LLaMA 4 Scout is a 17-billion parameter model leveraging a Mixture-of-Experts architecture with 16 active experts, positioning it as the top multimodal model in its category. It consistently outperforms competitors like Gemma 3, Gemini 2.0 Flash-Lite, and Mistral 3.1 across diverse benchmark tasks. Despite its performance, LLaMA 4 Scout is remarkably efficient—capable of running on a single NVIDIA H100 GPU with Int4 quantization. It also boasts an industry-leading 10 million token context window and is natively multimodal, seamlessly processing text, images, and video inputs for advanced real-world applications.
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 4 Scout | DeepSeek-R1 | |
|---|---|---|
Provider | ||
Web Site | ||
Release Date | Apr 05, 2025 2 weeks ago | Jan 21, 2025 3 months ago |
Modalities | text images video | text |
API Providers | Meta AI, Hugging Face, Fireworks, Together, DeepInfra | DeepSeek, HuggingFace |
Knowledge Cut-off Date | 2025-04 | Unknown |
Open Source | Yes (Source) | Yes |
Pricing Input | Not available | $0.55 per million tokens |
Pricing Output | Not available | $2.19 per million tokens |
MMLU | Not available | 90.8% Pass@1 Source |
MMLU Pro | 74.3% Reasoning & Knowledge Source | 84% EM Source |
MMMU | 69.4% Image Reasoning Source | - |
HellaSwag | Not available | - |
HumanEval | Not available | - |
MATH | Not available | - |
GPQA | 57.2% Diamond Source | 71.5% Pass@1 Source |
IFEval | Not available | 83.3% Prompt Strict Source |
Mobile Application | - |
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