Mistral NemovsMistral Small
Mistral AI vs Mistral AI — Side-by-side model comparison
Head-to-Head Comparison
| Metric | Mistral Nemo | Mistral Small |
|---|---|---|
| Provider | ||
| Arena Rank | #27 | #19 |
| Context Window | 128K | 32K |
| Input Pricing | $0.30/1M tokens | $0.20/1M tokens |
| Output Pricing | $0.30/1M tokens | $0.60/1M tokens |
| Parameters | 12B | 22B |
| Open Source | Yes | Yes |
| Best For | Lightweight tasks, drop-in replacement | Fast inference, cost-effective tasks, chat |
| Release Date | Jul 18, 2024 | Sep 18, 2024 |
Mistral Nemo
Mistral Nemo is a compact 12B parameter model co-developed by Mistral AI and Nvidia, designed as a high-performance drop-in replacement for smaller models. Despite its size, it delivers performance significantly above its weight class on coding, reasoning, and multilingual tasks. As an open-source model, it can be self-hosted on a single GPU, making it ideal for organizations with limited compute resources or strict data privacy requirements. Its small size enables fast inference and low-cost deployment while maintaining the quality standards of the Mistral model family.
View Mistral AI profile →Mistral Small
Mistral Small is Mistral AI's efficient model optimized for low-latency, cost-effective deployments. At 22 billion parameters with a 32K context window, it delivers strong performance for everyday tasks including summarization, classification, and conversational AI. It offers an excellent balance between capability and cost, making it suitable for high-volume production applications where fast response times matter.
View Mistral AI profile →Key Differences: Mistral Nemo vs Mistral Small
Mistral Small ranks higher in arena benchmarks (#19) indicating stronger overall performance.
Mistral Small is 1.3x cheaper on average, making it the better choice for high-volume applications.
Mistral Nemo supports a larger context window (128K), allowing it to process longer documents in a single request.
Mistral Nemo has 12B parameters vs Mistral Small's 22B, which affects inference speed and capability.
When to use Mistral Nemo
- +Quality matters more than cost
- +You need to process long documents (128K context)
- +Your use case involves lightweight tasks, drop-in replacement
When to use Mistral Small
- +You need the highest quality output based on arena rankings
- +Budget is a concern and you need cost efficiency
- +Your use case involves fast inference, cost-effective tasks, chat
Cost Analysis
At current pricing, Mistral Small is 1.3x more affordable than Mistral Nemo. For a typical enterprise workload processing 100M tokens per month:
Mistral Nemo monthly cost
$30
100M tokens/mo (50/50 in/out)
Mistral Small monthly cost
$40
100M tokens/mo (50/50 in/out)
The Verdict
Mistral Small wins our head-to-head comparison with 3 out of 5 category wins. It's the stronger choice for fast inference, cost-effective tasks, chat, though Mistral Nemo holds an edge in lightweight tasks, drop-in replacement.
Last compared: March 2026 · Data sourced from public benchmarks and official pricing pages