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Mistral NemovsMistral Small

Mistral AI vs Mistral AI — Side-by-side model comparison

Mistral Small leads 3/5 categories

Head-to-Head Comparison

MetricMistral NemoMistral 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, developed jointly by Mistral AI and NVIDIA, is a compact open-source model with 12 billion parameters designed as a high-performance replacement for smaller models. Despite its size, the model delivers performance significantly above its weight class on coding, reasoning, and multilingual tasks, benefiting from the combined expertise of Mistral's model architecture team and NVIDIA's training infrastructure. Mistral Nemo can run on a single consumer GPU, making it ideal for organizations with limited compute resources or strict data privacy requirements that preclude cloud-based API usage. Its small footprint enables fast inference and low-cost deployment while maintaining the quality standards of the Mistral model family. Free and open-source, the model supports commercial use and fine-tuning. It has become a popular choice for developers seeking capable, self-hosted AI without the hardware demands of larger models.

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Mistral Small

Mistral Small, developed by Mistral AI, is a compact 22 billion parameter model with a 32K token context window optimized for fast inference and low deployment costs. The model handles coding, summarization, classification, and conversational tasks while maintaining the quality standards established by the Mistral model family. Its small footprint makes it suitable for edge deployment, cost-sensitive production applications, and use cases requiring low-latency responses. Priced at $0.20 per million input tokens and $0.60 per million output tokens, it offers affordable access to Mistral's technology. As an open-source model, it can also be self-hosted without API costs. Mistral Small ranks #19 on the Chatbot Arena leaderboard, demonstrating competitive performance for its compact size and establishing it as a strong option for budget-conscious deployments.

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Key Differences: Mistral Nemo vs Mistral Small

1

Mistral Small ranks higher in arena benchmarks (#19) indicating stronger overall performance.

2

Mistral Small is 1.3x cheaper on average, making it the better choice for high-volume applications.

3

Mistral Nemo supports a larger context window (128K), allowing it to process longer documents in a single request.

4

Mistral Nemo has 12B parameters vs Mistral Small's 22B, which affects inference speed and capability.

M

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
View full Mistral Nemo specs →
M

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
View full Mistral Small specs →

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: April 2026 · Data sourced from public benchmarks and official pricing pages

Frequently Asked Questions

Which is better, Mistral Nemo or Mistral Small?
In our head-to-head comparison, Mistral Small leads in 3 out of 5 categories (arena rank, context window, input pricing, output pricing, and parameters). Mistral Small excels at fast inference, cost-effective tasks, chat, while Mistral Nemo is better suited for lightweight tasks, drop-in replacement. The best choice depends on your specific requirements, budget, and use case.
How does Mistral Nemo pricing compare to Mistral Small?
Mistral Nemo charges $0.30 per 1M input tokens and $0.30 per 1M output tokens. Mistral Small charges $0.20 per 1M input tokens and $0.60 per 1M output tokens. Mistral Small is the more affordable option, approximately 1.3x cheaper on average. For high-volume production workloads, the pricing difference can significantly impact total cost of ownership.
What is the context window difference between Mistral Nemo and Mistral Small?
Mistral Nemo supports a 128K token context window, while Mistral Small supports 32K tokens. Mistral Nemo can process longer documents, codebases, and conversations in a single request. Context window size matters most for tasks involving long documents, large codebases, or extended conversations.
Can I use Mistral Nemo or Mistral Small for free?
Mistral Nemo is a paid API model starting at $0.30 per 1M input tokens. Mistral Small is a paid API model starting at $0.20 per 1M input tokens. Open-source models can be self-hosted for free but require your own GPU infrastructure.
Which model has better benchmarks, Mistral Nemo or Mistral Small?
Mistral Nemo holds arena rank #27, while Mistral Small holds rank #19. Mistral Small performs better in overall arena benchmarks, which aggregate human preference ratings across coding, reasoning, and general tasks. Note that benchmarks don't capture every use case — we recommend testing both models on your specific tasks.
Is Mistral Nemo or Mistral Small better for coding?
Mistral Nemo's primary strength is lightweight tasks, drop-in replacement. Mistral Small's primary strength is fast inference, cost-effective tasks, chat. For coding specifically, arena rank and code-specific benchmarks are the best indicators of performance.