1
A
claude-opus-4-6-thinking
claude-opus-4-6-thinkingAnthropic
100.0
10K
1M
¥36 / ¥180输入/输出
对话 · 文本 · 指令遵循排行榜
基于公开偏好评测数据展示 文本 / 指令遵循 榜单，每个榜单独立排序。
指令遵循模型怎么选？
指令遵循排行榜用于回答“指令遵循哪个 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 10K。 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-thinkingclaude-opus-4-7mimo-v2.5-pro
2
Aclaude-opus-4-6
claude-opus-4-6Anthropic
99.7
11.2K
1M
¥36 / ¥180输入/输出
3
Aclaude-opus-4-7-thinking
claude-opus-4-7-thinkingAnthropic
99.4
6.6K
1M
¥36 / ¥180输入/输出
4
Aclaude-opus-4-7
claude-opus-4-7Anthropic
99.2
7K
1M
¥36 / ¥180输入/输出
5
MI
mimo-v2.5-pro
mimo-v2.5-proXiaomi
98.9
5.1K
1.05M
¥7.2 / ¥21.6输入/输出
6
O
gpt-5.5-high
gpt-5.5-highOpenai
98.6
5.4K
1.05M
¥36 / ¥216输入/输出
7
Aclaude-sonnet-4-6
claude-sonnet-4-6Anthropic
98.3
8.5K
1M
¥21.6 / ¥108输入/输出
8
Aclaude-opus-4-5-20251101-thinking-32k
claude-opus-4-5-20251101-thinking-32kAnthropic
98.1
9.5K
200K
¥108 / ¥540输入/输出
9
Ogpt-5.4-high
gpt-5.4-highOpenai
97.8
8.9K
1.05M
¥18 / ¥108输入/输出
10
Aclaude-opus-4-5-20251101
claude-opus-4-5-20251101Anthropic
97.5
18.9K
200K
¥36 / ¥180输入/输出
11
Ogpt-5.5
gpt-5.5Openai
97.2
5.6K
1.05M
¥36 / ¥216输入/输出
12
G
gemini-3.1-pro-preview
gemini-3.1-pro-previewGoogle
96.9
13.5K
1.05M
¥14.4 / ¥86.4输入/输出
13
A
qwen3.5-max-preview
qwen3.5-max-previewAlibaba
96.7
6.3K
-
-
14
B
ernie-5.1
ernie-5.1Baidu
96.4
4.4K
119K
¥5.4 / ¥21.6输入/输出
15
Ggemini-3.5-flash
gemini-3.5-flashGoogle
96.1
3K
1.05M
¥10.8 / ¥64.8输入/输出
16
Aqwen3.7-max-preview
qwen3.7-max-previewAlibaba
95.8
1.3K
1M
¥18 / ¥54输入/输出
17
Ggemini-3-pro
gemini-3-proGoogle
95.5
11.2K
1.05M
¥14.4 / ¥86.4输入/输出
18
Aclaude-sonnet-4-5-20250929
claude-sonnet-4-5-20250929Anthropic
95.3
21.5K
200K
¥21.6 / ¥108输入/输出
19
Ogpt-5.4
gpt-5.4Openai
95.0
9.6K
1.05M
¥18 / ¥108输入/输出
20
Aclaude-sonnet-4-5-20250929-thinking-32k
claude-sonnet-4-5-20250929-thinking-32kAnthropic
94.7
21.9K
200K
¥21.6 / ¥108输入/输出
21
Z
glm-5.1
glm-5.1Zai
94.4
4.5K
200K
¥0 / ¥0输入/输出
22
M
kimi-k2.6
kimi-k2.6Moonshot
94.2
5K
262K
¥6.84 / ¥28.8输入/输出
23
MImimo-v2-pro
mimo-v2-proXiaomi
93.9
7.2K
1.05M
¥7.2 / ¥21.6输入/输出
24
Ogpt-5.1-high
gpt-5.1-highOpenai
93.6
10.8K
400K
¥9 / ¥72输入/输出
25
M
muse-spark
muse-sparkMeta
93.3
3.9K
-
-
26
Ggemini-3-flash
gemini-3-flashGoogle
93.0
8.1K
1.05M
¥3.6 / ¥21.6输入/输出
27
Aclaude-opus-4-1-20250805-thinking-16k
claude-opus-4-1-20250805-thinking-16kAnthropic
92.8
13K
200K
¥108 / ¥540输入/输出
28
Ggemini-2.5-pro
