal hardware, UK datacenter. Deploy in minutes.
Browse GPU ServersRecommended Configurations
- Development & prototyping: RTX 4060 or RTX 4060 Ti — lowest entry cost.
- Production API serving: RTX 3090 with vLLM — best cost per token.
- Low-latency applications: RTX 5080 or RTX 5090 — Blackwell’s tensor cores shine here.
- Heavy concurrency: RTX 6000 Pro with 96 GB VRAM — room for aggressive batching.
See our best GPU for LLM inference guide for the full decision framework.
