DeepSeek-R1 is a 671B parameter Mixture-of-Experts (MoE) model with 37B activated parameters per token, trained via large-scale reinforcement learning with a focus on reasoning capabilities. It incorporates two RL stages for discovering improved reasoning patterns and aligning with human preferences, along with two SFT stages for seeding reasoning and non-reasoning capabilities. The model achieves performance comparable to OpenAI-o1 across math, code, and reasoning tasks.
Mistral Large 2, developed by Mistral, offers a 128K-token context window and is priced at $3.00 per million input tokens and $9.00 per million output tokens. Released on July 24, 2024, the model scored 84.0 on the MMLU benchmark in a 5-shot evaluation, demonstrating strong performance in diverse tasks.
| DeepSeek-R1 | Mistral Large 2 | |
|---|---|---|
Provider | ||
Web Site | ||
Release Date | Jan 21, 2025 3 months ago | Jun 24, 2024 9 months ago |
Modalities | text | text |
API Providers | DeepSeek, HuggingFace | Azure AI, AWS Bedrock, Google AI Studio, Vertex AI, Snowflake Cortex |
Knowledge Cut-off Date | Unknown | Unknown |
Open Source | Yes | Yes |
Pricing Input | $0.55 per million tokens | $3.00 per million tokens |
Pricing Output | $2.19 per million tokens | $9.00 per million tokens |
MMLU | 90.8% Pass@1 Source | 84% 5-shot Source |
MMLU Pro | 84% EM Source | 50.69% Source |
MMMU | - | Not available |
HellaSwag | - | Not available |
HumanEval | - | Not available |
MATH | - | 1.13% Source |
GPQA | 71.5% Pass@1 Source | 24.94% |
IFEval | 83.3% Prompt Strict Source | 84.01% |
Mobile Application | - |
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