1
A
claude-opus-4-6
claude-opus-4-6Anthropic
100.0
7.1K
1M
¥36 / ¥180输入/输出
对话 · 文本 · 商业、管理与金融排行榜
基于公开偏好评测数据展示 文本 / 商业、管理与金融 榜单，每个榜单独立排序。
商业、管理与金融模型怎么选？
商业、管理与金融排行榜用于回答“商业、管理与金融哪个 AI 模型更强”这类选型问题。页面基于公开偏好评测数据展示模型排名，每个榜单独立排序，不把不同任务的原始分数直接混合。当前榜首是 claude-opus-4-6，厂商为 anthropic，百分制分数 100.0，样本量 7.1K。 数据来源保留 Arena 原始榜单和 LMArena leaderboard dataset，更新时间以榜单发布时间 2026-05-27 为准。
claude-opus-4-6claude-opus-4-6-thinkingclaude-opus-4-7-thinkinggpt-5.5-highgpt-5.5
2
Aclaude-opus-4-6-thinking
claude-opus-4-6-thinkingAnthropic
99.7
6.6K
1M
¥36 / ¥180输入/输出
3
Aclaude-opus-4-7-thinking
claude-opus-4-7-thinkingAnthropic
99.4
3.9K
1M
¥36 / ¥180输入/输出
4
O
gpt-5.5-high
gpt-5.5-highOpenai
99.1
3.2K
1.05M
¥36 / ¥216输入/输出
5
Ogpt-5.5
gpt-5.5Openai
98.9
3.2K
1.05M
¥36 / ¥216输入/输出
6
Aclaude-opus-4-7
claude-opus-4-7Anthropic
98.6
4.1K
1M
¥36 / ¥180输入/输出
7
Ogpt-5.4-high
gpt-5.4-highOpenai
98.3
5.5K
1.05M
¥18 / ¥108输入/输出
8
B
ernie-5.1
ernie-5.1Baidu
98.0
2.8K
119K
¥5.4 / ¥21.6输入/输出
9
Ogpt-5.4
gpt-5.4Openai
97.7
5.9K
1.05M
¥18 / ¥108输入/输出
10
M
muse-spark
muse-sparkMeta
97.4
2.4K
-
-
11
G
gemini-3.1-pro-preview
gemini-3.1-pro-previewGoogle
97.2
8.4K
1.05M
¥14.4 / ¥86.4输入/输出
12
Ggemini-3-pro
gemini-3-proGoogle
96.9
7.6K
1.05M
¥14.4 / ¥86.4输入/输出
13
A
qwen3.5-max-preview
qwen3.5-max-previewAlibaba
96.6
4K
-
-
14
Aclaude-sonnet-4-6
claude-sonnet-4-6Anthropic
96.3
5.3K
1M
¥21.6 / ¥108输入/输出
15
MI
mimo-v2.5-pro
mimo-v2.5-proXiaomi
96.0
3.1K
1.05M
¥7.2 / ¥21.6输入/输出
16
Ggemini-3.5-flash
gemini-3.5-flashGoogle
95.7
1.8K
1.05M
¥10.8 / ¥64.8输入/输出
17
A
amazon-nova-experimental-chat-26-02-10
amazon-nova-experimental-chat-26-02-10Amazon
95.5
602
-
-
18
Ggemini-3-flash
gemini-3-flashGoogle
95.2
5.6K
1.05M
¥3.6 / ¥21.6输入/输出
19
M
kimi-k2.6
kimi-k2.6Moonshot
94.9
3.1K
262K
¥6.84 / ¥28.8输入/输出
20
Aqwen3.7-max-preview
qwen3.7-max-previewAlibaba
94.6
838
1M
¥18 / ¥54输入/输出
21
Aclaude-opus-4-5-20251101
claude-opus-4-5-20251101Anthropic
94.3
12.5K
200K
¥36 / ¥180输入/输出
22
Z
glm-5.1
glm-5.1Zai
94.0
2.8K
200K
¥0 / ¥0输入/输出
23
Ggemini-2.5-pro
gemini-2.5-proGoogle
93.8
22K
1.05M
¥9 / ¥72输入/输出
24
Aclaude-sonnet-4-5-20250929
claude-sonnet-4-5-20250929Anthropic
93.5
14.4K
200K
¥21.6 / ¥108输入/输出
25
B
dola-seed-2.0-pro
dola-seed-2.0-proBytedance
93.2
7.1K
-
-
26
MImimo-v2-pro
mimo-v2-proXiaomi
92.9
4.4K
1.05M
¥7.2 / ¥21.6输入/输出
27
Aqwen3-max-preview
qwen3-max-previewAlibaba
92.6
5.2K
262K
¥6.2 / ¥24.8输入/输出
28
D
deepseek-v4-pro
deepseek-v4-proDeepseek
92.3
3.3K
1M
¥3.13 / ¥6.26输入/输出
29
Aqwen3.6-plus
qwen3.6-plusAlibaba
92.0
3.7K
1M
¥3.6 / ¥21.6输入/输出
30
Ggemma-4-26b-a4b
gemma-4-26b-a4bGoogle
91.8
1K
262K
¥0.94 / ¥2.88输入/输出
31
X
grok-4.20-beta-0309-reasoning
grok-4.20-beta-0309-reasoningXai
91.5
5.7K
2M
¥14.4 / ¥43.2输入/输出
32
Aqwen3.5-397b-a17b
qwen3.5-397b-a17bAlibaba
91.2
6.1K
262K
¥3.1 / ¥18.6输入/输出
33
Ogpt-5.2-chat-latest-20260210
gpt-5.2-chat-latest-20260210Openai
90.9
6.2K
400K
¥12.6 / ¥101输入/输出
34
Aclaude-opus-4-5-20251101-thinking-32k
claude-opus-4-5-20251101-thinking-32kAnthropic
90.6
6.9K
200K
¥108 / ¥540输入/输出
35
Ddeepseek-v4-pro-thinking
deepseek-v4-pro-thinkingDeepseek
90.3
3.2K
1M
¥3.13 / ¥6.26输入/输出
36
Aqwen3-vl-235b-a22b-instruct
qwen3-vl-235b-a22b-instructAlibaba
90.1
2.2K
128K
¥2.16 / ¥8.64输入/输出
37
Ogpt-5.1-high
gpt-5.1-highOpenai
89.8
7.6K
400K
¥9 / ¥72输入/输出
38
Bernie-5.0-0110
ernie-5.0-0110Baidu
89.5
6.5K
128K
¥7.92 / ¥14.4输入/输出
39
Aclaude-sonnet-4-5-20250929-thinking-32k
claude-sonnet-4-5-20250929-thinking-32kAnthropic
89.2
14.7K
200K
¥21.6 / ¥108输入/输出
40
MImimo-v2.5
