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Meta: Llama 4 Scout vs Mistral: Devstral Small 1.1

Head-to-head API cost, context, and performance comparison. Synced at 5:02:07 PM.

Executive Summary

When evaluating Meta: Llama 4 Scout against Mistral: Devstral Small 1.1, the pricing structure is a key differentiator. Meta: Llama 4 Scout is approximately 5% more cost-effective per 1 million tokens overall.

However, when looking at raw reasoning capabilities, Mistral: Devstral Small 1.1 leads with a statistical ELO score of 1059. For tasks involving complex logic, coding, or instruction-following, developers might prefer Mistral: Devstral Small 1.1, provided their budget allows for the API burn rate.

Raw Technical comparison

Metric
Meta: Llama 4 Scout
Mistral: Devstral Small 1.1
Performance (ELO)
1059
1059
Input Cost / 1M
$0.08
$0.10
Output Cost / 1M
$0.30
$0.30
Context Window
327,680 tokens
131,072 tokens

Verdict

If you are looking for pure performance and capability, Tie is statistically superior. However, if API burn rate is the primary concern, Meta: Llama 4 Scout wins out aggressively in pricing.

People Also Ask

Is Meta: Llama 4 Scout cheaper than Mistral: Devstral Small 1.1?

Yes. Meta: Llama 4 Scout is cheaper for both input and output generation compared to Mistral: Devstral Small 1.1. Exploring alternatives often yields cost reductions.

Which model has the larger context window?

The Meta: Llama 4 Scout model has the advantage in memory, offering a massive 327,680 token limit for document ingestion.

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