Llama 3.1 70B Instruct
Zero-eval
#1GSM-8K (CoT)
#1MBPP ++ base version
#1MATH (CoT)
+8 more
by Meta
About
Llama 3.1 70B Instruct is a language model developed by Meta. It achieves strong performance with an average score of 74.7% across 18 benchmarks. It excels particularly in GSM-8K (CoT) (95.1%), ARC-C (94.8%), API-Bank (90.0%). 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.
Pricing Range
Input (per 1M)$0.20 -$5.00
Output (per 1M)$0.20 -$10.00
Providers9
Timeline
AnnouncedJul 23, 2024
ReleasedJul 23, 2024
Specifications
Training Tokens15.0T
License & Family
License
Llama 3.1 Community License
Benchmark Performance Overview
Performance metrics and category breakdown
Overall Performance
18 benchmarks
Average Score
74.7%
Best Score
95.1%
High Performers (80%+)
10Performance Metrics
Max Context Window
256.0KAvg Throughput
213.4 tok/sAvg Latency
0msTop Categories
reasoning
94.8%
math
83.3%
code
76.3%
general
68.7%
Benchmark Performance
Top benchmark scores with normalized values (0-100%)
Ranking Across Benchmarks
Position relative to other models on each benchmark
GSM-8K (CoT)
Rank #1 of 2
#1Llama 3.1 70B Instruct
95.1%
#2Llama 3.1 8B Instruct
84.5%
ARC-C
Rank #4 of 31
#1Nova Pro
94.8%
#2Claude 3 Opus
96.4%
#3Llama 3.1 405B Instruct
96.9%
#4Llama 3.1 70B Instruct
94.8%
#5Claude 3 Sonnet
93.2%
#6Jamba 1.5 Large
93.0%
#7Nova Lite
92.4%
API-Bank
Rank #2 of 3
#1Llama 3.1 405B Instruct
92.0%
#2Llama 3.1 70B Instruct
90.0%
#3Llama 3.1 8B Instruct
82.6%
IFEval
Rank #14 of 37
#11GPT-4.5
88.2%
#12Llama 3.1 405B Instruct
88.6%
#13Qwen3-235B-A22B-Instruct-2507
88.7%
#14Llama 3.1 70B Instruct
87.5%
#15GPT-4.1
87.4%
#16Kimi-k1.5
87.2%
#17Nova Micro
87.2%
Multilingual MGSM (CoT)
Rank #2 of 3
#1Llama 3.1 405B Instruct
91.6%
#2Llama 3.1 70B Instruct
86.9%
#3Llama 3.1 8B Instruct
68.9%
All Benchmark Results for Llama 3.1 70B Instruct
Complete list of benchmark scores with detailed information
GSM-8K (CoT) GSM-8K (CoT) benchmark | math | text | 0.95 | 95.1% | Self-reported |
ARC-C ARC-C benchmark | reasoning | text | 0.95 | 94.8% | Self-reported |
API-Bank API-Bank benchmark | general | text | 0.90 | 90.0% | Self-reported |
IFEval IFEval benchmark | code | text | 0.88 | 87.5% | Self-reported |
Multilingual MGSM (CoT) Multilingual MGSM (CoT) benchmark | math | text | 0.87 | 86.9% | Self-reported |
MBPP ++ base version MBPP ++ base version benchmark | code | text | 0.86 | 86.0% | Self-reported |
MMLU (CoT) MMLU (CoT) benchmark | general | text | 0.86 | 86.0% | Self-reported |
BFCL BFCL benchmark | general | text | 0.85 | 84.8% | Self-reported |
MMLU MMLU benchmark | general | text | 0.84 | 83.6% | Self-reported |
HumanEval HumanEval benchmark | code | text | 0.81 | 80.5% | Self-reported |
Showing 1 to 10 of 18 benchmarks