mimo-v2.5Xiaomi
88.9
3.2K
1.05M
¥2.88 / ¥14.4输入/输出
41
Zglm-4.7
glm-4.7Zai
88.6
2.2K
205K
¥0 / ¥0输入/输出
42
Zglm-5
glm-5Zai
88.4
4.3K
205K
¥7.2 / ¥23输入/输出
43
M
longcat-flash-chat
longcat-flash-chatMeituan
88.1
2.2K
128K
¥1.08 / ¥10.8输入/输出
44
Ggemini-3-flash (thinking-minimal)
gemini-3-flash (thinking-minimal)Google
87.8
10.2K
1.05M
¥3.6 / ¥21.6输入/输出
45
Aqwen3.6-max-preview
qwen3.6-max-previewAlibaba
87.5
883
246K
¥9.5 / ¥56.9输入/输出
46
Mkimi-k2.5-thinking
kimi-k2.5-thinkingMoonshot
87.2
7K
262K
¥4.32 / ¥21.6输入/输出
47
Xgrok-4.20-beta1
grok-4.20-beta1Xai
86.9
4.6K
2M
¥14.4 / ¥43.2输入/输出
48
Ggemma-4-31b
gemma-4-31bGoogle
86.6
1.1K
262K
¥3.24 / ¥7.2输入/输出
49
Xgrok-4.1
grok-4.1Xai
86.4
12.3K
200K
¥14.4 / ¥72输入/输出
50
Ochatgpt-4o-latest-20250326
chatgpt-4o-latest-20250326Openai
86.1
13.6K
128K
¥18 / ¥72输入/输出
51
MA
mistral-large-3
mistral-large-3Mistral
85.8
7.9K
262K
¥3.6 / ¥10.8输入/输出
52
Aamazon-nova-experimental-chat-12-10
amazon-nova-experimental-chat-12-10Amazon
85.5
594
-
-
53
Xgrok-4.20-multi-agent-beta-0309
grok-4.20-multi-agent-beta-0309Xai
85.2
5.5K
2M
¥14.4 / ¥43.2输入/输出
54
Aqwen3-next-80b-a3b-instruct
qwen3-next-80b-a3b-instructAlibaba
84.9
4.3K
131K
¥1.04 / ¥4.13输入/输出
55
Bernie-5.0-preview-1203
ernie-5.0-preview-1203Baidu
84.7
1.9K
128K
¥7.92 / ¥14.4输入/输出
56
Zglm-4.5
glm-4.5Zai
84.4
4.3K
131K
¥4.32 / ¥15.8输入/输出
57
MImimo-v2-omni
mimo-v2-omniXiaomi
84.1
595
262K
¥2.88 / ¥14.4输入/输出
58
Ogpt-5.1
gpt-5.1Openai
83.8
8.1K
400K
¥9 / ¥72输入/输出
59
Ogpt-5.4-mini-high
gpt-5.4-mini-highOpenai
83.5
5.3K
400K
¥5.4 / ¥32.4输入/输出
60
MAmistral-medium-2508
mistral-medium-2508Mistral
83.2
17K
262K
¥2.88 / ¥14.4输入/输出
61
Aamazon-nova-experimental-chat-11-10
amazon-nova-experimental-chat-11-10Amazon
83.0
4.7K
-
-
62
Zglm-4.6
glm-4.6Zai
82.7
6.8K
205K
¥4.32 / ¥15.8输入/输出
63
Xgrok-4.1-thinking
grok-4.1-thinkingXai
82.4
12.1K
200K
¥14.4 / ¥72输入/输出
64
Aqwen3-235b-a22b-instruct-2507
qwen3-235b-a22b-instruct-2507Alibaba
82.1
17.5K
128K
¥2.09 / ¥8.23输入/输出
65
Bernie-5.0-preview-1022
ernie-5.0-preview-1022Baidu
81.8
921
128K
¥7.92 / ¥14.4输入/输出
66
Ogpt-5.2-high
gpt-5.2-highOpenai
81.5
9K
400K
¥12.6 / ¥101输入/输出
67
Mlongcat-flash-chat-2602-exp
longcat-flash-chat-2602-expMeituan
81.3
4.6K
128K
¥1.08 / ¥10.8输入/输出
68
Aqwen3.5-122b-a10b
qwen3.5-122b-a10bAlibaba
81.0
5K
262K
¥2.88 / ¥23输入/输出
69
Ddeepseek-v3.2-exp
deepseek-v3.2-expDeepseek
80.7
2.2K
128K
¥0 / ¥0输入/输出
70
TE
hunyuan-vision-1.5-thinking
hunyuan-vision-1.5-thinkingTencent
80.4
472
-
-
71
Ddeepseek-v3.1-terminus-thinking
deepseek-v3.1-terminus-thinkingDeepseek
80.1
699
128K
¥1.8 / ¥5.04输入/输出
72
Ddeepseek-v4-flash-thinking
deepseek-v4-flash-thinkingDeepseek
79.8
3.3K
1M
¥1.01 / ¥2.02输入/输出
73
Ddeepseek-v4-flash
deepseek-v4-flashDeepseek
79.5
3.3K
1M
¥1.01 / ¥2.02输入/输出
74
Aqwen3-235b-a22b-thinking-2507
qwen3-235b-a22b-thinking-2507Alibaba
79.3
1.5K
131K
¥2.07 / ¥8.26输入/输出
75
Ogpt-5.2
gpt-5.2Openai
79.0
9K
400K
¥12.6 / ¥101输入/输出
76
Ddeepseek-v3.2
deepseek-v3.2Deepseek
78.7
8.5K
128K
¥2.09 / ¥3.1输入/输出
77
Xgrok-3-preview-02-24
grok-3-preview-02-24Xai
78.4
4K
1M
¥9 / ¥18输入/输出
78
Ogpt-5.5-instant
gpt-5.5-instantOpenai
78.1
5.2K
400K
¥9 / ¥72输入/输出
79
Ddeepseek-v3.1-thinking
deepseek-v3.1-thinkingDeepseek
77.8
1.9K
128K
¥1.44 / ¥5.04输入/输出
80
Ddeepseek-v3.2-thinking
deepseek-v3.2-thinkingDeepseek
77.6
7.7K
128K
¥2.09 / ¥3.1输入/输出
81
Ddeepseek-v3.1
deepseek-v3.1Deepseek
77.3
2.5K
128K
¥1.44 / ¥5.04输入/输出
82
Mkimi-k2.5-instant
kimi-k2.5-instantMoonshot
77.0
1.5K
262K
¥4.32 / ¥21.6输入/输出
83
Aclaude-opus-4-1-20250805
