DeepSeek-R1 vs Mistral Large 2
Comparing DeepSeek-R1 and Mistral Large 2 across benchmarks, pricing, and capabilities.
DeepSeek · Mistral AI · Updated for 2026
Which is better?
DeepSeek-R1 and Mistral Large 2 trade strengths across price, capabilities, and technical limits. The better choice depends on the workload.
On price, DeepSeek-R1 is roughly 3.1x 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.
Based on current benchmark, pricing, and model metadata for 2026.
Choose DeepSeek-R1
- cost matters — it's about 3.1x cheaper per token
- you process long inputs — it offers a 131,072 token context window
- you want the most recent training data — it shipped Jan 2025
Choose Mistral Large 2
- you want predictable pricing at $2.00/M input and $6.00/M output
At a glance
The differences that matter most.
Performance Benchmarks
Comparative analysis across standard metrics
DeepSeek-R1 and Mistral Large 2don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.
Arena Performance
Playground indexes and blind preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek-R1 ($0.55/1M tokens) is 3.6x cheaper than Mistral Large 2 ($2.00/1M tokens).
For output processing, DeepSeek-R1 ($2.19/1M tokens) is 2.7x cheaper than Mistral Large 2 ($6.00/1M tokens).
In conclusion, Mistral Large 2 is more expensive than DeepSeek-R1.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
DeepSeek-R1 has 548.0B more parameters than Mistral Large 2, making it 445.5% larger.
Context Window
Maximum input and output token capacity
DeepSeek-R1 accepts 131,072 input tokens compared to Mistral Large 2's 128,000 tokens. DeepSeek-R1 can generate longer responses up to 131,072 tokens, while Mistral Large 2 is limited to 128,000 tokens.
License
Usage and distribution terms
DeepSeek-R1 is licensed under MIT, while Mistral Large 2 uses Mistral Research License.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Mistral Research License
Open weights
Release Timeline
When each model was launched
DeepSeek-R1 was released on 2025-01-20, while Mistral Large 2 was released on 2024-07-24.
DeepSeek-R1 is 6 months newer than Mistral Large 2.
Jan 20, 2025
1.6 years ago
6mo newerJul 24, 2024
2.1 years ago
Knowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
DeepSeek-R1 is available from DeepSeek, DeepInfra, Together, Fireworks. Mistral Large 2 is available from Google, Mistral AI.
DeepSeek-R1
Mistral Large 2
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-R1 and Mistral Large 2 side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-R1 vs Mistral Large 2.