1
A
claude-opus-4-6-thinking
claude-opus-4-6-thinkingAnthropic
100.0
5.6K
1M
¥36 / ¥180输入/输出
对话 · 文本 · 生命、物理与社会科学排行榜
基于公开偏好评测数据展示 文本 / 生命、物理与社会科学 榜单，每个榜单独立排序。
生命、物理与社会科学模型怎么选？
生命、物理与社会科学排行榜用于回答“生命、物理与社会科学哪个 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-thinking，厂商为 anthropic，百分制分数 100.0，样本量 5.6K。 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-4-6-thinkingclaude-opus-4-6claude-opus-4-7-thinkinggemini-3.5-flashgemini-3.1-pro-preview
2
Aclaude-opus-4-6
claude-opus-4-6Anthropic
99.7
5.9K
1M
¥36 / ¥180输入/输出
3
Aclaude-opus-4-7-thinking
claude-opus-4-7-thinkingAnthropic
99.4
3.4K
1M
¥36 / ¥180输入/输出
4
G
gemini-3.5-flash
gemini-3.5-flashGoogle
99.2
1.4K
1.05M
¥10.8 / ¥64.8输入/输出
5
Ggemini-3.1-pro-preview
gemini-3.1-pro-previewGoogle
98.9
7.1K
1.05M
¥14.4 / ¥86.4输入/输出
6
A
qwen3.5-max-preview
qwen3.5-max-previewAlibaba
98.6
3.2K
-
-
7
Aclaude-opus-4-7
claude-opus-4-7Anthropic
98.3
3.5K
1M
¥36 / ¥180输入/输出
8
B
ernie-5.1
ernie-5.1Baidu
98.0
2.4K
119K
¥5.4 / ¥21.6输入/输出
9
Z
glm-5.1
glm-5.1Zai
97.8
2.3K
200K
¥0 / ¥0输入/输出
10
Ggemini-3-pro
gemini-3-proGoogle
97.5
6.7K
1.05M
¥14.4 / ¥86.4输入/输出
11
O
gpt-5.5
gpt-5.5Openai
97.2
2.8K
1.05M
¥36 / ¥216输入/输出
12
M
muse-spark
muse-sparkMeta
96.9
2K
-
-
13
Ogpt-5.4-high
gpt-5.4-highOpenai
96.6
4.6K
1.05M
¥18 / ¥108输入/输出
14
Ggemini-2.5-pro
gemini-2.5-proGoogle
96.4
20.1K
1.05M
¥9 / ¥72输入/输出
15
Ogpt-5.5-high
gpt-5.5-highOpenai
96.1
2.7K
1.05M
¥36 / ¥216输入/输出
16
MI
mimo-v2.5-pro
mimo-v2.5-proXiaomi
95.8
2.6K
1.05M
¥7.2 / ¥21.6输入/输出
17
Aqwen3.7-max-preview
qwen3.7-max-previewAlibaba
95.5
664
1M
¥18 / ¥54输入/输出
18
Ggemini-3-flash
gemini-3-flashGoogle
95.2
4.9K
1.05M
¥3.6 / ¥21.6输入/输出
19
Aclaude-sonnet-4-6
claude-sonnet-4-6Anthropic
95.0
4.4K
1M
¥21.6 / ¥108输入/输出
20
Aqwen3.6-max-preview
qwen3.6-max-previewAlibaba
94.7
773
246K
¥9.5 / ¥56.9输入/输出
21
Bernie-5.0-preview-1203
ernie-5.0-preview-1203Baidu
94.4
1.6K
128K
¥7.92 / ¥14.4输入/输出
22
M
kimi-k2.6
kimi-k2.6Moonshot
94.1
2.6K
262K
¥6.84 / ¥28.8输入/输出
23
Zglm-5
glm-5Zai
93.8
3.4K
205K
¥7.2 / ¥23输入/输出
24
D
deepseek-v4-pro
deepseek-v4-proDeepseek
93.6
2.8K
1M
¥3.13 / ¥6.26输入/输出
25
Mkimi-k2.5-thinking
kimi-k2.5-thinkingMoonshot
93.3
5.7K
262K
¥4.32 / ¥21.6输入/输出
26
Aqwen3.5-397b-a17b
qwen3.5-397b-a17bAlibaba
93.0
5.3K
262K
¥3.1 / ¥18.6输入/输出
27
Ogpt-5.4
gpt-5.4Openai
92.7
4.8K
1.05M
¥18 / ¥108输入/输出
28
Ggemini-3-flash (thinking-minimal)
gemini-3-flash (thinking-minimal)Google
92.4
8.6K
1.05M
¥3.6 / ¥21.6输入/输出
29
X
grok-4.20-multi-agent-beta-0309
grok-4.20-multi-agent-beta-0309Xai
92.2
4.7K
2M
¥14.4 / ¥43.2输入/输出
30
Zglm-4.6
glm-4.6Zai
91.9
5.9K
205K
¥4.32 / ¥15.8输入/输出
31
MImimo-v2-pro
mimo-v2-proXiaomi
91.6
3.6K
1.05M
¥7.2 / ¥21.6输入/输出
32
Xgrok-4.20-beta-0309-reasoning
grok-4.20-beta-0309-reasoningXai
91.3
4.7K
2M
¥14.4 / ¥43.2输入/输出
33
Aqwen3-max-preview
qwen3-max-previewAlibaba
91.0
4.2K
262K
¥6.2 / ¥24.8输入/输出
34
Ddeepseek-v4-pro-thinking
deepseek-v4-pro-thinkingDeepseek
90.8
2.5K
1M
¥3.13 / ¥6.26输入/输出
35
Ogpt-5.1-high
gpt-5.1-highOpenai
90.5
6.6K
400K
¥9 / ¥72输入/输出
36
Zglm-4.7
glm-4.7Zai
90.2
2.1K
205K
¥0 / ¥0输入/输出
37
B
dola-seed-2.0-pro
dola-seed-2.0-proBytedance
89.9
6K
-
-
38
Ggemma-4-31b
gemma-4-31bGoogle
89.6
872
262K
¥3.24 / ¥7.2输入/输出
39
Aclaude-opus-4-5-20251101
claude-opus-4-5-20251101Anthropic
89.4
10.3K
200K
¥36 / ¥180输入/输出
40
Ddeepseek-v3.1-terminus
deepseek-v3.1-terminusDeepseek
89.1
577
128K
¥1.8 / ¥5.04输入/输出
41
Bernie-5.0-0110
ernie-5.0-0110Baidu
88.8
5.6K
128K
¥7.92 / ¥14.4输入/输出
42
Ddeepseek-v3.1-terminus-thinking