gemini-2.5-proGoogle
92.5
33.4K
1.05M
¥9 / ¥72输入/输出
29
D
deepseek-v4-pro
deepseek-v4-proDeepseek
92.2
5.5K
1M
¥3.13 / ¥6.26输入/输出
30
Ddeepseek-v4-pro-thinking
deepseek-v4-pro-thinkingDeepseek
91.9
5.3K
1M
¥3.13 / ¥6.26输入/输出
31
Aclaude-opus-4-1-20250805
claude-opus-4-1-20250805Anthropic
91.6
20.3K
200K
¥108 / ¥540输入/输出
32
Aqwen3.6-max-preview
qwen3.6-max-previewAlibaba
91.4
1.5K
246K
¥9.5 / ¥56.9输入/输出
33
MImimo-v2.5
mimo-v2.5Xiaomi
91.1
5.3K
1.05M
¥2.88 / ¥14.4输入/输出
34
Ggemma-4-31b
gemma-4-31bGoogle
90.8
1.6K
262K
¥3.24 / ¥7.2输入/输出
35
Mkimi-k2.5-instant
kimi-k2.5-instantMoonshot
90.5
2.2K
262K
¥4.32 / ¥21.6输入/输出
36
Mkimi-k2.5-thinking
kimi-k2.5-thinkingMoonshot
90.3
10.8K
262K
¥4.32 / ¥21.6输入/输出
37
Zglm-5
glm-5Zai
90.0
6.8K
205K
¥7.2 / ¥23输入/输出
38
A
amazon-nova-experimental-chat-26-02-10
amazon-nova-experimental-chat-26-02-10Amazon
89.7
935
-
-
39
Aqwen3.6-plus
qwen3.6-plusAlibaba
89.4
6K
1M
¥3.6 / ¥21.6输入/输出
40
Aqwen3.5-397b-a17b
qwen3.5-397b-a17bAlibaba
89.1
9.9K
262K
¥3.1 / ¥18.6输入/输出
41
X
grok-4.20-beta-0309-reasoning
grok-4.20-beta-0309-reasoningXai
88.9
9.4K
2M
¥14.4 / ¥43.2输入/输出
42
Ddeepseek-v4-flash
deepseek-v4-flashDeepseek
88.6
5.6K
1M
¥1.01 / ¥2.02输入/输出
43
Ggemma-4-26b-a4b
gemma-4-26b-a4bGoogle
88.3
1.6K
262K
¥0.94 / ¥2.88输入/输出
44
Aqwen3-max-preview
qwen3-max-previewAlibaba
88.0
7.3K
262K
¥6.2 / ¥24.8输入/输出
45
Xgrok-4.20-multi-agent-beta-0309
grok-4.20-multi-agent-beta-0309Xai
87.7
9.1K
2M
¥14.4 / ¥43.2输入/输出
46
Ogpt-5.1
gpt-5.1Openai
87.5
11.9K
400K
¥9 / ¥72输入/输出
47
Ggemini-3-flash (thinking-minimal)
gemini-3-flash (thinking-minimal)Google
87.2
15.8K
1.05M
¥3.6 / ¥21.6输入/输出
48
Ogpt-5.2-chat-latest-20260210
gpt-5.2-chat-latest-20260210Openai
86.9
10K
400K
¥12.6 / ¥101输入/输出
49
Ddeepseek-v4-flash-thinking
deepseek-v4-flash-thinkingDeepseek
86.6
5.6K
1M
¥1.01 / ¥2.02输入/输出
50
Xgrok-4.20-beta1
grok-4.20-beta1Xai
86.4
7.4K
2M
¥14.4 / ¥43.2输入/输出
51
Bernie-5.0-0110
ernie-5.0-0110Baidu
86.1
10K
128K
¥7.92 / ¥14.4输入/输出
52
Zglm-4.7
glm-4.7Zai
85.8
3.2K
205K
¥0 / ¥0输入/输出
53
B
dola-seed-2.0-pro
dola-seed-2.0-proBytedance
85.5
11.6K
-
-
54
Zglm-4.6
glm-4.6Zai
85.2
10K
205K
¥4.32 / ¥15.8输入/输出
55
Ddeepseek-v3.2
deepseek-v3.2Deepseek
85.0
12.5K
128K
¥2.09 / ¥3.1输入/输出
56
Aclaude-haiku-4-5-20251001
claude-haiku-4-5-20251001Anthropic
84.7
22.4K
200K
¥7.2 / ¥36输入/输出
57
M
longcat-flash-chat-2602-exp
longcat-flash-chat-2602-expMeituan
