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.
Command R+ is Cohere’s cutting-edge generative AI model, engineered for enterprise-grade performance where speed, security, and output quality are critical. Designed to run efficiently with minimal infrastructure, it outperforms top-tier models like GPT-4o and DeepSeek-V3 in both capability and cost-effectiveness. Featuring an extended 256K token context window—twice as large as most leading models—it excels at complex multilingual and agent-based tasks essential for modern business operations. Despite its power, it can be deployed on just two GPUs, making it highly accessible. With blazing-fast throughput of up to 156 tokens per second—about 1.75x faster than GPT-4o—Command R+ delivers exceptional efficiency without compromising accuracy or depth.
| Llama 4 Scout | Command A | |
|---|---|---|
Web Site
| ||
Provider
| ||
Chat
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Release Date
| ||
Modalities
| text images video | text |
API Providers
| Meta AI, Hugging Face, Fireworks, Together, DeepInfra | Cohere, Hugging Face, Major cloud providers |
Knowledge Cut-off Date
| 2025-04 | - |
Open Source
| Yes (Source) | Yes |
Pricing Input
| Not available | $2.50 per million tokens |
Pricing Output
| Not available | $10.00 per million tokens |
MMLU
| Not available | 85.5% Source |
MMLU-Pro
| 74.3% Reasoning & Knowledge Source | Not available |
MMMU
| 69.4% Image Reasoning Source | Not available |
HellaSwag
| Not available | Not available |
HumanEval
| Not available | Not available |
MATH
| Not available | 80% Source |
GPQA
| 57.2% Diamond Source | 50.8% Source |
IFEval
| Not available | 90.9% Source |
SimpleQA
| - | - |
AIME 2024 | - | - |
AIME 2025 | - | - |
Aider Polyglot
| - | - |
LiveCodeBench v5
| - | - |
Global MMLU (Lite)
| - | - |
MathVista
| - | - |
Mobile Application | - | - |
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