deepseek-v3.1-terminus-thinkingDeepseek
88.5
538
128K
¥1.8 / ¥5.04输入/输出
43
MA
mistral-large-3
mistral-large-3Mistral
88.2
6.8K
262K
¥3.6 / ¥10.8输入/输出
44
A
amazon-nova-experimental-chat-26-02-10
amazon-nova-experimental-chat-26-02-10Amazon
88.0
512
-
-
45
Ddeepseek-v4-flash
deepseek-v4-flashDeepseek
87.7
2.8K
1M
¥1.01 / ¥2.02输入/输出
46
MAmistral-medium-2508
mistral-medium-2508Mistral
87.4
14.5K
262K
¥2.88 / ¥14.4输入/输出
47
Aamazon-nova-experimental-chat-12-10
amazon-nova-experimental-chat-12-10Amazon
87.1
600
-
-
48
Aamazon-nova-experimental-chat-11-10
amazon-nova-experimental-chat-11-10Amazon
86.8
3.9K
-
-
49
Bernie-5.0-preview-1022
ernie-5.0-preview-1022Baidu
86.6
776
128K
¥7.92 / ¥14.4输入/输出
50
Aclaude-sonnet-4-5-20250929
claude-sonnet-4-5-20250929Anthropic
86.3
12.3K
200K
¥21.6 / ¥108输入/输出
51
Ddeepseek-v3.2-exp-thinking
deepseek-v3.2-exp-thinkingDeepseek
86.0
1.4K
128K
¥0 / ¥0输入/输出
52
Xgrok-4.1
grok-4.1Xai
85.7
10.4K
200K
¥14.4 / ¥72输入/输出
53
Ggemma-4-26b-a4b
gemma-4-26b-a4bGoogle
85.4
871
262K
¥0.94 / ¥2.88输入/输出
54
Ddeepseek-v3.2
deepseek-v3.2Deepseek
85.2
7.2K
128K
¥2.09 / ¥3.1输入/输出
55
Aclaude-opus-4-5-20251101-thinking-32k
claude-opus-4-5-20251101-thinking-32kAnthropic
84.9
5.8K
200K
¥108 / ¥540输入/输出
56
Aqwen3-vl-235b-a22b-instruct
qwen3-vl-235b-a22b-instructAlibaba
84.6
1.8K
128K
¥2.16 / ¥8.64输入/输出
57
Xgrok-4.20-beta1
grok-4.20-beta1Xai
84.3
4K
2M
¥14.4 / ¥43.2输入/输出
58
Zglm-4.5
glm-4.5Zai
84.0
3.9K
131K
¥4.32 / ¥15.8输入/输出
59
Ochatgpt-4o-latest-20250326
chatgpt-4o-latest-20250326Openai
83.8
13.7K
128K
¥18 / ¥72输入/输出
60
Ogpt-5.2-chat-latest-20260210
gpt-5.2-chat-latest-20260210Openai
83.5
5.1K
400K
¥12.6 / ¥101输入/输出
61
Ogpt-5.1
gpt-5.1Openai
83.2
6.9K
400K
¥9 / ¥72输入/输出
62
Ddeepseek-v4-flash-thinking
deepseek-v4-flash-thinkingDeepseek
82.9
2.8K
1M
¥1.01 / ¥2.02输入/输出
63
Xgrok-4.1-thinking
grok-4.1-thinkingXai
82.6
10.4K
200K
¥14.4 / ¥72输入/输出
64
Aqwen3-235b-a22b-instruct-2507
qwen3-235b-a22b-instruct-2507Alibaba
82.4
15.1K
128K
¥2.09 / ¥8.23输入/输出
65
Xgrok-3-preview-02-24
grok-3-preview-02-24Xai
82.1
5.8K
1M
¥9 / ¥18输入/输出
66
Aclaude-sonnet-4-5-20250929-thinking-32k
claude-sonnet-4-5-20250929-thinking-32kAnthropic
81.8
12.3K
200K
¥21.6 / ¥108输入/输出
67
MImimo-v2.5
mimo-v2.5Xiaomi
81.5
2.6K
1.05M
¥2.88 / ¥14.4输入/输出
68
Xgrok-4-0709
grok-4-0709Xai
81.2
6.9K
256K
¥21.6 / ¥108输入/输出
69
Aqwen3.6-plus
qwen3.6-plusAlibaba
81.0
3K
1M
¥3.6 / ¥21.6输入/输出
70
Ggemini-2.5-flash-preview-09-2025
gemini-2.5-flash-preview-09-2025Google
80.7
5.2K
1M
¥2.16 / ¥18输入/输出
71
Aqwen3-next-80b-a3b-instruct
qwen3-next-80b-a3b-instructAlibaba
80.4
3.5K
131K
¥1.04 / ¥4.13输入/输出
72
Aqwen3.5-27b
qwen3.5-27bAlibaba
80.1
4.2K
262K
¥2.16 / ¥17.3输入/输出
73
Ggemini-2.5-flash
gemini-2.5-flashGoogle
79.8
19.8K
1.05M
¥2.16 / ¥18输入/输出
74
Ddeepseek-v3.1
deepseek-v3.1Deepseek
79.6
2.3K
128K
¥1.44 / ¥5.04输入/输出
75
Aqwen3.5-122b-a10b
qwen3.5-122b-a10bAlibaba
79.3
4.3K
262K
¥2.88 / ¥23输入/输出
76
TE
hunyuan-t1-20250711
hunyuan-t1-20250711Tencent
79.0
723
131K
¥0 / ¥0输入/输出
77
Aqwen3-235b-a22b-thinking-2507
qwen3-235b-a22b-thinking-2507Alibaba
78.7
1.5K
131K
¥2.07 / ¥8.26输入/输出
78
M
longcat-flash-chat-2602-exp
longcat-flash-chat-2602-expMeituan
78.4
3.9K
128K
¥1.08 / ¥10.8输入/输出
79
Ddeepseek-r1-0528
deepseek-r1-0528Deepseek
78.2
3.4K
164K
¥3.6 / ¥15.5输入/输出
80
Mkimi-k2.5-instant
kimi-k2.5-instantMoonshot
77.9
1.2K
262K
¥4.32 / ¥21.6输入/输出
81
Ggemini-3.1-flash-lite-preview
gemini-3.1-flash-lite-previewGoogle
77.6
5.7K
1.05M
¥1.8 / ¥10.8输入/输出
82
Ddeepseek-v3.1-thinking
deepseek-v3.1-thinkingDeepseek
