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.
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 3.3 70B Instruct | Command A | |
|---|---|---|
Web Site
| ||
Provider
| ||
Chat
| ||
Release Date
| ||
Modalities
| text | text |
API Providers
| Fireworks, Together, DeepInfra, Hyperbolic | Cohere, Hugging Face, Major cloud providers |
Knowledge Cut-off Date
| 12.2024 | - |
Open Source
| Yes | Yes |
Pricing Input
| $0.23 per million tokens | $2.50 per million tokens |
Pricing Output
| $0.40 per million tokens | $10.00 per million tokens |
MMLU
| 86% 0-shot, CoT Source | 85.5% Source |
MMLU-Pro
| 68.9% 5-shot, CoT Source | Not available |
MMMU
| Not available | Not available |
HellaSwag
| Not available | Not available |
HumanEval
| 88.4% pass@1 Source | Not available |
MATH
| 77% 0-shot, CoT Source | 80% Source |
GPQA
| 50.5% 0-shot, CoT Source | 50.8% Source |
IFEval
| 92.1% Source | 90.9% Source |
SimpleQA
| - | - |
AIME 2024 | - | - |
AIME 2025 | - | - |
Aider Polyglot
| - | - |
LiveCodeBench v5
| - | - |
Global MMLU (Lite)
| - | - |
MathVista
| - | - |
Mobile Application | - | - |
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