Llama 3.3 70B Instruct
Zero-eval
#1BFCL v2
#2MBPP EvalPlus
#3IFEval
by Meta
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About
Llama 3.3 70B Instruct is a language model developed by Meta. It achieves strong performance with an average score of 79.9% across 9 benchmarks. It excels particularly in IFEval (92.1%), MGSM (91.1%), HumanEval (88.4%). It supports a 256K token context window for handling large documents. The model is available through 9 API providers. Released in 2024, it represents Meta's latest advancement in AI technology.
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Pricing Range
Input (per 1M)$0.20 -$0.89
Output (per 1M)$0.20 -$7.90
Providers9
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Timeline
AnnouncedDec 6, 2024
ReleasedDec 6, 2024
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Specifications
Training Tokens15.0T
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License & Family
License
Llama 3.3 Community License Agreement
Performance Overview
Performance metrics and category breakdown
Overall Performance
9 benchmarks
Average Score
79.9%
Best Score
92.1%
High Performers (80%+)
5Performance Metrics
Max Context Window
256.0KAvg Throughput
451.9 tok/sAvg Latency
1ms+
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All Benchmark Results for Llama 3.3 70B Instruct
Complete list of benchmark scores with detailed information
| IFEval | text | 0.92 | 92.1% | Self-reported | |
| MGSM | text | 0.91 | 91.1% | Self-reported | |
| HumanEval | text | 0.88 | 88.4% | Self-reported | |
| MBPP EvalPlus | text | 0.88 | 87.6% | Self-reported | |
| MMLU | text | 0.86 | 86.0% | Self-reported | |
| BFCL v2 | text | 0.77 | 77.3% | Self-reported | |
| MATH | text | 0.77 | 77.0% | Self-reported | |
| MMLU-Pro | text | 0.69 | 68.9% | Self-reported | |
| GPQA | text | 0.51 | 50.5% | Self-reported |