77.3
1.9K
128K
¥1.44 / ¥5.04输入/输出
83
Oo3-2025-04-16
o3-2025-04-16Openai
77.0
10K
200K
¥14.4 / ¥57.6输入/输出
84
Ddeepseek-v3.2-exp
deepseek-v3.2-expDeepseek
76.8
1.9K
128K
¥0 / ¥0输入/输出
85
Ddeepseek-v3.2-thinking
deepseek-v3.2-thinkingDeepseek
76.5
6.4K
128K
¥2.09 / ¥3.1输入/输出
86
Ogpt-5.5-instant
gpt-5.5-instantOpenai
76.2
4K
400K
¥9 / ¥72输入/输出
87
Mlongcat-flash-chat
longcat-flash-chatMeituan
75.9
1.7K
128K
¥1.08 / ¥10.8输入/输出
88
Aamazon-nova-experimental-chat-10-20
amazon-nova-experimental-chat-10-20Amazon
75.6
1.8K
-
-
89
Ogpt-5.2
gpt-5.2Openai
75.4
7.5K
400K
¥12.6 / ¥101输入/输出
90
Ogpt-5.2-high
gpt-5.2-highOpenai
75.1
7.5K
400K
¥12.6 / ¥101输入/输出
91
Xgrok-4-fast-reasoning
grok-4-fast-reasoningXai
74.8
3K
2M
¥1.44 / ¥3.6输入/输出
92
TEhunyuan-hy3-preview
hunyuan-hy3-previewTencent
74.5
1.1K
256K
¥0 / ¥0输入/输出
93
MImimo-v2-flash (non-thinking)
mimo-v2-flash (non-thinking)Xiaomi
74.2
7.1K
262K
¥0.72 / ¥2.16输入/输出
94
Aclaude-opus-4-1-20250805-thinking-16k
claude-opus-4-1-20250805-thinking-16kAnthropic
73.9
7.9K
200K
¥108 / ¥540输入/输出
95
Xgrok-4-1-fast-reasoning
grok-4-1-fast-reasoningXai
73.7
8.8K
2M
¥1.44 / ¥3.6输入/输出
96
Ogpt-5.4-mini-high
gpt-5.4-mini-highOpenai
73.4
4.3K
400K
¥5.4 / ¥32.4输入/输出
97
Mkimi-k2-thinking-turbo
kimi-k2-thinking-turboMoonshot
73.1
9.6K
262K
¥17.3 / ¥72输入/输出
98
Ogpt-4.5-preview-2025-02-27
gpt-4.5-preview-2025-02-27Openai
72.8
2.5K
8.19K
¥216 / ¥432输入/输出
99
Xgrok-4.3
grok-4.3Xai
72.5
2.6K
1M
¥9 / ¥18输入/输出
100
Ogpt-5-chat
gpt-5-chatOpenai
72.3
5K
400K
¥9 / ¥72输入/输出
101
ST
step-3.5-flash
step-3.5-flashStepfun
72.0
5.5K
256K
¥0.69 / ¥2.07输入/输出
102
Aclaude-opus-4-1-20250805
claude-opus-4-1-20250805Anthropic
71.7
12.1K
200K
¥108 / ¥540输入/输出
103
M
minimax-m2.1-preview
minimax-m2.1-previewMinimax
71.4
2.7K
205K
¥0 / ¥0输入/输出
104
Aqwen3.5-flash
qwen3.5-flashAlibaba
71.1
4.7K
1M
¥1.24 / ¥12.4输入/输出
105
Xgrok-4-fast-chat
grok-4-fast-chatXai
70.9
1K
2M
¥1.44 / ¥3.6输入/输出
106
Aqwen3-max-2025-09-23
qwen3-max-2025-09-23Alibaba
70.6
1.4K
258K
¥6.19 / ¥24.7输入/输出
107
Aqwen3-vl-235b-a22b-thinking
qwen3-vl-235b-a22b-thinkingAlibaba
70.3
1.3K
131K
¥2.06 / ¥8.26输入/输出
108
Aqwen3.5-35b-a3b
qwen3.5-35b-a3bAlibaba
70.0
4.6K
262K
¥1.8 / ¥14.4输入/输出
109
TEhunyuan-vision-1.5-thinking
hunyuan-vision-1.5-thinkingTencent
69.7
339
-
-
110
Aamazon-nova-experimental-chat-26-01-10
amazon-nova-experimental-chat-26-01-10Amazon
69.5
555
-
-
111
Zglm-4.5-air
glm-4.5-airZai
69.2
4.9K
131K
¥0 / ¥0输入/输出
112
Aamazon-nova-experimental-chat-10-09
amazon-nova-experimental-chat-10-09Amazon
68.9
434
-
-
113
Aqwen3-235b-a22b-no-thinking
qwen3-235b-a22b-no-thinkingAlibaba
68.6
6.3K
131K
¥2.07 / ¥8.26输入/输出
114
Mminimax-m2.7
minimax-m2.7Minimax
68.3
3.7K
205K
¥0 / ¥0输入/输出
115
MImimo-v2-flash (thinking)
mimo-v2-flash (thinking)Xiaomi
68.1
1.7K
262K
¥0.72 / ¥2.16输入/输出
116
Ogpt-5-high
gpt-5-highOpenai
67.8
5.1K
400K
¥9 / ¥72输入/输出
117
MImimo-v2-omni
mimo-v2-omniXiaomi
67.5
463
262K
¥2.88 / ¥14.4输入/输出
118
TEhunyuan-turbos-20250416
hunyuan-turbos-20250416Tencent
67.2
2K
131K
¥0 / ¥0输入/输出
119
Aclaude-haiku-4-5-20251001
claude-haiku-4-5-20251001Anthropic
66.9
12.5K
200K
¥7.2 / ¥36输入/输出
120
Ggemini-2.5-flash-lite-preview-09-2025-no-thinking
gemini-2.5-flash-lite-preview-09-2025-no-thinkingGoogle
66.7
7.5K
1.05M
¥0.72 / ¥2.88输入/输出
121
Zglm-4.6v
glm-4.6vZai
66.4
467
128K
¥2.16 / ¥6.48输入/输出
122
Aqwen3-30b-a3b-instruct-2507
qwen3-30b-a3b-instruct-2507Alibaba
66.1
3.7K
262K
¥2.16 / ¥3.6输入/输出
123
NV
nvidia-nemotron-3-super-120b-a12b
nvidia-nemotron-3-super-120b-a12bNvidia
