Model Comparison
DeepSeek-R1 vs Mistral Small 3 24B InstructWhich is better in 2026?
Comparing DeepSeek-R1 and Mistral Small 3 24B Instruct across benchmarks, pricing, and capabilities.
Verdict: DeepSeek-R1 vs Mistral Small 3 24B Instruct — which is better?
DeepSeek-R1 (by DeepSeek) and Mistral Small 3 24B Instruct (by Mistral AI) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.
On price, Mistral Small 3 24B Instruct is roughly 11.0x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
DeepSeek-R1 also accepts a larger context window (131,072 input tokens), making it the stronger choice for long documents and large codebases.
Choose DeepSeek-R1 if…
- you process long inputs — it offers a 131,072 token context window
Choose Mistral Small 3 24B Instruct if…
- cost matters — it's about 11.0x cheaper per token
- you want the most recent training data — it shipped Jan 2025
Performance Benchmarks
Comparative analysis across standard metrics
DeepSeek-R1 and Mistral Small 3 24B Instructdon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek-R1 ($0.55/1M tokens) is 7.9x more expensive than Mistral Small 3 24B Instruct ($0.07/1M tokens).
For output processing, DeepSeek-R1 ($2.19/1M tokens) is 15.6x more expensive than Mistral Small 3 24B Instruct ($0.14/1M tokens).
In conclusion, DeepSeek-R1 is more expensive than Mistral Small 3 24B Instruct.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
DeepSeek-R1 has 647.0B more parameters than Mistral Small 3 24B Instruct, making it 2695.8% larger.
Context Window
Maximum input and output token capacity
DeepSeek-R1 accepts 131,072 input tokens compared to Mistral Small 3 24B Instruct's 32,000 tokens. DeepSeek-R1 can generate longer responses up to 131,072 tokens, while Mistral Small 3 24B Instruct is limited to 32,000 tokens.
License
Usage and distribution terms
DeepSeek-R1 is licensed under MIT, while Mistral Small 3 24B Instruct uses Apache 2.0.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Apache 2.0
Open weights
Release Timeline
When each model was launched
DeepSeek-R1 was released on 2025-01-20, while Mistral Small 3 24B Instruct was released on 2025-01-30.
Mistral Small 3 24B Instruct is 0 month newer than DeepSeek-R1.
Jan 20, 2025
1.4 years ago
Jan 30, 2025
1.4 years ago
1w newerKnowledge Cutoff
When training data ends
Mistral Small 3 24B Instruct has a documented knowledge cutoff of 2023-10-01, while DeepSeek-R1's cutoff date is not specified.
We can confirm Mistral Small 3 24B Instruct's training data extends to 2023-10-01, but cannot make a direct comparison without DeepSeek-R1's cutoff date.
—
Oct 2023
Provider Availability
DeepSeek-R1 is available from DeepSeek, DeepInfra, Together, Fireworks. Mistral Small 3 24B Instruct is available from DeepInfra, Mistral AI.
DeepSeek-R1
Mistral Small 3 24B Instruct
Outputs Comparison
Key Takeaways
DeepSeek-R1
View detailsDeepSeek
Mistral Small 3 24B Instruct
View detailsMistral AI
Detailed Comparison
Interactive Arena
Judge for yourself.
Run your own prompts against DeepSeek-R1 and Mistral Small 3 24B Instruct side-by-side, then vote on the output you prefer.
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FAQ
Common questions about DeepSeek-R1 vs Mistral Small 3 24B Instruct.