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AITier

Qwen2.5 Instruct 72B

AlibabaQwen開源權重Qwen · 商用許可

描述

Qwen2.5-72B-Instruct is an instruction-tuned 72 billion parameter language model, part of the Qwen2.5 series. It is designed to follow instructions, generate long texts (over 8K tokens), understand structured data (e.g., tables), and generate structured outputs, especially JSON. The model supports multilingual capabilities across over 29 languages.

發布日期
2024-09-19
參數規模
72.7B
上下文長度
131K
支援模態
text

能力雷達圖

27
general
27
coding
29
reasoning
32
science
28
agents
0
multimodal

排行榜排名

領域#排名分數來源
程式碼能力榜428
20.0
AA
通用能力榜373
35.0
AA
科學能力421
32.0
AA

基準測試分數 (LLM Stats)

(LLM Stats (zeroeval))

Biology

GPQANYU + Cohere + Anthropic (2023)49.0%自報

Code

HumanEvalOpenAI (2021)86.6%自報
LiveCodeBench55.5%自報

Communication

MT-Bench0.94 / 100自報

Creativity

AlignBench81.6%自報
Arena Hard81.2%自報

Finance

MMLU-Pro71.1%自報

General

MBPP0.88 / 100自報
MMLU-Redux86.8%自報
IFEvalGoogle Research (2023)84.1%自報
MultiPL-E75.1%自報
LiveBench52.3%自報

Math

GSM8k95.8%自報
MATH83.1%自報

AA 評測指數

(Artificial Analysis)
Math Index(Artificial Analysis)
14.0
Intelligence Index(Artificial Analysis)
9.4
Math 500(OpenAI (2024), subset of Hendrycks et al. MATH (2021))
0.9
Mmlu Pro(TIGER-Lab (Univ. of Waterloo, Toronto, CMU, 2024))
0.7
Gpqa(NYU + Cohere + Anthropic (2023))
0.5
Ifbench(Google Research (2023))
0.4
Tau2(Sierra + U Toronto + Vector Institute (2025))
0.3
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
Aime 25(MAA (Mathematical Association of America))
0.1
Terminalbench Hard(Stanford × Laude Institute (2026))
0.0
Hle(Center for AI Safety + Scale AI (2025))
0.0

LLM Stats 分類評分

(LLM Stats (zeroeval))
Roleplay
90
Communication
90
Creativity
90
Math
80
Reasoning
80
Structured Output
80
Instruction Following
80
Language
80
General
80
Writing
80
Legal
70
Finance
70
Healthcare
70
Code
70
Physics
50
Biology
50
Chemistry
50

定價

輸入價格$0.475 / 1M tokens
輸出價格$0.495 / 1M tokens
混合價格(3:1)$0.48 / 1M tokens

速度

Tokens/秒0.0
首Token延遲0.00s
首回答延遲0.00s

供應商價格排行

供應商價格排行

2 個供應商

最便宜: Alibaba最貴: Alibaba (China)
供應商輸入輸出
1Alibaba主要
$0.475
$0.495
2Alibaba (China)
$0.574
$1.721

比較該模型在不同 API 供應商之間的定價。

外部連結

LLM StatsArtificial Analysis