65.8
1.1K
262K
¥1.44 / ¥5.76输入/输出
124
Mkimi-k2-0905-preview
kimi-k2-0905-previewMoonshot
65.5
1.7K
262K
¥4.32 / ¥18输入/输出
125
AG
ling-flash-2.0
ling-flash-2.0Ant Group
65.3
1K
131K
¥1.01 / ¥4.1输入/输出
126
Ggemma-3-27b-it
gemma-3-27b-itGoogle
65.0
7.9K
128K
¥2.15 / ¥2.15输入/输出
127
Aqwen3-next-80b-a3b-thinking
qwen3-next-80b-a3b-thinkingAlibaba
64.7
2.1K
131K
¥1.04 / ¥10.3输入/输出
128
Ogpt-5.3-chat-latest
gpt-5.3-chat-latestOpenai
64.4
4.8K
128K
¥12.6 / ¥101输入/输出
129
Ddeepseek-v3-0324
deepseek-v3-0324Deepseek
64.1
7.7K
75K
¥1.44 / ¥5.76输入/输出
130
Ogpt-oss-120b
gpt-oss-120bOpenai
63.9
4.8K
131K
¥1.08 / ¥4.32输入/输出
131
Ogpt-4.1-2025-04-14
gpt-4.1-2025-04-14Openai
63.6
8.5K
1.05M
¥14.4 / ¥57.6输入/输出
132
Aqwen2.5-max
qwen2.5-maxAlibaba
63.3
5.7K
32K
¥11.5 / ¥46输入/输出
133
Anova-2-lite
nova-2-liteAmazon
63.0
2.1K
128K
¥2.38 / ¥19.8输入/输出
134
MAmistral-medium-2505
mistral-medium-2505Mistral
62.7
5.7K
262K
¥2.88 / ¥14.4输入/输出
135
Xgrok-3-mini-high
grok-3-mini-highXai
62.5
2.8K
128K
¥0 / ¥0输入/输出
136
Ogpt-5.4-nano-high
gpt-5.4-nano-highOpenai
62.2
4.2K
400K
¥1.44 / ¥9输入/输出
137
Ddeepseek-r1
deepseek-r1Deepseek
61.9
3.3K
164K
¥5.04 / ¥18输入/输出
138
Xgrok-3-mini-beta
grok-3-mini-betaXai
61.6
3.9K
1M
¥9 / ¥18输入/输出
139
Ggemini-2.5-flash-lite-preview-06-17-thinking
gemini-2.5-flash-lite-preview-06-17-thinkingGoogle
61.3
5.3K
65.5K
¥0.72 / ¥2.88输入/输出
140
Aqwen3-32b
qwen3-32bAlibaba
61.1
798
131K
¥2.07 / ¥8.26输入/输出
141
Aqwen3-235b-a22b
qwen3-235b-a22bAlibaba
60.8
4.6K
131K
¥2.07 / ¥8.26输入/输出
142
Ogpt-5-mini-high
gpt-5-mini-highOpenai
60.5
4.2K
400K
¥1.8 / ¥14.4输入/输出
143
Oo1-2024-12-17
o1-2024-12-17Openai
60.2
4.8K
128K
¥108 / ¥432输入/输出
144
Aclaude-opus-4-20250514-thinking-16k
claude-opus-4-20250514-thinking-16kAnthropic
59.9
6K
200K
¥108 / ¥540输入/输出
145
Mminimax-m2.5
minimax-m2.5Minimax
59.7
5.9K
205K
¥0 / ¥0输入/输出
146
Ggemma-3-12b-it
gemma-3-12b-itGoogle
59.4
760
128K
¥1.96 / ¥1.96输入/输出
147
NVnvidia-llama-3.3-nemotron-super-49b-v1.5
nvidia-llama-3.3-nemotron-super-49b-v1.5Nvidia
59.1
594
131K
¥2.88 / ¥2.88输入/输出
148
Mkimi-k2-0711-preview
kimi-k2-0711-previewMoonshot
58.8
4.4K
131K
¥4.32 / ¥18输入/输出
149
UNtrinity-large-thinking
-
58.5
3.9K
262K
¥1.8 / ¥6.48输入/输出
150
Aclaude-opus-4-20250514
claude-opus-4-20250514Anthropic
58.3
7.1K
200K
¥108 / ¥540输入/输出
151
Zglm-4.7-flash
glm-4.7-flashZai
58.0
1.8K
200K
¥0 / ¥0输入/输出
152
UNintellect-3
-
57.7
890
131K
¥1.44 / ¥7.92输入/输出
153
Ggemini-2.0-flash-001
gemini-2.0-flash-001Google
57.4
7.8K
1.05M
¥1.08 / ¥4.32输入/输出
154
NVnvidia-nemotron-3-nano-30b-a3b-bf16
nvidia-nemotron-3-nano-30b-a3b-bf16Nvidia
57.1
2.5K
131K
¥0 / ¥0输入/输出
155
STstep-1o-turbo-202506
step-1o-turbo-202506Stepfun
56.9
1.5K
-
-
156
Mminimax-m1
minimax-m1Minimax
56.6
5.9K
1M
¥0.95 / ¥9.03输入/输出
157
STstep-3
step-3Stepfun
56.3
1.1K
65.5K
¥1.8 / ¥4.68输入/输出
158
Oo4-mini-2025-04-16
o4-mini-2025-04-16Openai
56.0
7.6K
200K
¥7.92 / ¥31.7输入/输出
159
Aqwen-plus-0125
qwen-plus-0125Alibaba
55.7
968
1M
¥0.83 / ¥2.07输入/输出
160
UNtrinity-large-preview
-
55.5
4.6K
262K
¥1.8 / ¥6.48输入/输出
161
Zglm-4-plus-0111
glm-4-plus-0111Zai
55.2
986
128K
¥72 / ¥72输入/输出
162
Mminimax-m2
minimax-m2Minimax
54.9
1.1K
197K
¥0 / ¥0输入/输出
163
Aqwen3-coder-480b-a35b-instruct
qwen3-coder-480b-a35b-instructAlibaba
54.6
4.1K
262K
¥6.2 / ¥24.8输入/输出
164
Oo1-preview
o1-previewOpenai
54.3
5.4K
128K
¥108 / ¥432输入/输出
165
Aqwq-32b
qwq-32bAlibaba
54.1
4.5K
131K
¥2.07 / ¥6.2输入/输出
166
Aclaude-sonnet-4-20250514-thinking-32k
claude-sonnet-4-20250514-thinking-32kAnthropic
53.8
5.7K
200K
¥21.6 / ¥108输入/输出