claude-opus-4-1-20250805Anthropic
76.7
13.9K
200K
¥108 / ¥540输入/输出
84
M
minimax-m2.7
minimax-m2.7Minimax
76.4
4.6K
205K
¥0 / ¥0输入/输出
85
Aclaude-opus-4-1-20250805-thinking-16k
claude-opus-4-1-20250805-thinking-16kAnthropic
76.1
9.1K
200K
¥108 / ¥540输入/输出
86
Ggemini-2.5-flash
gemini-2.5-flashGoogle
75.9
21.8K
1.05M
¥2.16 / ¥18输入/输出
87
Aamazon-nova-experimental-chat-10-20
amazon-nova-experimental-chat-10-20Amazon
75.6
2.1K
-
-
88
MImimo-v2-flash (non-thinking)
mimo-v2-flash (non-thinking)Xiaomi
75.3
8.4K
262K
¥0.72 / ¥2.16输入/输出
89
Ddeepseek-r1-0528
deepseek-r1-0528Deepseek
75.0
2.9K
164K
¥3.6 / ¥15.5输入/输出
90
Ogpt-5-chat
gpt-5-chatOpenai
74.7
5.6K
400K
¥9 / ¥72输入/输出
91
TEhunyuan-hy3-preview
hunyuan-hy3-previewTencent
74.4
1.2K
256K
¥0 / ¥0输入/输出
92
Mkimi-k2-thinking-turbo
kimi-k2-thinking-turboMoonshot
74.1
11.4K
262K
¥17.3 / ¥72输入/输出
93
Ggemini-2.5-flash-preview-09-2025
gemini-2.5-flash-preview-09-2025Google
73.9
6.1K
1M
¥2.16 / ¥18输入/输出
94
Aqwen3.5-27b
qwen3.5-27bAlibaba
73.6
4.9K
262K
¥2.16 / ¥17.3输入/输出
95
Aqwen3-max-2025-09-23
qwen3-max-2025-09-23Alibaba
73.3
1.8K
258K
¥6.19 / ¥24.7输入/输出
96
Aclaude-haiku-4-5-20251001
claude-haiku-4-5-20251001Anthropic
73.0
14.8K
200K
¥7.2 / ¥36输入/输出
97
Aqwen3.5-flash
qwen3.5-flashAlibaba
72.7
5.7K
1M
¥1.24 / ¥12.4输入/输出
98
Aqwen3.5-35b-a3b
qwen3.5-35b-a3bAlibaba
72.4
5.4K
262K
¥1.8 / ¥14.4输入/输出
99
Ddeepseek-v3.2-exp-thinking
deepseek-v3.2-exp-thinkingDeepseek
72.2
1.8K
128K
¥0 / ¥0输入/输出
100
ST
step-3.5-flash
step-3.5-flashStepfun
71.9
6.5K
256K
¥0.69 / ¥2.07输入/输出
101
Aamazon-nova-experimental-chat-26-01-10
amazon-nova-experimental-chat-26-01-10Amazon
71.6
603
-
-
102
Xgrok-4-fast-reasoning
grok-4-fast-reasoningXai
71.3
3.7K
2M
¥1.44 / ¥3.6输入/输出
103
Oo3-2025-04-16
o3-2025-04-16Openai
71.0
9.6K
200K
¥14.4 / ¥57.6输入/输出
104
Aqwen3-vl-235b-a22b-thinking
qwen3-vl-235b-a22b-thinkingAlibaba
70.7
1.6K
131K
¥2.06 / ¥8.26输入/输出
105
Aqwen3-235b-a22b-no-thinking
qwen3-235b-a22b-no-thinkingAlibaba
70.5
6.4K
131K
¥2.07 / ¥8.26输入/输出
106
Ggemini-3.1-flash-lite-preview
gemini-3.1-flash-lite-previewGoogle
70.2
6.7K
1.05M
¥1.8 / ¥10.8输入/输出
107
Mminimax-m2.1-preview
minimax-m2.1-previewMinimax
69.9
3.1K
205K
¥0 / ¥0输入/输出
108
Xgrok-4.3
grok-4.3Xai
69.6
3.2K
1M
¥9 / ¥18输入/输出
109
Aqwen3-30b-a3b-instruct-2507
qwen3-30b-a3b-instruct-2507Alibaba
69.3
4.2K
262K
¥2.16 / ¥3.6输入/输出
110
Xgrok-4-0709
grok-4-0709Xai
69.0
7.3K
256K
¥21.6 / ¥108输入/输出
111
MImimo-v2-flash (thinking)
mimo-v2-flash (thinking)Xiaomi
68.8
2.1K
262K
¥0.72 / ¥2.16输入/输出
112
Ddeepseek-v3.1-terminus
deepseek-v3.1-terminusDeepseek
68.5
740
128K
¥1.8 / ¥5.04输入/输出
113
Ogpt-4.5-preview-2025-02-27
gpt-4.5-preview-2025-02-27Openai
68.2
1.4K
8.19K
¥216 / ¥432输入/输出
114
Xgrok-4-1-fast-reasoning
grok-4-1-fast-reasoningXai
67.9
10.3K
2M
¥1.44 / ¥3.6输入/输出
115
Xgrok-4-fast-chat
grok-4-fast-chatXai
67.6
1.2K
2M
¥1.44 / ¥3.6输入/输出
116
TEhunyuan-turbos-20250416
hunyuan-turbos-20250416Tencent
67.3
1.4K
131K
¥0 / ¥0输入/输出
117
Ogpt-5.3-chat-latest
gpt-5.3-chat-latestOpenai
67.0
6K
128K
¥12.6 / ¥101输入/输出
118
Ogpt-5-high
gpt-5-highOpenai
66.8
5.5K
400K
¥9 / ¥72输入/输出
119
Aamazon-nova-experimental-chat-10-09
amazon-nova-experimental-chat-10-09Amazon
66.5
579
-
-
120
Ggemma-3-12b-it
gemma-3-12b-itGoogle
66.2
364
128K
¥1.96 / ¥1.96输入/输出
121
TEhunyuan-t1-20250711
hunyuan-t1-20250711Tencent
65.9
770
131K
¥0 / ¥0输入/输出
122
Zglm-4.5-air
glm-4.5-airZai
65.6
5.5K
131K
¥0 / ¥0输入/输出
123
Ogpt-4.1-2025-04-14
gpt-4.1-2025-04-14Openai
65.3
8.3K
1.05M
¥14.4 / ¥57.6输入/输出
124