84.4
7.5K
128K
¥1.08 / ¥10.8输入/输出
58
Xgrok-3-preview-02-24
grok-3-preview-02-24Xai
84.1
9.7K
1M
¥9 / ¥18输入/输出
59
Aqwen3-vl-235b-a22b-instruct
qwen3-vl-235b-a22b-instructAlibaba
83.8
2.9K
128K
¥2.16 / ¥8.64输入/输出
60
Ogpt-5.2-high
gpt-5.2-highOpenai
83.6
13.7K
400K
¥12.6 / ¥101输入/输出
61
Aqwen3-235b-a22b-instruct-2507
qwen3-235b-a22b-instruct-2507Alibaba
83.3
26.2K
128K
¥2.09 / ¥8.23输入/输出
62
Ogpt-5.5-instant
gpt-5.5-instantOpenai
83.0
8.7K
400K
¥9 / ¥72输入/输出
63
Ddeepseek-v3.2-thinking
deepseek-v3.2-thinkingDeepseek
82.7
10.7K
128K
¥2.09 / ¥3.1输入/输出
64
Aclaude-opus-4-20250514-thinking-16k
claude-opus-4-20250514-thinking-16kAnthropic
82.5
9.1K
200K
¥108 / ¥540输入/输出
65
MA
mistral-large-3
mistral-large-3Mistral
82.2
11.8K
262K
¥3.6 / ¥10.8输入/输出
66
Ggemini-2.5-flash
gemini-2.5-flashGoogle
81.9
33K
1.05M
¥2.16 / ¥18输入/输出
67
Ddeepseek-v3.1-terminus-thinking
deepseek-v3.1-terminus-thinkingDeepseek
81.6
864
128K
¥1.8 / ¥5.04输入/输出
68
Ogpt-5.4-mini-high
gpt-5.4-mini-highOpenai
81.3
8.6K
400K
¥5.4 / ¥32.4输入/输出
69
Ogpt-4.5-preview-2025-02-27
gpt-4.5-preview-2025-02-27Openai
81.1
5.5K
8.19K
¥216 / ¥432输入/输出
70
Ochatgpt-4o-latest-20250326
chatgpt-4o-latest-20250326Openai
80.8
22.8K
128K
¥18 / ¥72输入/输出
71
Zglm-4.5
glm-4.5Zai
80.5
6.2K
131K
¥4.32 / ¥15.8输入/输出
72
Ddeepseek-v3.2-exp
deepseek-v3.2-expDeepseek
80.2
3.3K
128K
¥0 / ¥0输入/输出
73
Ddeepseek-v3.1-thinking
deepseek-v3.1-thinkingDeepseek
79.9
2.9K
128K
¥1.44 / ¥5.04输入/输出
74
Ogpt-5.2
gpt-5.2Openai
79.7
14.2K
400K
¥12.6 / ¥101输入/输出
75
Mkimi-k2-thinking-turbo
kimi-k2-thinking-turboMoonshot
79.4
17.1K
262K
¥17.3 / ¥72输入/输出
76
Bernie-5.0-preview-1203
ernie-5.0-preview-1203Baidu
79.1
2.6K
128K
¥7.92 / ¥14.4输入/输出
77
M
minimax-m2.7
minimax-m2.7Minimax
78.8
7.1K
205K
¥0 / ¥0输入/输出
78
Ddeepseek-v3.2-exp-thinking
deepseek-v3.2-exp-thinkingDeepseek
78.6
2.5K
128K
¥0 / ¥0输入/输出
79
Xgrok-4.1
grok-4.1Xai
78.3
17.8K
200K
¥14.4 / ¥72输入/输出
80
MAmistral-medium-2508
mistral-medium-2508Mistral
78.0
25.9K
262K
¥2.88 / ¥14.4输入/输出
81
Aqwen3-max-2025-09-23
qwen3-max-2025-09-23Alibaba
77.7
2.6K
258K
¥6.19 / ¥24.7输入/输出
82
Mminimax-m2.1-preview
minimax-m2.1-previewMinimax
77.4
4.5K
205K
¥0 / ¥0输入/输出
83
Mlongcat-flash-chat
longcat-flash-chatMeituan
77.2
3K
128K
¥1.08 / ¥10.8输入/输出
84
Xgrok-4.1-thinking
grok-4.1-thinkingXai
76.9
17.6K
200K
¥14.4 / ¥72输入/输出
85
Aqwen3.5-122b-a10b
qwen3.5-122b-a10bAlibaba
76.6
8.3K
262K