167
IA
mercury-2
mercury-2Inception Ai
53.5
472
128K
¥1.8 / ¥5.4输入/输出
168
MAmistral-small-2506
mistral-small-2506Mistral
53.2
2.9K
262K
¥2.88 / ¥14.4输入/输出
169
Aclaude-sonnet-4-20250514
claude-sonnet-4-20250514Anthropic
52.9
6.4K
200K
¥21.6 / ¥108输入/输出
170
Oo3-mini-high
o3-mini-highOpenai
52.7
3.4K
200K
¥7.92 / ¥31.7输入/输出
171
AGring-flash-2.0
ring-flash-2.0Ant Group
52.4
1.1K
131K
¥1.01 / ¥4.1输入/输出
172
CO
command-a-03-2025
command-a-03-2025Cohere
52.1
9.4K
256K
¥18 / ¥72输入/输出
173
Ddeepseek-v3
deepseek-v3Deepseek
51.8
3.8K
128K
¥0 / ¥0输入/输出
174
NVllama-3.3-nemotron-49b-super-v1
llama-3.3-nemotron-49b-super-v1Nvidia
51.5
395
131K
¥0 / ¥0输入/输出
175
Ggemini-2.0-flash-lite-preview-02-05
gemini-2.0-flash-lite-preview-02-05Google
51.3
4.4K
1.05M
¥0.54 / ¥2.16输入/输出
176
STstep-2-16k-exp-202412
step-2-16k-exp-202412Stepfun
51.0
863
16.4K
¥37.5 / ¥118输入/输出
177
Zglm-4.5v
glm-4.5vZai
50.7
749
64K
¥4.32 / ¥13输入/输出
178
TEhunyuan-turbo-0110
hunyuan-turbo-0110Tencent
50.4
414
-
-
179
Ogpt-4.1-mini-2025-04-14
gpt-4.1-mini-2025-04-14Openai
50.1
6.5K
1.05M
¥2.88 / ¥11.5输入/输出
180
NVllama-3.1-nemotron-ultra-253b-v1
llama-3.1-nemotron-ultra-253b-v1Nvidia
49.9
498
128K
¥4.32 / ¥13输入/输出
181
Ggemma-3n-e4b-it
gemma-3n-e4b-itGoogle
49.6
3.7K
128K
¥0 / ¥0输入/输出
182
Aqwen3-30b-a3b
qwen3-30b-a3bAlibaba
49.3
4.6K
128K
¥0.79 / ¥7.78输入/输出
183
Ggemini-1.5-pro-002
gemini-1.5-pro-002Google
49.0
9.8K
-
-
184
TEhunyuan-turbos-20250226
hunyuan-turbos-20250226Tencent
48.7
384
131K
¥0 / ¥0输入/输出
185
Ogpt-5-nano-high
gpt-5-nano-highOpenai
48.5
1.3K
400K
¥0.36 / ¥2.88输入/输出
186
Aqwen2.5-plus-1127
qwen2.5-plus-1127Alibaba
48.2
1.8K
-
-
187
Oo1-mini
o1-miniOpenai
47.9
9K
128K
¥7.92 / ¥31.7输入/输出
188
UNyi-lightning
-
47.6
4.8K
12K
¥1.44 / ¥1.44输入/输出
189
Oo3-mini
o3-miniOpenai
47.3
9.7K
200K
¥7.92 / ¥31.7输入/输出
190
Xgrok-2-2024-08-13
grok-2-2024-08-13Xai
47.1
10.8K
1M
¥9 / ¥18输入/输出
191
AI
olmo-3.1-32b-instruct
olmo-3.1-32b-instructAllenai
46.8
1.9K
200K
¥14.4 / ¥57.6输入/输出
192
AIolmo-3-32b-think
olmo-3-32b-thinkAllenai
46.5
1K
128K
¥2.16 / ¥3.24输入/输出
193
UNathene-v2-chat
-
46.2
4.4K
-
-
194
IB
granite-4.1-8b
granite-4.1-8bIbm
45.9
603
131K
¥0.36 / ¥0.72输入/输出
195
Ggemma-3-4b-it
gemma-3-4b-itGoogle
45.7
780
128K
¥1.44 / ¥1.44输入/输出
196
Xgrok-2-mini-2024-08-13
grok-2-mini-2024-08-13Xai
45.4
8.8K
1M
¥9 / ¥18输入/输出
197
Ggemini-1.5-flash-002
gemini-1.5-flash-002Google
45.1
6.1K
2M
¥0.54 / ¥2.2输入/输出
198
Aclaude-3-7-sonnet-20250219-thinking-32k
claude-3-7-sonnet-20250219-thinking-32kAnthropic
44.8
6.8K
-
-
199
Ogpt-oss-20b
gpt-oss-20bOpenai
44.5
1.7K
131K
¥0.32 / ¥1.3输入/输出
200
Ogpt-4.1-nano-2025-04-14
gpt-4.1-nano-2025-04-14Openai
44.3
1.2K
1.05M
¥14.4 / ¥57.6输入/输出
201
IAmercury
mercuryInception Ai
44.0
288
128K
¥1.8 / ¥5.4输入/输出
202
Mllama-3.1-405b-instruct-bf16
llama-3.1-405b-instruct-bf16Meta
43.7
7.2K
128K
¥0 / ¥0输入/输出
203
Ogpt-4o-2024-05-13
gpt-4o-2024-05-13Openai
43.4
19K
128K
¥36 / ¥108输入/输出
204
Zglm-4-plus
glm-4-plusZai
43.1
4.7K
128K
¥54 / ¥54输入/输出
205
UNathene-70b-0725
-
42.9
3K
-
-
206
NVllama-3.1-nemotron-70b-instruct
llama-3.1-nemotron-70b-instructNvidia
42.6
1.3K
128K
¥0 / ¥0输入/输出
207
TEhunyuan-large-2025-02-10
hunyuan-large-2025-02-10Tencent
42.3
707
-
-
208
Ddeepseek-v2.5-1210
deepseek-v2.5-1210Deepseek
42.0
1.1K
1M
¥1.01 / ¥2.02输入/输出
209
Mllama-4-maverick-17b-128e-instruct
llama-4-maverick-17b-128e-instructMeta
41.7
6.8K
1M
¥1.8 / ¥6.26输入/输出
210
Ogpt-4o-mini-2024-07-18
gpt-4o-mini-2024-07-18Openai
41.5
11.6K
128K
¥1.08 / ¥4.32输入/输出
211
TEhunyuan-standard-2025-02-10
