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Mistral NemovsMixtral 8x22B

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

Mistral Nemo leads 3/5 categories

Head-to-Head Comparison

MetricMistral NemoMixtral 8x22B
Provider
Arena Rank
#27
#16
Context Window
128K
64K
Input Pricing
$0.30/1M tokens
$0.90/1M tokens
Output Pricing
$0.30/1M tokens
$2.70/1M tokens
Parameters
12B
176B (39B active)
Open Source
Yes
Yes
Best For
Lightweight tasks, drop-in replacement
Efficient reasoning, multilingual, coding
Release Date
Jul 18, 2024
Apr 17, 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 →

Mixtral 8x22B

Mixtral 8x22B is Mistral AI's large mixture-of-experts model that uses a sparse architecture to achieve strong performance while activating only a fraction of its total parameters per token. With 176 billion total parameters but only 39 billion active per forward pass, it delivers efficiency that makes it practical to deploy despite its size. It features a 64K context window and excels at multilingual tasks, coding, and mathematical reasoning.

View Mistral AI profile →

Key Differences: Mistral Nemo vs Mixtral 8x22B

1

Mixtral 8x22B ranks higher in arena benchmarks (#16) indicating stronger overall performance.

2

Mistral Nemo is 6.0x 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 Mixtral 8x22B's 176B (39B active), which affects inference speed and capability.

M

When to use Mistral Nemo

  • +Budget is a concern and you need cost efficiency
  • +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 Mixtral 8x22B

  • +You need the highest quality output based on arena rankings
  • +Quality matters more than cost
  • +Your use case involves efficient reasoning, multilingual, coding
View full Mixtral 8x22B specs →

Cost Analysis

At current pricing, Mistral Nemo is 6.0x more affordable than Mixtral 8x22B. For a typical enterprise workload processing 100M tokens per month:

Mistral Nemo monthly cost

$30

100M tokens/mo (50/50 in/out)

Mixtral 8x22B monthly cost

$180

100M tokens/mo (50/50 in/out)

The Verdict

Mistral Nemo wins our head-to-head comparison with 3 out of 5 category wins. It's the stronger choice for lightweight tasks, drop-in replacement, though Mixtral 8x22B holds an edge in efficient reasoning, multilingual, coding.

Last compared: March 2026 · Data sourced from public benchmarks and official pricing pages

Frequently Asked Questions

Which is better, Mistral Nemo or Mixtral 8x22B?
In our head-to-head comparison, Mistral Nemo leads in 3 out of 5 categories (arena rank, context window, input pricing, output pricing, and parameters). Mistral Nemo excels at lightweight tasks, drop-in replacement, while Mixtral 8x22B is better suited for efficient reasoning, multilingual, coding. The best choice depends on your specific requirements, budget, and use case.
How does Mistral Nemo pricing compare to Mixtral 8x22B?
Mistral Nemo charges $0.30 per 1M input tokens and $0.30 per 1M output tokens. Mixtral 8x22B charges $0.90 per 1M input tokens and $2.70 per 1M output tokens. Mistral Nemo is the more affordable option, approximately 6.0x 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 Mixtral 8x22B?
Mistral Nemo supports a 128K token context window, while Mixtral 8x22B supports 64K 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 Mixtral 8x22B for free?
Mistral Nemo is a paid API model starting at $0.30 per 1M input tokens. Mixtral 8x22B is a paid API model starting at $0.90 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 Mixtral 8x22B?
Mistral Nemo holds arena rank #27, while Mixtral 8x22B holds rank #16. Mixtral 8x22B 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 Mixtral 8x22B better for coding?
Mistral Nemo's primary strength is lightweight tasks, drop-in replacement. Mixtral 8x22B is specifically optimized for coding tasks. For coding specifically, arena rank and code-specific benchmarks are the best indicators of performance.