Anova-2-lite
nova-2-liteAmazon
65.1
2.3K
128K
¥2.38 / ¥19.8输入/输出
125
Ggemini-2.5-flash-lite-preview-09-2025-no-thinking
gemini-2.5-flash-lite-preview-09-2025-no-thinkingGoogle
64.8
9K
1.05M
¥0.72 / ¥2.88输入/输出
126
NV
nvidia-nemotron-3-super-120b-a12b
nvidia-nemotron-3-super-120b-a12bNvidia
64.5
1.4K
262K
¥1.44 / ¥5.76输入/输出
127
Ogpt-5.4-nano-high
gpt-5.4-nano-highOpenai
64.2
5.1K
400K
¥1.44 / ¥9输入/输出
128
Aqwen3-next-80b-a3b-thinking
qwen3-next-80b-a3b-thinkingAlibaba
63.9
2.5K
131K
¥1.04 / ¥10.3输入/输出
129
Ggemma-3-27b-it
gemma-3-27b-itGoogle
63.6
6.6K
128K
¥2.15 / ¥2.15输入/输出
130
AG
ling-flash-2.0
ling-flash-2.0Ant Group
63.4
1.3K
131K
¥1.01 / ¥4.1输入/输出
131
Ogpt-5-mini-high
gpt-5-mini-highOpenai
63.1
4.8K
400K
¥1.8 / ¥14.4输入/输出
132
Ogpt-oss-120b
gpt-oss-120bOpenai
62.8
5.4K
131K
¥1.08 / ¥4.32输入/输出
133
Zglm-4.6v
glm-4.6vZai
62.5
540
128K
¥2.16 / ¥6.48输入/输出
134
Mminimax-m2.5
minimax-m2.5Minimax
62.2
6.9K
205K
¥0 / ¥0输入/输出
135
Ggemini-2.5-flash-lite-preview-06-17-thinking
gemini-2.5-flash-lite-preview-06-17-thinkingGoogle
61.9
5.5K
65.5K
¥0.72 / ¥2.88输入/输出
136
Mkimi-k2-0905-preview
kimi-k2-0905-previewMoonshot
61.6
2.1K
262K
¥4.32 / ¥18输入/输出
137
MAmistral-medium-2505
mistral-medium-2505Mistral
61.4
5.1K
262K
¥2.88 / ¥14.4输入/输出
138
Ddeepseek-v3-0324
deepseek-v3-0324Deepseek
61.1
6.9K
75K
¥1.44 / ¥5.76输入/输出
139
Aqwen2.5-max
qwen2.5-maxAlibaba
60.8
3.7K
32K
¥11.5 / ¥46输入/输出
140
IA
mercury-2
mercury-2Inception Ai
60.5
478
128K
¥1.8 / ¥5.4输入/输出
141
Aqwen3-235b-a22b
qwen3-235b-a22bAlibaba
60.2
4K
131K
¥2.07 / ¥8.26输入/输出
142
UNintellect-3
-
59.9
985
131K
¥1.44 / ¥7.92输入/输出
143
Ddeepseek-r1
deepseek-r1Deepseek
59.7
1.8K
164K
¥5.04 / ¥18输入/输出
144
NVnvidia-nemotron-3-nano-30b-a3b-bf16
nvidia-nemotron-3-nano-30b-a3b-bf16Nvidia
59.4
2.9K
131K
¥0 / ¥0输入/输出
145
Zglm-4.7-flash
glm-4.7-flashZai
59.1
2.2K
200K
¥0 / ¥0输入/输出
146
Xgrok-3-mini-beta
grok-3-mini-betaXai
58.8
3.6K
1M
¥9 / ¥18输入/输出
147
Aclaude-opus-4-20250514-thinking-16k
claude-opus-4-20250514-thinking-16kAnthropic
58.5
6.1K
200K
¥108 / ¥540输入/输出
148
Aqwen3-coder-480b-a35b-instruct
qwen3-coder-480b-a35b-instructAlibaba
58.2
4.4K
262K
¥6.2 / ¥24.8输入/输出
149
STstep-3
step-3Stepfun
58.0
1.2K
65.5K
¥1.8 / ¥4.68输入/输出
150
Xgrok-3-mini-high
grok-3-mini-highXai
57.7
2.8K
128K
¥0 / ¥0输入/输出
151
Mkimi-k2-0711-preview
kimi-k2-0711-previewMoonshot
57.4
4.6K
131K
¥4.32 / ¥18输入/输出
152
Mminimax-m2
minimax-m2Minimax
57.1
1.3K
197K
¥0 / ¥0输入/输出
153
Ggemini-2.0-flash-001
gemini-2.0-flash-001Google
56.8
5.3K
1.05M
¥1.08 / ¥4.32输入/输出
154
Aclaude-opus-4-20250514
claude-opus-4-20250514Anthropic
56.5
7.2K
200K
¥108 / ¥540输入/输出
155
Ggemini-2.0-flash-lite-preview-02-05
gemini-2.0-flash-lite-preview-02-05Google
56.3
2.4K
1.05M
¥0.54 / ¥2.16输入/输出
156
UNtrinity-large-thinking
-
56.0
4.7K
262K
¥1.8 / ¥6.48输入/输出
157
Oo1-2024-12-17
o1-2024-12-17Openai
55.7
2.7K
128K
¥108 / ¥432输入/输出
158
STstep-1o-turbo-202506
step-1o-turbo-202506Stepfun
55.4
1.4K
-
-
159
MAmistral-small-2506
mistral-small-2506Mistral
55.1
2.9K
262K
¥2.88 / ¥14.4输入/输出
160
Zglm-4-plus-0111
glm-4-plus-0111Zai
54.8
592
128K
¥72 / ¥72输入/输出
161
AGring-flash-2.0
ring-flash-2.0Ant Group
54.5
1.3K
131K
¥1.01 / ¥4.1输入/输出
162
Oo4-mini-2025-04-16
o4-mini-2025-04-16Openai
54.3
7.1K
200K
¥7.92 / ¥31.7输入/输出
163
TEhunyuan-turbos-20250226
hunyuan-turbos-20250226Tencent
54.0
263
131K
¥0 / ¥0输入/输出
164
UNtrinity-large-preview
-
53.7
5.4K
262K
¥1.8 / ¥6.48输入/输出
165
Ogpt-4.1-mini-2025-04-14
gpt-4.1-mini-2025-04-14Openai
53.4
6.1K
1.05M
¥2.88 / ¥11.5输入/输出
166