hunyuan-standard-2025-02-10Tencent
41.2
696
-
-
212
Mllama-3.1-405b-instruct-fp8
llama-3.1-405b-instruct-fp8Meta
40.9
10K
128K
¥0 / ¥0输入/输出
213
Aclaude-3-7-sonnet-20250219
claude-3-7-sonnet-20250219Anthropic
40.6
7.5K
200K
¥21.6 / ¥108输入/输出
214
Mllama-3.3-70b-instruct
llama-3.3-70b-instructMeta
40.3
9.4K
128K
¥0 / ¥0输入/输出
215
AIolmo-3.1-32b-think
olmo-3.1-32b-thinkAllenai
40.1
1.4K
200K
¥14.4 / ¥57.6输入/输出
216
Mllama-4-scout-17b-16e-instruct
llama-4-scout-17b-16e-instructMeta
39.8
5K
128K
¥1.44 / ¥5.62输入/输出
217
Aqwen-max-0919
qwen-max-0919Alibaba
39.5
3K
131K
¥2.48 / ¥9.91输入/输出
218
Mllama-3.1-70b-instruct
llama-3.1-70b-instructMeta
39.2
9.4K
131K
¥2.88 / ¥2.88输入/输出
219
Aqwen2.5-72b-instruct
qwen2.5-72b-instructAlibaba
38.9
6.9K
131K
¥4.13 / ¥12.4输入/输出
220
Ogpt-4o-2024-08-06
gpt-4o-2024-08-06Openai
38.7
7.6K
128K
¥18 / ¥72输入/输出
221
Ddeepseek-v2.5
deepseek-v2.5Deepseek
38.4
4.3K
1M
¥1.01 / ¥2.02输入/输出
222
Aclaude-3-5-sonnet-20241022
claude-3-5-sonnet-20241022Anthropic
38.1
15.6K
200K
¥21.6 / ¥108输入/输出
223
Aclaude-3-5-sonnet-20240620
claude-3-5-sonnet-20240620Anthropic
37.8
13.7K
200K
¥21.6 / ¥108输入/输出
224
Ggemini-advanced-0514
gemini-advanced-0514Google
37.5
8.8K
-
-
225
Ggemini-1.5-pro-001
gemini-1.5-pro-001Google
37.3
13.6K
-
-
226
AIllama-3.1-tulu-3-70b
llama-3.1-tulu-3-70bAllenai
37.0
520
-
-
227
MAmistral-large-2407
mistral-large-2407Mistral
36.7
7.5K
131K
¥14.4 / ¥43.2输入/输出
228
MAmistral-small-3.1-24b-instruct-2503
mistral-small-3.1-24b-instruct-2503Mistral
36.4
5.3K
262K
¥2.88 / ¥14.4输入/输出
229
UNreka-core-20240904
-
36.1
1.2K
-
-
230
MAmistral-large-2411
mistral-large-2411Mistral
35.9
4.9K
128K
¥14.4 / ¥43.2输入/输出
231
TEhunyuan-large-vision
hunyuan-large-visionTencent
35.6
930
-
-
232
Ogpt-4-turbo-2024-04-09
gpt-4-turbo-2024-04-09Openai
35.3
16.4K
128K
¥72 / ¥216输入/输出
233
Aamazon-nova-pro-v1.0
amazon-nova-pro-v1.0Amazon
35.0
4.3K
300K
¥5.76 / ¥23输入/输出
234
Ogpt-4-1106-preview
gpt-4-1106-previewOpenai
34.7
17.7K
8.19K
¥216 / ¥432输入/输出
235
Aclaude-3-opus-20240229
claude-3-opus-20240229Anthropic
34.5
33.8K
200K
¥108 / ¥540输入/输出
236
IBibm-granite-h-small
ibm-granite-h-smallIbm
34.2
898
-
-
237
COcommand-r-plus-08-2024
command-r-plus-08-2024Cohere
33.9
1.6K
128K
¥18 / ¥72输入/输出
238
Ogpt-4-0125-preview
gpt-4-0125-previewOpenai
33.6
16K
8.19K
¥216 / ¥432输入/输出
239
UNjamba-1.5-large
-
33.3
1.4K
256K
¥0 / ¥0输入/输出
240
Aclaude-3-5-haiku-20241022
claude-3-5-haiku-20241022Anthropic
33.1
11.9K
200K
¥5.76 / ¥28.8输入/输出
241
AIolmo-2-0325-32b-instruct
olmo-2-0325-32b-instructAllenai
32.8
580
-
-
242
MAmagistral-medium-2506
magistral-medium-2506Mistral
32.5
2K
128K
¥14.4 / ¥36输入/输出
243
MAmistral-small-24b-instruct-2501
mistral-small-24b-instruct-2501Mistral
32.2
2.6K
262K
¥2.88 / ¥14.4输入/输出
244
COc4ai-aya-expanse-32b
c4ai-aya-expanse-32bCohere
31.9
4.8K
-
-
245
Aamazon-nova-lite-v1.0
amazon-nova-lite-v1.0Amazon
31.7
3.3K
300K
¥0.43 / ¥1.73输入/输出
246
Ggemini-1.5-flash-8b-001
gemini-1.5-flash-8b-001Google
31.4
6.2K
2M
¥0.54 / ¥2.2输入/输出
247
Ggemini-1.5-flash-001
gemini-1.5-flash-001Google
31.1
10.9K
2M
¥0.54 / ¥2.2输入/输出
248
UNgemma-2-9b-it-simpo
-
30.8
1.6K
8.19K
¥1.44 / ¥1.44输入/输出
249
NVnemotron-4-340b-instruct
nemotron-4-340b-instructNvidia
30.5
3.3K
-
-
250
Ggemma-2-27b-it
gemma-2-27b-itGoogle
30.3
12.9K
8.19K
¥0.58 / ¥0.58输入/输出
251
Zglm-4-0520
glm-4-0520Zai
30.0
1.6K
128K
¥108 / ¥108输入/输出
252
NVllama-3.1-nemotron-51b-instruct
llama-3.1-nemotron-51b-instructNvidia
29.7
682
128K
¥0 / ¥0输入/输出
253
Mllama-3-70b-instruct
