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Llama 3.1 Instruct 405B

MetaLlama开源权重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.

发布日期
2024-07-23
参数规模
405.0B
上下文长度
—
支持模态
text

能力雷达图

27
general
31
coding
23
reasoning
37
science
70
agents
0
multimodal

排行榜排名

领域#排名分数来源
代码能力榜472
24.0
AA
通用能力榜453
31.0
AA
科学能力494
27.0
AA

基准测试分数 (LLM Stats)

(LLM Stats (zeroeval))

Chat

IFEvalGoogle Research (2023)88.6%自报

General

BFCL88.5%自报
MMLU87.3%自报
Multipl-E MBPP65.7%自报
Nexus58.7%自报

Language

MMLU (CoT)88.6%自报
Multipl-E HumanEval75.2%自报
MMLU-Pro73.3%自报

Math

GSM8k96.8%自报
Multilingual MGSM (CoT)91.6%自报
MATH73.8%自报

Reasoning

ARC-C96.9%自报
API-Bank92.0%自报
HumanEvalOpenAI (2021)89.0%自报
MBPP EvalPlus88.6%自报
DROP84.8%自报
GPQANYU + Cohere + Anthropic (2023)50.7%自报
Gorilla Benchmark API Bench35.3%自报

AA 评测指数

(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 分类评分

(LLM Stats (zeroeval))
Chat
90
Instruction Following
90
Math
90
Structured Output
90
Language
80
Legal
80
Reasoning
80
Finance
80
General
80
Healthcare
80
Tool Calling
70
Code
60
Physics
50
Biology
50
Chemistry
50

定价

输入价格免费
输出价格免费
混合价格(3:1)免费

速度

Tokens/秒0.0
首Token延迟0.00s
首回答延迟0.00s

供应商价格排行

暂无提供商数据

外部链接