¥2.88 / ¥23输入/输出
86
MImimo-v2-omni
mimo-v2-omniXiaomi
76.3
958
262K
¥2.88 / ¥14.4输入/输出
87
TE
hunyuan-vision-1.5-thinking
hunyuan-vision-1.5-thinkingTencent
76.0
626
-
-
88
Bernie-5.0-preview-1022
ernie-5.0-preview-1022Baidu
75.8
1.3K
128K
¥7.92 / ¥14.4输入/输出
89
Ggemini-2.5-flash-preview-09-2025
gemini-2.5-flash-preview-09-2025Google
75.5
9.2K
1M
¥2.16 / ¥18输入/输出
90
TEhunyuan-hy3-preview
hunyuan-hy3-previewTencent
75.2
1.9K
256K
¥0 / ¥0输入/输出
91
Aamazon-nova-experimental-chat-12-10
amazon-nova-experimental-chat-12-10Amazon
74.9
921
-
-
92
Xgrok-4-fast-chat
grok-4-fast-chatXai
74.7
1.7K
2M
¥1.44 / ¥3.6输入/输出
93
MImimo-v2-flash (non-thinking)
mimo-v2-flash (non-thinking)Xiaomi
74.4
13.1K
262K
¥0.72 / ¥2.16输入/输出
94
Aqwen3.5-27b
qwen3.5-27bAlibaba
74.1
7.9K
262K
¥2.16 / ¥17.3输入/输出
95
Aqwen3-next-80b-a3b-instruct
qwen3-next-80b-a3b-instructAlibaba
73.8
6.3K
131K
¥1.04 / ¥4.13输入/输出
96
Ddeepseek-v3.1
deepseek-v3.1Deepseek
73.5
3.7K
128K
¥1.44 / ¥5.04输入/输出
97
Aamazon-nova-experimental-chat-11-10
amazon-nova-experimental-chat-11-10Amazon
73.3
6.7K
-
-
98
Ogpt-5-high
gpt-5-highOpenai
73.0
8.3K
400K
¥9 / ¥72输入/输出
99
Xgrok-4-0709
grok-4-0709Xai
72.7
10.8K
256K
¥21.6 / ¥108输入/输出
100
ST
step-3.5-flash
step-3.5-flashStepfun
72.4
10.2K
256K
¥0.69 / ¥2.07输入/输出
101
Aqwen3-235b-a22b-thinking-2507
qwen3-235b-a22b-thinking-2507Alibaba
72.1
2.1K
131K
¥2.07 / ¥8.26输入/输出
102
Aamazon-nova-experimental-chat-26-01-10
amazon-nova-experimental-chat-26-01-10Amazon
71.9
926
-
-
103
Ogpt-5-chat
gpt-5-chatOpenai
71.6
8.1K
400K
¥9 / ¥72输入/输出
104
Aqwen3.5-35b-a3b
qwen3.5-35b-a3bAlibaba
71.3
8.5K
262K
¥1.8 / ¥14.4输入/输出
105
Ddeepseek-r1-0528
deepseek-r1-0528Deepseek
71.0
4K
164K
¥3.6 / ¥15.5输入/输出
106
Xgrok-4-fast-reasoning
grok-4-fast-reasoningXai
70.8
5.3K
2M
¥1.44 / ¥3.6输入/输出
107
Ddeepseek-v3.1-terminus
deepseek-v3.1-terminusDeepseek
70.5
1K
128K
¥1.8 / ¥5.04输入/输出
108
Ggemini-3.1-flash-lite-preview
gemini-3.1-flash-lite-previewGoogle
70.2
11K
1.05M
¥1.8 / ¥10.8输入/输出
109
Xgrok-4.3
grok-4.3Xai
69.9
5.3K
1M
¥9 / ¥18输入/输出
110
MImimo-v2-flash (thinking)
mimo-v2-flash (thinking)Xiaomi
69.6
3K
262K
¥0.72 / ¥2.16输入/输出
111
TEhunyuan-t1-20250711
hunyuan-t1-20250711Tencent
69.4
1.1K
131K
¥0 / ¥0输入/输出
112
Xgrok-4-1-fast-reasoning
grok-4-1-fast-reasoningXai
69.1
15.7K
2M
¥1.44 / ¥3.6输入/输出
113
Aclaude-sonnet-4-20250514-thinking-32k
claude-sonnet-4-20250514-thinking-32kAnthropic