llama-3-70b-instructMeta
29.4
25.9K
8.19K
¥3.67 / ¥5.33输入/输出
254
UNreka-flash-20240904
-
29.1
1.3K
65.5K
¥0.72 / ¥1.44输入/输出
255
Aqwen2.5-coder-32b-instruct
qwen2.5-coder-32b-instructAlibaba
28.9
956
131K
¥2.07 / ¥6.2输入/输出
256
COcommand-r-08-2024
command-r-08-2024Cohere
28.6
1.6K
128K
¥18 / ¥72输入/输出
257
COcommand-r-plus
command-r-plusCohere
28.3
13.2K
128K
¥18 / ¥72输入/输出
258
Aamazon-nova-micro-v1.0
amazon-nova-micro-v1.0Amazon
28.0
3.3K
128K
¥0.25 / ¥1.01输入/输出
259
Aclaude-3-sonnet-20240229
claude-3-sonnet-20240229Anthropic
27.7
19.1K
200K
¥21.6 / ¥108输入/输出
260
M
phi-4
phi-4Microsoft
27.5
4.2K
128K
¥0.9 / ¥3.6输入/输出
261
COc4ai-aya-expanse-8b
c4ai-aya-expanse-8bCohere
27.2
1.7K
-
-
262
Ggemma-2-9b-it
gemma-2-9b-itGoogle
26.9
9.2K
8.19K
¥1.44 / ¥1.44输入/输出
263
TEhunyuan-standard-256k
hunyuan-standard-256kTencent
26.6
538
-
-
264
Aqwen2-72b-instruct
qwen2-72b-instructAlibaba
26.3
6.5K
131K
¥4.13 / ¥12.4输入/输出
265
AIllama-3.1-tulu-3-8b
llama-3.1-tulu-3-8bAllenai
26.1
516
-
-
266
Mllama-3.1-8b-instruct
llama-3.1-8b-instructMeta
25.8
8.4K
131K
¥0.79 / ¥0.79输入/输出
267
UNjamba-1.5-mini
-
25.5
1.5K
256K
¥0 / ¥0输入/输出
268
MAministral-8b-2410
ministral-8b-2410Mistral
25.2
827
128K
¥0.72 / ¥0.72输入/输出
269
Aclaude-3-haiku-20240307
claude-3-haiku-20240307Anthropic
24.9
20.6K
200K
¥1.8 / ¥9输入/输出
270
Ogpt-4-0314
gpt-4-0314Openai
24.6
9.6K
8.19K
¥216 / ¥432输入/输出
271
UNyi-1.5-34b-chat
-
24.4
4.3K
-
-
272
COcommand-r
command-rCohere
24.1
9.2K
128K
¥18 / ¥72输入/输出
273
Mllama-3-8b-instruct
llama-3-8b-instructMeta
23.8
17.3K
8.19K
¥0.29 / ¥0.29输入/输出
274
UNreka-flash-21b-20240226-online
-
23.5
2.6K
-
-
275
Aqwen1.5-110b-chat
qwen1.5-110b-chatAlibaba
23.2
4.4K
-
-
276
UNinternlm2_5-20b-chat
-
23.0
1.7K
-
-
277
Ddeepseek-coder-v2
deepseek-coder-v2Deepseek
22.7
2.6K
1M
¥1.01 / ¥2.02输入/输出
278
UNreka-flash-21b-20240226
-
22.4
4.1K
-
-
279
Ggemma-2-2b-it
gemma-2-2b-itGoogle
22.1
7.9K
128K
¥0 / ¥0输入/输出
280
MAmistral-medium
mistral-mediumMistral
21.8
6.1K
262K
¥2.88 / ¥14.4输入/输出
281
Aqwen1.5-72b-chat
qwen1.5-72b-chatAlibaba
21.6
6.9K
-
-
282
Aqwq-32b-preview
qwq-32b-previewAlibaba
21.3
583
131K
¥2.07 / ¥6.2输入/输出
283
MAmistral-large-2402
mistral-large-2402Mistral
21.0
10.9K
262K
¥2.88 / ¥14.4输入/输出
284
Ogpt-4-0613
gpt-4-0613Openai
20.7
15.3K
8.19K
¥216 / ¥432输入/输出
285
MAmixtral-8x22b-instruct-v0.1
mixtral-8x22b-instruct-v0.1Mistral
20.4
8.7K
64K
¥14.4 / ¥43.2输入/输出
286
Ggemini-pro-dev-api
gemini-pro-dev-apiGoogle
20.2
3.3K
1.05M
¥14.4 / ¥86.4输入/输出
287
UNzephyr-orpo-141b-A35b-v0.1
-
19.9
827
200K
¥108 / ¥432输入/输出
288
UNstarling-lm-7b-beta
-
19.6
2.9K
200K
¥5.4 / ¥18.7输入/输出
289
Mphi-3-medium-4k-instruct
phi-3-medium-4k-instructMicrosoft
19.3
4.2K
4.1K
¥1.22 / ¥4.9输入/输出
290
IBgranite-3.1-8b-instruct
granite-3.1-8b-instructIbm
19.0
560
-
-
291
UNyi-34b-chat
-
18.8
2.7K
-
-
292
Aqwen1.5-32b-chat
qwen1.5-32b-chatAlibaba
18.5
3.9K
-
-
293
Mllama-2-70b-chat
llama-2-70b-chatMeta
18.2
6.6K
-
-
294
Ggemini-pro
gemini-proGoogle
17.9
1.1K
1.05M
¥14.4 / ¥86.4输入/输出
295
MAmixtral-8x7b-instruct-v0.1
mixtral-8x7b-instruct-v0.1Mistral
17.6
12.8K
32K
¥5.04 / ¥5.04输入/输出
296
UNstarling-lm-7b-alpha
-
17.4
1.9K
200K
¥5.4 / ¥18.7输入/输出
297
Mwizardlm-70b
wizardlm-70bMicrosoft
17.1
1.3K
-
-
298
IBgranite-3.1-2b-instruct
granite-3.1-2b-instructIbm
16.8
549
-
-
299
Mphi-3-small-8k-instruct
phi-3-small-8k-instructMicrosoft
16.5
3.1K
8.19K
¥1.08 / ¥4.32输入/输出
300
Mllama-3.2-3b-instruct
llama-3.2-3b-instructMeta
16.2
1.4K
131K
¥0.22 / ¥0.35输入/输出
301
UNtulu-2-dpo-70b
-
16.0
1.1K
-
-
302