Aqwq-32b
qwq-32bAlibaba
53.1
3.5K
131K
¥2.07 / ¥6.2输入/输出
167
Mminimax-m1
minimax-m1Minimax
52.8
6.1K
1M
¥0.95 / ¥9.03输入/输出
168
Aqwen3-32b
qwen3-32bAlibaba
52.6
437
131K
¥2.07 / ¥8.26输入/输出
169
Aclaude-sonnet-4-20250514
claude-sonnet-4-20250514Anthropic
52.3
6.7K
200K
¥21.6 / ¥108输入/输出
170
AI
olmo-3.1-32b-instruct
olmo-3.1-32b-instructAllenai
52.0
2.2K
200K
¥14.4 / ¥57.6输入/输出
171
CO
command-a-03-2025
command-a-03-2025Cohere
51.7
8.8K
256K
¥18 / ¥72输入/输出
172
Aclaude-sonnet-4-20250514-thinking-32k
claude-sonnet-4-20250514-thinking-32kAnthropic
51.4
5.9K
200K
¥21.6 / ¥108输入/输出
173
Oo3-mini-high
o3-mini-highOpenai
51.1
1.8K
200K
¥7.92 / ¥31.7输入/输出
174
Ggemma-3-4b-it
gemma-3-4b-itGoogle
50.9
390
128K
¥1.44 / ¥1.44输入/输出
175
NVnvidia-llama-3.3-nemotron-super-49b-v1.5
nvidia-llama-3.3-nemotron-super-49b-v1.5Nvidia
50.6
599
131K
¥2.88 / ¥2.88输入/输出
176
Ogpt-5-nano-high
gpt-5-nano-highOpenai
50.3
1.5K
400K
¥0.36 / ¥2.88输入/输出
177
Zglm-4.5v
glm-4.5vZai
50.0
921
64K
¥4.32 / ¥13输入/输出
178
TEhunyuan-turbo-0110
hunyuan-turbo-0110Tencent
49.7
256
-
-
179
Aqwen3-30b-a3b
qwen3-30b-a3bAlibaba
49.4
4K
128K
¥0.79 / ¥7.78输入/输出
180
Ddeepseek-v3
deepseek-v3Deepseek
49.1
2.2K
128K
¥0 / ¥0输入/输出
181
Oo1-preview
o1-previewOpenai
48.9
3.8K
128K
¥108 / ¥432输入/输出
182
Aqwen-plus-0125
qwen-plus-0125Alibaba
48.6
571
1M
¥0.83 / ¥2.07输入/输出
183
NVllama-3.1-nemotron-ultra-253b-v1
llama-3.1-nemotron-ultra-253b-v1Nvidia
48.3
254
128K
¥4.32 / ¥13输入/输出
184
IAmercury
mercuryInception Ai
48.0
351
128K
¥1.8 / ¥5.4输入/输出
185
Ggemma-3n-e4b-it
gemma-3n-e4b-itGoogle
47.7
3.3K
128K
¥0 / ¥0输入/输出
186
AIolmo-3-32b-think
olmo-3-32b-thinkAllenai
47.4
1.1K
128K
¥2.16 / ¥3.24输入/输出
187
Aqwen2.5-plus-1127
qwen2.5-plus-1127Alibaba
47.2
1.1K
-
-
188
Oo3-mini
o3-miniOpenai
46.9
7.7K
200K
¥7.92 / ¥31.7输入/输出
189
Oo1-mini
o1-miniOpenai
46.6
6.1K
128K
¥7.92 / ¥31.7输入/输出
190
NVllama-3.3-nemotron-49b-super-v1
llama-3.3-nemotron-49b-super-v1Nvidia
46.3
241
131K
¥0 / ¥0输入/输出
191
Ggemini-1.5-pro-002
gemini-1.5-pro-002Google
46.0
6.4K
-
-
192
Ogpt-oss-20b
gpt-oss-20bOpenai
45.7
1.8K
131K
¥0.32 / ¥1.3输入/输出
193
STstep-2-16k-exp-202412
step-2-16k-exp-202412Stepfun
45.5
506
16.4K
¥37.5 / ¥118输入/输出
194
IB
granite-4.1-8b
granite-4.1-8bIbm
45.2
587
131K
¥0.36 / ¥0.72输入/输出
195
UNathene-v2-chat
-
44.9
2.7K
-
-
196
Aclaude-3-7-sonnet-20250219
claude-3-7-sonnet-20250219Anthropic
44.6
5.8K
200K
¥21.6 / ¥108输入/输出
197
Zglm-4-plus
glm-4-plusZai
44.3
3.3K
128K
¥54 / ¥54输入/输出
198
UNyi-lightning
-
44.0
3.4K
12K
¥1.44 / ¥1.44输入/输出
199
Aclaude-3-7-sonnet-20250219-thinking-32k
claude-3-7-sonnet-20250219-thinking-32kAnthropic
43.8
5.6K
-
-
200
Ogpt-4.1-nano-2025-04-14
gpt-4.1-nano-2025-04-14Openai
43.5
651
1.05M
¥14.4 / ¥57.6输入/输出
201
Xgrok-2-2024-08-13
grok-2-2024-08-13Xai
43.2
7.5K
1M
¥9 / ¥18输入/输出
202
Ogpt-4o-mini-2024-07-18
gpt-4o-mini-2024-07-18Openai
42.9
7.8K
128K
¥1.08 / ¥4.32输入/输出
203
Ggemini-1.5-flash-002
gemini-1.5-flash-002Google
42.6
4.3K
2M
¥0.54 / ¥2.2输入/输出
204
NVllama-3.1-nemotron-70b-instruct
llama-3.1-nemotron-70b-instructNvidia
42.3
904
128K
¥0 / ¥0输入/输出
205
Ogpt-4o-2024-05-13
gpt-4o-2024-05-13Openai
42.0
13.3K
128K
¥36 / ¥108输入/输出
206
Mllama-4-maverick-17b-128e-instruct
llama-4-maverick-17b-128e-instructMeta
41.8
6.2K
1M
¥1.8 / ¥6.26输入/输出
207
Ddeepseek-v2.5-1210
deepseek-v2.5-1210Deepseek
41.5
715
1M
¥1.01 / ¥2.02输入/输出
208
Mllama-4-scout-17b-16e-instruct
llama-4-scout-17b-16e-instructMeta
41.2
5K
128K
¥1.44 / ¥5.62输入/输出
209
MAmistral-small-3.1-24b-instruct-2503
mistral-small-3.1-24b-instruct-2503Mistral