68.8
8.6K
200K
¥21.6 / ¥108输入/输出
114
Ogpt-5.3-chat-latest
gpt-5.3-chat-latestOpenai
68.5
9.6K
128K
¥12.6 / ¥101输入/输出
115
Aqwen3-vl-235b-a22b-thinking
qwen3-vl-235b-a22b-thinkingAlibaba
68.2
2.1K
131K
¥2.06 / ¥8.26输入/输出
116
Aclaude-opus-4-20250514
claude-opus-4-20250514Anthropic
68.0
10.7K
200K
¥108 / ¥540输入/输出
117
Aqwen3.5-flash
qwen3.5-flashAlibaba
67.7
9.1K
1M
¥1.24 / ¥12.4输入/输出
118
Oo3-2025-04-16
o3-2025-04-16Openai
67.4
15.5K
200K
¥14.4 / ¥57.6输入/输出
119
Oo1-2024-12-17
o1-2024-12-17Openai
67.1
10.2K
128K
¥108 / ¥432输入/输出
120
Ggemini-2.5-flash-lite-preview-06-17-thinking
gemini-2.5-flash-lite-preview-06-17-thinkingGoogle
66.9
8.1K
65.5K
¥0.72 / ¥2.88输入/输出
121
Ogpt-4.1-2025-04-14
gpt-4.1-2025-04-14Openai
66.6
13.3K
1.05M
¥14.4 / ¥57.6输入/输出
122
Aamazon-nova-experimental-chat-10-20
amazon-nova-experimental-chat-10-20Amazon
66.3
3K
-
-
123
Aqwen3-30b-a3b-instruct-2507
qwen3-30b-a3b-instruct-2507Alibaba
66.0
6K
262K
¥2.16 / ¥3.6输入/输出
124
Aqwen3-235b-a22b-no-thinking
qwen3-235b-a22b-no-thinkingAlibaba
65.7
9.3K
131K
¥2.07 / ¥8.26输入/输出
125
Ogpt-5.4-nano-high
gpt-5.4-nano-highOpenai
65.5
8.3K
400K
¥1.44 / ¥9输入/输出
126
Ogpt-5-mini-high
gpt-5-mini-highOpenai
65.2
6.9K
400K
¥1.8 / ¥14.4输入/输出
127
Ddeepseek-r1
deepseek-r1Deepseek
64.9
6.4K
164K
¥5.04 / ¥18输入/输出
128
Xgrok-3-mini-high
grok-3-mini-highXai
64.6
4.2K
128K
¥0 / ¥0输入/输出
129
Aqwen3-coder-480b-a35b-instruct
qwen3-coder-480b-a35b-instructAlibaba
64.3
6.2K
262K
¥6.2 / ¥24.8输入/输出
130
Ggemini-2.5-flash-lite-preview-09-2025-no-thinking
gemini-2.5-flash-lite-preview-09-2025-no-thinkingGoogle
64.1
12.9K
1.05M
¥0.72 / ¥2.88输入/输出
131
Mminimax-m2.5
minimax-m2.5Minimax
63.8
11.2K
205K
¥0 / ¥0输入/输出
132
Zglm-4.5-air
glm-4.5-airZai
63.5
8.1K
131K
¥0 / ¥0输入/输出
133
Zglm-4.6v
glm-4.6vZai
63.2
733
128K
¥2.16 / ¥6.48输入/输出
134
Aclaude-3-7-sonnet-20250219-thinking-32k
claude-3-7-sonnet-20250219-thinking-32kAnthropic
63.0
10.1K
-
-
135
Aclaude-sonnet-4-20250514
claude-sonnet-4-20250514Anthropic
62.7
10K
200K
¥21.6 / ¥108输入/输出
136
NV
nvidia-nemotron-3-super-120b-a12b
nvidia-nemotron-3-super-120b-a12bNvidia
62.4
2K
262K
¥1.44 / ¥5.76输入/输出
137
Mkimi-k2-0905-preview
kimi-k2-0905-previewMoonshot
62.1
2.9K
262K
¥4.32 / ¥18输入/输出
138
Ddeepseek-v3-0324
deepseek-v3-0324Deepseek
61.8
12.4K
75K
¥1.44 / ¥5.76输入/输出
139
Xgrok-3-mini-beta
grok-3-mini-betaXai
61.6
5.5K
1M
¥9 / ¥18输入/输出
140