UNnous-hermes-2-mixtral-8x7b-dpo
-
15.7
651
1M
¥36 / ¥180输入/输出
303
Aqwen1.5-14b-chat
qwen1.5-14b-chatAlibaba
15.4
3.1K
-
-
304
UNdbrx-instruct-preview
-
15.1
5.6K
-
-
305
UNvicuna-33b
-
14.8
4K
-
-
306
IBgranite-3.0-8b-instruct
granite-3.0-8b-instructIbm
14.6
1.1K
-
-
307
NVllama2-70b-steerlm-chat
llama2-70b-steerlm-chatNvidia
14.3
642
-
-
308
Ogpt-3.5-turbo-0125
gpt-3.5-turbo-0125Openai
14.0
11.4K
16.4K
¥3.6 / ¥10.8输入/输出
309
Mllama-2-13b-chat
llama-2-13b-chatMeta
13.7
3.3K
-
-
310
UNsnowflake-arctic-instruct
-
13.4
5.4K
-
-
311
UNopenchat-3.5-0106
-
13.2
2.2K
-
-
312
MAmistral-7b-instruct-v0.2
mistral-7b-instruct-v0.2Mistral
12.9
3.3K
262K
¥2.88 / ¥14.4输入/输出
313
Ggemma-1.1-7b-it
gemma-1.1-7b-itGoogle
12.6
4.1K
-
-
314
Aqwen1.5-7b-chat
qwen1.5-7b-chatAlibaba
12.3
828
-
-
315
UNsolar-10.7b-instruct-v1.0
-
12.0
721
128K
¥0 / ¥0输入/输出
316
IBgranite-3.0-2b-instruct
granite-3.0-2b-instructIbm
11.8
1.2K
-
-
317
Mwizardlm-13b
wizardlm-13bMicrosoft
11.5
1.2K
-
-
318
Mphi-3-mini-4k-instruct-june-2024
phi-3-mini-4k-instruct-june-2024Microsoft
11.2
2K
4.1K
¥0.94 / ¥3.74输入/输出
319
UNopenchat-3.5
-
10.9
1.4K
-
-
320
Mcodellama-34b-instruct
codellama-34b-instructMeta
10.6
1.2K
-
-
321
Ddeepseek-llm-67b-chat
deepseek-llm-67b-chatDeepseek
10.4
876
1M
¥1.01 / ¥2.02输入/输出
322
UNdolphin-2.2.1-mistral-7b
-
10.1
308
262K
¥2.88 / ¥14.4输入/输出
323
UNopenhermes-2.5-mistral-7b
-
9.8
884
1M
¥36 / ¥180输入/输出
324
Mphi-3-mini-4k-instruct
phi-3-mini-4k-instructMicrosoft
9.5
3.5K
4.1K
¥0.94 / ¥3.74输入/输出
325
UNzephyr-7b-beta
-
9.2
2K
-
-
326
UNguanaco-33b
-
9.0
526
200K
¥14.4 / ¥57.6输入/输出
327
Mllama-3.2-1b-instruct
llama-3.2-1b-instructMeta
8.7
1.4K
16.4K
¥0.07 / ¥0.08输入/输出
328
Ogpt-3.5-turbo-1106
gpt-3.5-turbo-1106Openai
8.4
3K
16.4K
¥7.2 / ¥14.4输入/输出
329
Mllama-2-7b-chat
llama-2-7b-chatMeta
8.1
2.5K
128K
¥4.03 / ¥48输入/输出
330
UNsmollm2-1.7b-instruct
-
7.8
352
-
-
331
UNmpt-30b-chat
-
7.6
509
-
-
332
UNvicuna-13b
-
7.3
3.3K
-
-
333
UNzephyr-7b-alpha
-
7.0
294
-
-
334
Mphi-3-mini-128k-instruct
phi-3-mini-128k-instructMicrosoft
6.7
3.4K
128K
¥0.94 / ¥3.74输入/输出
335
Ggemma-7b-it
gemma-7b-itGoogle
6.4
1.6K
-
-
336
UNfalcon-180b-chat
-
6.2
206
-
-
337
UNstripedhyena-nous-7b
-
5.9
863
-
-
338
Gpalm-2
palm-2Google
5.6
1.4K
-
-
339
Aqwen-14b-chat
qwen-14b-chatAlibaba
5.3
894
32.8K
¥1.04 / ¥3.1输入/输出
340
AIolmo-7b-instruct
olmo-7b-instructAllenai
5.0
1.2K
-
-
341
UNvicuna-7b
-
4.8
1.2K
-
-
342
MAmistral-7b-instruct
mistral-7b-instructMistral
4.5
1.6K
262K
¥2.88 / ¥14.4输入/输出
343
Ggemma-1.1-2b-it
gemma-1.1-2b-itGoogle
4.2
1.9K
-
-
344
UNkoala-13b
-
3.9
1.2K
-
-
345
Aqwen1.5-4b-chat
qwen1.5-4b-chatAlibaba
3.6
1.3K
-
-
346
Ggemma-2b-it
gemma-2b-itGoogle
3.4
879
-
-
347
UNchatglm3-6b
-
3.1
888
200K
¥5.4 / ¥18.7输入/输出
348
UNRWKV-4-Raven-14B
-
2.8
844
-
-
349
UNchatglm2-6b
-
2.5
436
200K
¥5.4 / ¥18.7输入/输出
350
UNmpt-7b-chat
-
2.2
677
-
-
351
UNgpt4all-13b-snoozy
-
2.0
305
1M
¥36 / ¥216输入/输出
352
UNoasst-pythia-12b
-
1.7
1.1K
-
-
353
UNalpaca-13b
-
1.4
986
-
-
354
UNfastchat-t5-3b
-
1.1
685
-
-
355
UNchatglm-6b
-
0.8
819
200K
¥5.4 / ¥18.7输入/输出
356
Mllama-13b
llama-13bMeta
0.6
414
-
-
357
UNstablelm-tuned-alpha-7b
-
0.3
615
-
-
358
UNdolly-v2-12b
-
0.0
589
-
-
claude-opus-4-6-thinking 为什么排第一
claude-opus-4-6-thinking 当前排名第 1，厂商为 anthropic，百分制分数 100.0，样本量 5.6K。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
生命、物理与社会科学常见问题
生命、物理与社会科学排行榜看什么指标？
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。
生命、物理与社会科学模型应该怎么选？
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。