40.9
5.6K
262K
¥2.88 / ¥14.4输入/输出
210
Aqwen-max-0919
qwen-max-0919Alibaba
40.6
2.2K
131K
¥2.48 / ¥9.91输入/输出
211
TEhunyuan-standard-2025-02-10
hunyuan-standard-2025-02-10Tencent
40.3
376
-
-
212
Aclaude-3-5-sonnet-20241022
claude-3-5-sonnet-20241022Anthropic
40.1
11.3K
200K
¥21.6 / ¥108输入/输出
213
Xgrok-2-mini-2024-08-13
grok-2-mini-2024-08-13Xai
39.8
6.1K
1M
¥9 / ¥18输入/输出
214
AIolmo-3.1-32b-think
olmo-3.1-32b-thinkAllenai
39.5
1.5K
200K
¥14.4 / ¥57.6输入/输出
215
Aqwen2.5-72b-instruct
qwen2.5-72b-instructAlibaba
39.2
4.7K
131K
¥4.13 / ¥12.4输入/输出
216
Ggemini-1.5-pro-001
gemini-1.5-pro-001Google
38.9
9.3K
-
-
217
Ddeepseek-v2.5
deepseek-v2.5Deepseek
38.6
2.8K
1M
¥1.01 / ¥2.02输入/输出
218
Mllama-3.1-405b-instruct-fp8
llama-3.1-405b-instruct-fp8Meta
38.4
6.7K
128K
¥0 / ¥0输入/输出
219
Ggemini-advanced-0514
gemini-advanced-0514Google
38.1
6.1K
-
-
220
UNathene-70b-0725
-
37.8
2.1K
-
-
221
Mllama-3.1-405b-instruct-bf16
llama-3.1-405b-instruct-bf16Meta
37.5
4.5K
128K
¥0 / ¥0输入/输出
222
Mllama-3.3-70b-instruct
llama-3.3-70b-instructMeta
37.2
6.7K
128K
¥0 / ¥0输入/输出
223
TEhunyuan-large-2025-02-10
hunyuan-large-2025-02-10Tencent
36.9
357
-
-
224
MAmistral-large-2411
mistral-large-2411Mistral
36.6
3K
128K
¥14.4 / ¥43.2输入/输出
225
Mllama-3.1-70b-instruct
llama-3.1-70b-instructMeta
36.4
6.4K
131K
¥2.88 / ¥2.88输入/输出
226
Aclaude-3-5-sonnet-20240620
claude-3-5-sonnet-20240620Anthropic
36.1
9.7K
200K
¥21.6 / ¥108输入/输出
227
Ogpt-4o-2024-08-06
gpt-4o-2024-08-06Openai
35.8
5.1K
128K
¥18 / ¥72输入/输出
228
TEhunyuan-large-vision
hunyuan-large-visionTencent
35.5
798
-
-
229
Aamazon-nova-pro-v1.0
amazon-nova-pro-v1.0Amazon
35.2
2.6K
300K
¥5.76 / ¥23输入/输出
230
AIllama-3.1-tulu-3-70b
llama-3.1-tulu-3-70bAllenai
34.9
288
-
-
231
MAmistral-large-2407
mistral-large-2407Mistral
34.7
5.2K
131K
¥14.4 / ¥43.2输入/输出
232
Ggemini-1.5-flash-001
gemini-1.5-flash-001Google
34.4
7.3K
2M
¥0.54 / ¥2.2输入/输出
233
Aqwen2.5-coder-32b-instruct
qwen2.5-coder-32b-instructAlibaba
34.1
629
131K
¥2.07 / ¥6.2输入/输出
234
MAmagistral-medium-2506
magistral-medium-2506Mistral
33.8
2.2K
128K
¥14.4 / ¥36输入/输出
235
Aclaude-3-5-haiku-20241022
claude-3-5-haiku-20241022Anthropic
33.5
9.2K
200K
¥5.76 / ¥28.8输入/输出
236
Ogpt-4-turbo-2024-04-09
gpt-4-turbo-2024-04-09Openai
33.2
10.8K
128K
¥72 / ¥216输入/输出
237
UNgemma-2-9b-it-simpo
-
33.0
1.1K
8.19K
¥1.44 / ¥1.44输入/输出
238
Aclaude-3-opus-20240229
claude-3-opus-20240229Anthropic
32.7
21.7K
200K
¥108 / ¥540输入/输出
239
Aamazon-nova-lite-v1.0
amazon-nova-lite-v1.0Amazon
32.4
2.1K
300K
¥0.43 / ¥1.73输入/输出
240
UNreka-core-20240904
-
32.1
837
-
-
241
Ogpt-4-0125-preview
gpt-4-0125-previewOpenai
31.8
9.7K
8.19K
¥216 / ¥432输入/输出
242
NVllama-3.1-nemotron-51b-instruct
llama-3.1-nemotron-51b-instructNvidia
31.5
421
128K
¥0 / ¥0输入/输出
243
COcommand-r-plus-08-2024
command-r-plus-08-2024Cohere
31.3
1.1K
128K
¥18 / ¥72输入/输出
244
IBibm-granite-h-small
ibm-granite-h-smallIbm
31.0
1K
-
-
245
Ogpt-4-1106-preview
gpt-4-1106-previewOpenai
30.7
9.6K
8.19K
¥216 / ¥432输入/输出
246
Ggemini-1.5-flash-8b-001
gemini-1.5-flash-8b-001Google
30.4
4.3K
2M
¥0.54 / ¥2.2输入/输出
247
COc4ai-aya-expanse-32b
c4ai-aya-expanse-32bCohere
30.1
3.1K
-
-
248
Ggemma-2-27b-it
gemma-2-27b-itGoogle
29.8
8.7K
8.19K
¥0.58 / ¥0.58输入/输出
249
MAmistral-small-24b-instruct-2501
mistral-small-24b-instruct-2501Mistral
29.5
1.4K
262K
¥2.88 / ¥14.4输入/输出
250
M
phi-4
phi-4Microsoft
29.3
2.4K
128K
¥0.9 / ¥3.6输入/输出
251
AIllama-3.1-tulu-3-8b
llama-3.1-tulu-3-8bAllenai
29.0
285
-
-
252
UNjamba-1.5-large
-
28.7
979
256K
