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.
NVIDIA's Llama 3.1 Nemotron 70B is a powerful language model optimized for delivering accurate and informative responses. Built on the Llama 3.1 70B architecture and enhanced with Reinforcement Learning from Human Feedback (RLHF),it achieves top performance in automatic alignment benchmarks. Designed for applications demanding high precision in response generation and helpfulness, this model is well-suited for a wide range of user queries across multiple domains.
| Llama 3.3 70B Instruct | Llama 3.1 Nemotron 70B Instruct | |
|---|---|---|
Web Site
| ||
Provider
| ||
Chat
| ||
Release Date
| ||
Modalities
| text | text |
API Providers
| Fireworks, Together, DeepInfra, Hyperbolic | OpenRouter |
Knowledge Cut-off Date
| 12.2024 | - |
Open Source
| Yes | Yes |
Pricing Input
| $0.23 per million tokens | $0.35 per million tokens |
Pricing Output
| $0.40 per million tokens | $0.40 per million tokens |
MMLU
| 86% 0-shot, CoT Source | 85% 5-shot 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 | 75% Source |
MATH
| 77% 0-shot, CoT Source | 71% Source |
GPQA
| 50.5% 0-shot, CoT Source | Not available |
IFEval
| 92.1% Source | Not available |
SimpleQA
| - | - |
AIME 2024 | - | - |
AIME 2025 | - | - |
Aider Polyglot
| - | - |
LiveCodeBench v5
| - | - |
Global MMLU (Lite)
| - | - |
MathVista
| - | - |
Mobile Application | - | - |
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