Llama 3.1 Instruct 405B
MetaLlama開源權重Llama 3.1 Community License
描述
Llama 3.1 405B Instruct is a large language model optimized for multilingual dialogue use cases. It outperforms many available open source and closed chat models on common industry benchmarks. The model supports 8 languages and has a 128K token context length.
發布日期
2024-07-23
參數規模
405.0B
上下文長度
—
支援模態
text
能力雷達圖
27
general
30
coding
23
reasoning
34
science
70
agents
0
multimodal
排行榜排名
基準測試分數 (LLM Stats)
(LLM Stats (zeroeval))Biology
GPQANYU + Cohere + Anthropic (2023)
50.7%自報
Code
HumanEvalOpenAI (2021)
89.0%自報
Gorilla Benchmark API Bench
35.3%自報
Finance
MMLU (CoT)
88.6%自報
MMLU
87.3%自報
MMLU-Pro
73.3%自報
General
ARC-C
96.9%自報
MBPP EvalPlus
88.6%自報
IFEvalGoogle Research (2023)
88.6%自報
BFCL
88.5%自報
Multipl-E HumanEval
75.2%自報
Multipl-E MBPP
65.7%自報
Nexus
58.7%自報
Math
GSM8k
96.8%自報
Multilingual MGSM (CoT)
91.6%自報
DROP
84.8%自報
MATH
73.8%自報
Reasoning
API-Bank
92.0%自報
AA 評測指數
(Artificial Analysis)Intelligence Index(Artificial Analysis)8.3
Math Index(Artificial Analysis)3.0
Mmlu Pro(TIGER-Lab (Univ. of Waterloo, Toronto, CMU, 2024))0.7
Math 500(OpenAI (2024), subset of Hendrycks et al. MATH (2021))0.7
Gpqa(NYU + Cohere + Anthropic (2023))0.5
Ifbench(Google Research (2023))0.4
Livecodebench(UC Berkeley + MIT + Cornell (2024))0.3
Scicode(UIUC + Argonne National Lab (2024))0.3
Lcr(Artificial Analysis)0.2
Aime(MAA (Mathematical Association of America))0.2
Tau2(Sierra + U Toronto + Vector Institute (2025))0.2
Terminalbench Hard(Stanford × Laude Institute (2026))0.1
Hle(Center for AI Safety + Scale AI (2025))0.0
Aime 25(MAA (Mathematical Association of America))0.0
LLM Stats 分類評分
(LLM Stats (zeroeval))Math90
Structured Output90
Instruction Following90
Legal80
Reasoning80
Language80
Finance80
General80
Healthcare80
Tool Calling70
Code60
Physics50
Biology50
Chemistry50
定價
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輸出價格免費
混合價格(3:1)免費
速度
Tokens/秒0.0
首Token延遲0.00s
首回答延遲0.00s
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