Mistral 7B vs Gemma 2 9B for Cost-Optimised Batch Processing: GPU Benchmark

Quick Verdict

Mistral 7B pushes 475 batch tok/s. Gemma 2 9B pushes 328. That is a 45% throughput gap — the widest in any workload we tested between these two models. But here is the twist: Gemma 2 9B costs $0.07 per million tokens versus Mistral 7B’s $0.16. The slower model is somehow cheaper per token. The explanation is GPU utilisation: Gemma 2 9B hits 95% utilisation to Mistral’s 92%, meaning its larger parameter count saturates the compute units more completely even at lower absolute throughput. On a dedicated GPU server, the right pick depends on whether you are constrained by time (Mistral) or by budget (Gemma).

For broader model comparisons, see our GPU comparisons hub.

Specs Comparison

For batch processing, VRAM footprint determines maximum batch size, and batch size drives throughput. Mistral 7B’s 1.5 GB VRAM advantage at INT4 allows larger batches, which partially explains its higher absolute token throughput. The licensing difference also matters: Mistral’s Apache 2.0 licence places no restrictions on batch-processing commercial content, while Gemma’s terms require review for certain use cases on self-hosted infrastructure.

For detailed VRAM breakdowns, see our guides on Mistral 7B VRAM requirements and Gemma 2 9B VRAM requirements.

Batch Processing Benchmark

We tested both models on an NVIDIA RTX 3090 (24 GB VRAM) using vLLM with INT4 quantisation, maximum batch sizes, and continuous batching. The workload simulated large-scale offline processing: classification, entity extraction, and summarisation across thousands of items. For live speed data, check our tokens-per-second benchmark.

The 475 vs 328 tok/s gap means Mistral 7B finishes a 10-million-token batch job in roughly 5.8 hours versus Gemma 2 9B’s 8.5 hours. If your batch window is overnight (say, 8 hours), Mistral handles nearly 50% more volume before the workday starts. Gemma 2 9B’s cost advantage only materialises if you are not time-constrained. Visit our best GPU for LLM inference guide for hardware-level comparisons.

See also: Mistral 7B vs Gemma 2 9B for Chatbot / Conversational AI for a related comparison.

See also: LLaMA 3 8B vs Mistral 7B for Cost-Optimised Batch Processing for a related comparison.

Cost Analysis

The cost-per-token numbers tell an unexpected story. Despite lower throughput, Gemma 2 9B achieves a lower cost per million tokens thanks to its higher GPU utilisation efficiency. On the same dedicated GPU server, this creates a genuine trade-off between time and money.

If your batch jobs run 24/7, Gemma 2 9B’s lower cost per token wins over the course of a month. If your batch window is limited, Mistral 7B’s throughput advantage is more valuable than Gemma’s cost edge. Use our cost-per-million-tokens calculator to model the economics at your volume.

Recommendation

Choose Mistral 7B if your batch jobs have deadlines — nightly data processing, morning report generation, or any pipeline where wall-clock time is the binding constraint. The 45% throughput advantage means dramatically shorter job completion times, and the Apache 2.0 licence removes friction for commercial batch processing.

Choose Gemma 2 9B if your batch pipeline runs continuously and cost per token is the primary metric. Gemma 2 9B’s $0.07/M tokens is less than half Mistral’s cost, and its safety-aligned output requires less post-processing filtering for content that will eventually reach end users — a hidden cost saving that does not appear in the throughput numbers.

Run batch workloads overnight on dedicated GPU servers to maximise utilisation and minimise cost per processed unit.