Mistral Nemo vs QVQ 72B Preview

Performance benchmarks + pricing comparison — updated April 2026

Mistral Nemo

Mistral

Compact 12B open-weight model co-developed with NVIDIA. Excellent coding performance at minimal cost.

Input$0.150/M
Output$0.150/M
Context128K tokens
Best ForSelf-hosted deployments, cost-sensitive coding, edge deployments
Benchmark48/100

QVQ 72B Preview

Qwen

Qwen's visual reasoning model. Advanced image + text reasoning capabilities.

Input$0.500/M
Output$1.50/M
Context32K tokens
Best ForImage analysis, visual question answering, multimodal reasoning

Cost Comparison by Scenario

Estimated cost per project with 30% cache hit rate. Actual costs may vary based on usage patterns.

ScenarioMistral NemoQVQ 72B PreviewSavings
Small Script (1K lines) <$0.01 $0.06 Mistral Nemo saves $0.05 (84%)
Medium Feature (10K lines) $0.08 $0.48 Mistral Nemo saves $0.39 (83%)
Large Project (50K lines) $0.41 $2.38 Mistral Nemo saves $1.96 (83%)
Code Review (5K lines) $0.03 $0.13 Mistral Nemo saves $0.10 (76%)

Verdict

Mistral Nemo wins on both price and performance — $0.150/M input with a benchmark score of N/A/100.

For most developers, this is the clear choice between these two models.

Compare with Other Models