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.
Llama 3.3 70B Instruct, created by Meta, is a multilingual large language model specifically fine-tuned for instruction-based tasks and optimized for conversational applications. It is capable of processing and generating text in multiple languages, with a context window supporting up to 128,000 tokens. Launched on December 6, 2024, the model surpasses numerous open-source and proprietary chat models in various industry benchmarks. It utilizes Grouped-Query Attention (GQA) to improve scalability and has been trained on a diverse dataset comprising over 15 trillion tokens from publicly available sources. The model's knowledge is current up to December 2023.
| DeepSeek-R1 | Llama 3.3 70B Instruct | |
|---|---|---|
Provider | ||
Web Site | ||
Release Date | Jan 21, 2025 3 months ago | Dec 06, 2024 4 months ago |
Modalities | text | text |
API Providers | DeepSeek, HuggingFace | Fireworks, Together, DeepInfra, Hyperbolic |
Knowledge Cut-off Date | Unknown | 12.2024 |
Open Source | Yes | Yes |
Pricing Input | $0.55 per million tokens | $0.23 per million tokens |
Pricing Output | $2.19 per million tokens | $0.40 per million tokens |
MMLU | 90.8% Pass@1 Source | 86% 0-shot, CoT Source |
MMLU Pro | 84% EM Source | 68.9% 5-shot, CoT Source |
MMMU | - | Not available |
HellaSwag | - | Not available |
HumanEval | - | 88.4% pass@1 Source |
MATH | - | 77% 0-shot, CoT Source |
GPQA | 71.5% Pass@1 Source | 50.5% 0-shot, CoT Source |
IFEval | 83.3% Prompt Strict Source | 92.1% Source |
Mobile Application | - |
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