Llama 3.1 Instruct 405B
MetaLlama오픈 웨이트Llama 3.1 Community License
설명
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.
출시일
2024-07-23
파라미터
405.0B
컨텍스트 길이
—
모달리티
text
능력 레이더
27
general
31
coding
23
reasoning
37
science
70
agents
0
multimodal
랭킹
벤치마크 점수 (LLM Stats)
(LLM Stats (zeroeval))Chat
IFEvalGoogle Research (2023)
88.6%자체 보고
General
BFCL
88.5%자체 보고
MMLU
87.3%자체 보고
Multipl-E MBPP
65.7%자체 보고
Nexus
58.7%자체 보고
Language
MMLU (CoT)
88.6%자체 보고
Multipl-E HumanEval
75.2%자체 보고
MMLU-Pro
73.3%자체 보고
Math
GSM8k
96.8%자체 보고
Multilingual MGSM (CoT)
91.6%자체 보고
MATH
73.8%자체 보고
Reasoning
ARC-C
96.9%자체 보고
API-Bank
92.0%자체 보고
HumanEvalOpenAI (2021)
89.0%자체 보고
MBPP EvalPlus
88.6%자체 보고
DROP
84.8%자체 보고
GPQANYU + Cohere + Anthropic (2023)
50.7%자체 보고
Gorilla Benchmark API Bench
35.3%자체 보고
AA 평가 지수
(Artificial Analysis)Mmlu Pro(TIGER-Lab (Univ. of Waterloo, Toronto, CMU, 2024))73.2
Math 500(OpenAI (2024), subset of Hendrycks et al. MATH (2021))70.3
Gpqa(NYU + Cohere + Anthropic (2023))51.5
Ifbench(Google Research (2023))39.0
Livecodebench(UC Berkeley + MIT + Cornell (2024))30.5
Lcr(Artificial Analysis)25.3
Aime(MAA (Mathematical Association of America))21.3
Tau2(Sierra + U Toronto + Vector Institute (2025))19.0
Intelligence Index(Artificial Analysis)7.3
Terminalbench Hard(Stanford × Laude Institute (2026))6.8
Hle(Center for AI Safety + Scale AI (2025))4.0
Math Index(Artificial Analysis)3.0
Aime 25(MAA (Mathematical Association of America))3.0
LLM Stats 카테고리 점수
(LLM Stats (zeroeval))Chat90
Instruction Following90
Math90
Structured Output90
Language80
Legal80
Reasoning80
Finance80
General80
Healthcare80
Tool Calling70
Code60
Physics50
Biology50
Chemistry50
가격
입력 가격무료
출력 가격무료
혼합 가격 (3:1)무료
속도
토큰/초0.0
첫 토큰 지연0.00s
첫 응답 지연0.00s
공급자 가격 순위
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