¥0 / ¥0输入/输出
253
UNreka-flash-20240904
-
28.4
904
65.5K
¥0.72 / ¥1.44输入/输出
254
COcommand-r-plus
command-r-plusCohere
28.1
8.5K
128K
¥18 / ¥72输入/输出
255
Ggemma-2-9b-it
gemma-2-9b-itGoogle
27.8
6.2K
8.19K
¥1.44 / ¥1.44输入/输出
256
NVnemotron-4-340b-instruct
nemotron-4-340b-instructNvidia
27.6
2.2K
-
-
257
Aamazon-nova-micro-v1.0
amazon-nova-micro-v1.0Amazon
27.3
2.1K
128K
¥0.25 / ¥1.01输入/输出
258
AIolmo-2-0325-32b-instruct
olmo-2-0325-32b-instructAllenai
27.0
336
-
-
259
TEhunyuan-standard-256k
hunyuan-standard-256kTencent
26.7
328
-
-
260
Zglm-4-0520
glm-4-0520Zai
26.4
1.2K
128K
¥108 / ¥108输入/输出
261
COc4ai-aya-expanse-8b
c4ai-aya-expanse-8bCohere
26.1
1.1K
-
-
262
Aclaude-3-sonnet-20240229
claude-3-sonnet-20240229Anthropic
25.9
11.9K
200K
¥21.6 / ¥108输入/输出
263
MAministral-8b-2410
ministral-8b-2410Mistral
25.6
572
128K
¥0.72 / ¥0.72输入/输出
264
Mllama-3-70b-instruct
llama-3-70b-instructMeta
25.3
16.6K
8.19K
¥3.67 / ¥5.33输入/输出
265
Mllama-3.1-8b-instruct
llama-3.1-8b-instructMeta
25.0
5.7K
131K
¥0.79 / ¥0.79输入/输出
266
Aclaude-3-haiku-20240307
claude-3-haiku-20240307Anthropic
24.7
13.2K
200K
¥1.8 / ¥9输入/输出
267
UNjamba-1.5-mini
-
24.4
1K
256K
¥0 / ¥0输入/输出
268
COcommand-r-08-2024
command-r-08-2024Cohere
24.1
1.2K
128K
¥18 / ¥72输入/输出
269
Ddeepseek-coder-v2
deepseek-coder-v2Deepseek
23.9
1.8K
1M
¥1.01 / ¥2.02输入/输出
270
Aqwen2-72b-instruct
qwen2-72b-instructAlibaba
23.6
4.3K
131K
¥4.13 / ¥12.4输入/输出
271
Ogpt-4-0314
gpt-4-0314Openai
23.3
5.1K
8.19K
¥216 / ¥432输入/输出
272
IBgranite-3.1-8b-instruct
granite-3.1-8b-instructIbm
23.0
316
-
-
273
COcommand-r
command-rCohere
22.7
6K
128K
¥18 / ¥72输入/输出
274
Aqwen1.5-110b-chat
qwen1.5-110b-chatAlibaba
22.4
3.1K
-
-
275
IBgranite-3.1-2b-instruct
granite-3.1-2b-instructIbm
22.2
382
-
-
276
UNreka-flash-21b-20240226-online
-
21.9
1.7K
-
-
277
UNyi-1.5-34b-chat
-
21.6
2.8K
-
-
278
Ggemini-pro-dev-api
gemini-pro-dev-apiGoogle
21.3
1.7K
1.05M
¥14.4 / ¥86.4输入/输出
279
MAmistral-large-2402
mistral-large-2402Mistral
21.0
6.5K
262K
¥2.88 / ¥14.4输入/输出
280
Mllama-3-8b-instruct
llama-3-8b-instructMeta
20.7
10.8K
8.19K
¥0.29 / ¥0.29输入/输出
281
UNreka-flash-21b-20240226
-
20.5
2.7K
-
-
282
Ggemma-2-2b-it
gemma-2-2b-itGoogle
20.2
5.2K
128K
¥0 / ¥0输入/输出
283
Ogpt-4-0613
gpt-4-0613Openai
19.9
8.7K
8.19K
¥216 / ¥432输入/输出
284
MAmistral-medium
mistral-mediumMistral
19.6
3.2K
262K
¥2.88 / ¥14.4输入/输出
285
MAmixtral-8x22b-instruct-v0.1
mixtral-8x22b-instruct-v0.1Mistral
19.3
5.6K
64K
¥14.4 / ¥43.2输入/输出
286
Aqwen1.5-72b-chat
qwen1.5-72b-chatAlibaba
19.0
3.8K
-
-
287
UNinternlm2_5-20b-chat
-
18.8
1.3K
-
-
288
UNstarling-lm-7b-beta
-
18.5
1.7K
200K
¥5.4 / ¥18.7输入/输出
289
Mphi-3-medium-4k-instruct
phi-3-medium-4k-instructMicrosoft
18.2
2.8K
4.1K
¥1.22 / ¥4.9输入/输出
290
Aqwq-32b-preview
qwq-32b-previewAlibaba
17.9
374
131K
¥2.07 / ¥6.2输入/输出
291
Aqwen1.5-32b-chat
qwen1.5-32b-chatAlibaba
17.6
2.3K
-
-
292
UNzephyr-orpo-141b-A35b-v0.1
-
17.3
441
200K
¥108 / ¥432输入/输出
293
UNyi-34b-chat
-
17.0
1.4K
-
-
294
MAmixtral-8x7b-instruct-v0.1
mixtral-8x7b-instruct-v0.1Mistral
16.8
7.1K
32K
¥5.04 / ¥5.04输入/输出
295
Ggemini-pro
gemini-proGoogle
16.5
431
1.05M
¥14.4 / ¥86.4输入/输出
296
Aqwen1.5-14b-chat
qwen1.5-14b-chatAlibaba
16.2
1.9K
-
-
297
Mllama-2-70b-chat
llama-2-70b-chatMeta
15.9
3.5K
-
-
298
Mwizardlm-70b
wizardlm-70bMicrosoft
15.6
682
-
-
299
NVllama2-70b-steerlm-chat
llama2-70b-steerlm-chatNvidia
15.3
282
-
-
300
UNtulu-2-dpo-70b
-
15.1
540
-
-
301
Mphi-3-small-8k-instruct
phi-3-small-8k-instructMicrosoft
14.8
2.2K
8.19K
¥1.08 / ¥4.32输入/输出
302
Ogpt-3.5-turbo-0125
gpt-3.5-turbo-0125Openai
14.5
6.9K
16.4K
¥3.6 / ¥10.8输入/输出
303
UNopenchat-3.5-0106
-
14.2
1.2K
-
-
304
Mllama-3.2-3b-instruct
llama-3.2-3b-instructMeta
13.9
1K
131K
¥0.22 / ¥0.35输入/输出
305
UNstarling-lm-7b-alpha
-
13.6
841
200K
¥5.4 / ¥18.7输入/输出
306
UNdbrx-instruct-preview
-
13.4
3.4K
-
-
307
UNnous-hermes-2-mixtral-8x7b-dpo
-
13.1
282
1M
¥36 / ¥180输入/输出
308
Aqwen1.5-7b-chat
qwen1.5-7b-chatAlibaba
12.8
447
-
-
309
Ggemma-1.1-7b-it
gemma-1.1-7b-itGoogle
12.5
2.7K
-
-
310
Mllama-2-13b-chat
llama-2-13b-chatMeta
12.2
1.7K
-
-
311
UNvicuna-33b
-
11.9
1.9K
-
-
312
Ddeepseek-llm-67b-chat
deepseek-llm-67b-chatDeepseek
11.6
441
1M
¥1.01 / ¥2.02输入/输出
313
IBgranite-3.0-8b-instruct
granite-3.0-8b-instructIbm
11.4
813
-
-
314
MAmistral-7b-instruct-v0.2
mistral-7b-instruct-v0.2Mistral
11.1
1.7K
262K
¥2.88 / ¥14.4输入/输出
315
UNopenchat-3.5
-
10.8
615
-
-
316
IBgranite-3.0-2b-instruct
granite-3.0-2b-instructIbm
10.5
873
-
-
317
Mcodellama-34b-instruct
codellama-34b-instructMeta
10.2
639
-
-
318
Mphi-3-mini-4k-instruct
phi-3-mini-4k-instructMicrosoft
9.9
2.5K
4.1K
¥0.94 / ¥3.74输入/输出
319
UNsnowflake-arctic-instruct
-
9.7
3.3K
-
-
320
Mllama-2-7b-chat
llama-2-7b-chatMeta
9.4
1.3K
128K
¥4.03 / ¥48输入/输出
321
Ggemma-7b-it
gemma-7b-itGoogle
9.1
818
-
-
322
UNopenhermes-2.5-mistral-7b
-
8.8
381
1M
¥36 / ¥180输入/输出
323
Mphi-3-mini-4k-instruct-june-2024
phi-3-mini-4k-instruct-june-2024Microsoft
8.5
1.4K
4.1K
¥0.94 / ¥3.74输入/输出
324
UNsolar-10.7b-instruct-v1.0
-
8.2
311
128K
¥0 / ¥0输入/输出
325
Ogpt-3.5-turbo-1106
gpt-3.5-turbo-1106Openai
8.0
1.4K
16.4K
¥7.2 / ¥14.4输入/输出
326
AIolmo-7b-instruct
olmo-7b-instructAllenai
7.7
548
-
-
327
UNmpt-30b-chat
-
7.4
207
-
-
328
Mwizardlm-13b
wizardlm-13bMicrosoft
7.1
634
-
-
329
UNvicuna-13b
-
6.8
1.6K
-
-
330
Aqwen-14b-chat
qwen-14b-chatAlibaba
6.5
426
32.8K
¥1.04 / ¥3.1输入/输出
331
UNzephyr-7b-beta
-
6.3
997
-
-
332
Mllama-3.2-1b-instruct
llama-3.2-1b-instructMeta
6.0
1K
16.4K
¥0.07 / ¥0.08输入/输出
333
Ggemma-2b-it
gemma-2b-itGoogle
5.7
447
-
-
334
Mphi-3-mini-128k-instruct
phi-3-mini-128k-instructMicrosoft
5.4
2.1K
128K
¥0.94 / ¥3.74输入/输出
335
Ggemma-1.1-2b-it
gemma-1.1-2b-itGoogle
5.1
1.1K
-
-
336
UNguanaco-33b
-
4.8
261
200K
¥14.4 / ¥57.6输入/输出
337
UNvicuna-7b
-
4.5
555
-
-
338
UNstripedhyena-nous-7b
-
4.3
455
-
-
339
UNsmollm2-1.7b-instruct
-
4.0
252
-
-
340
Aqwen1.5-4b-chat
qwen1.5-4b-chatAlibaba
3.7
738
-
-
341
Gpalm-2
palm-2Google
3.4
755
-
-
342
MAmistral-7b-instruct
mistral-7b-instructMistral
3.1
747
262K
¥2.88 / ¥14.4输入/输出
343
UNkoala-13b
-
2.8
503
-
-
344
UNchatglm3-6b
-
2.6
378
200K
¥5.4 / ¥18.7输入/输出
345
UNRWKV-4-Raven-14B
-
2.3
360
-
-
346
UNchatglm2-6b
-
2.0
234
200K
¥5.4 / ¥18.7输入/输出
347
UNfastchat-t5-3b
-
1.7
287
-
-
348
UNmpt-7b-chat
-
1.4
306
-
-
349
UNchatglm-6b
-
1.1
300
200K
¥5.4 / ¥18.7输入/输出
350
UNoasst-pythia-12b
-
0.9
454
-
-
351
UNalpaca-13b
-
0.6
391
-
-
352
UNstablelm-tuned-alpha-7b
-
0.3
238
-
-
353
UNdolly-v2-12b
-
0.0
233
-
-
claude-opus-4-6 为什么排第一
claude-opus-4-6 当前排名第 1，厂商为 anthropic，百分制分数 100.0，样本量 7.1K。如果你的任务与本榜单口径一致，可以优先把它作为候选模型，再结合价格、上下文长度和可用性做最终选择。
不要只看第一名
先选择最接近真实任务的排行榜，再比较 Top 模型的分数和样本量。分数越高说明同一榜单内偏好表现越强；样本量越高通常结果更稳定。最后再结合价格、上下文长度、开源闭源和厂商可用性筛选。
继续比较相近能力
商业、管理与金融常见问题
商业、管理与金融排行榜看什么指标？
主要看排名、百分制分数、样本量和来源。分数用于快速比较同一榜单内模型表现，样本量用于判断结果稳定性。
为什么不同榜单不能直接混合成总分？
不同榜单的任务、样本和评测口径不同，模力榜默认只在同一榜单内排序，避免把写作、代码、图像等能力强行合并。
商业、管理与金融模型应该怎么选？
优先看与你任务最接近的榜单，再结合价格、上下文长度、开源闭源和厂商可用性。排名靠前不代表适合所有预算和部署方式。
榜单多久更新？
页面展示的是最新成功采集的公开榜单数据。当前优先使用 LMArena leaderboard dataset，并在页面来源中保留原始链接。