Aqwen3-next-80b-a3b-thinking
qwen3-next-80b-a3b-thinkingAlibaba
61.3
3.5K
131K
¥1.04 / ¥10.3输入/输出
141
Oo1-preview
o1-previewOpenai
61.0
12.8K
128K
¥108 / ¥432输入/输出
142
TEhunyuan-turbos-20250416
hunyuan-turbos-20250416Tencent
60.7
2.4K
131K
¥0 / ¥0输入/输出
143
MAmistral-medium-2505
mistral-medium-2505Mistral
60.4
7.9K
262K
¥2.88 / ¥14.4输入/输出
144
Oo3-mini-high
o3-mini-highOpenai
60.2
6.7K
200K
¥7.92 / ¥31.7输入/输出
145
Ggemini-2.0-flash-001
gemini-2.0-flash-001Google
59.9
13.6K
1.05M
¥1.08 / ¥4.32输入/输出
146
Anova-2-lite
nova-2-liteAmazon
59.6
3.3K
128K
¥2.38 / ¥19.8输入/输出
147
Aqwen2.5-max
qwen2.5-maxAlibaba
59.3
11K
32K
¥11.5 / ¥46输入/输出
148
UNtrinity-large-preview
-
59.1
8.5K
262K
¥1.8 / ¥6.48输入/输出
149
Mminimax-m2
minimax-m2Minimax
58.8
2K
197K
¥0 / ¥0输入/输出
150
Aqwen3-235b-a22b
qwen3-235b-a22bAlibaba
58.5
6.2K
131K
¥2.07 / ¥8.26输入/输出
151
Ogpt-4.1-mini-2025-04-14
gpt-4.1-mini-2025-04-14Openai
58.2
10.1K
1.05M
¥2.88 / ¥11.5输入/输出
152
STstep-3
step-3Stepfun
57.9
1.6K
65.5K
¥1.8 / ¥4.68输入/输出
153
Zglm-4.7-flash
glm-4.7-flashZai
57.7
3.2K
200K
¥0 / ¥0输入/输出
154
UNtrinity-large-thinking
-
57.4
7.9K
262K
¥1.8 / ¥6.48输入/输出
155
Aclaude-3-7-sonnet-20250219
claude-3-7-sonnet-20250219Anthropic
57.1
12.3K
200K
¥21.6 / ¥108输入/输出
156
Mkimi-k2-0711-preview
kimi-k2-0711-previewMoonshot
56.8
6.8K
131K
¥4.32 / ¥18输入/输出
157
Ggemma-3-27b-it
gemma-3-27b-itGoogle
56.5
12.5K
128K
¥2.15 / ¥2.15输入/输出
158
IA
mercury-2
mercury-2Inception Ai
56.3
836
128K
¥1.8 / ¥5.4输入/输出
159
Oo4-mini-2025-04-16
o4-mini-2025-04-16Openai
56.0
11.9K
200K
¥7.92 / ¥31.7输入/输出
160
Ogpt-oss-120b
gpt-oss-120bOpenai
55.7
7.8K
131K
¥1.08 / ¥4.32输入/输出
161
AG
ling-flash-2.0
ling-flash-2.0Ant Group
55.4
1.8K
131K
¥1.01 / ¥4.1输入/输出
162
TEhunyuan-turbos-20250226
hunyuan-turbos-20250226Tencent
55.2
886
131K
¥0 / ¥0输入/输出
163
Aamazon-nova-experimental-chat-10-09
amazon-nova-experimental-chat-10-09Amazon
54.9
720
-
-
164
Ddeepseek-v3
deepseek-v3Deepseek
54.6
8.6K
128K
¥0 / ¥0输入/输出
165
Oo3-mini
o3-miniOpenai
54.3
17K
200K
¥7.92 / ¥31.7输入/输出
166
Zglm-4.5v
glm-4.5vZai
54.0
1.3K
64K
¥4.32 / ¥13输入/输出
167
AGring-flash-2.0
ring-flash-2.0Ant Group
53.8
1.9K
131K
¥1.01 / ¥4.1输入/输出
168
UNintellect-3
-
53.5
1.4K
131K
¥1.44 / ¥7.92输入/输出
169
Mminimax-m1
minimax-m1Minimax
53.2
8.7K
1M
¥0.95 / ¥9.03输入/输出
170
MAmistral-small-2506
mistral-small-2506Mistral
52.9
4.4K
262K
¥2.88 / ¥14.4输入/输出
171
STstep-1o-turbo-202506
step-1o-turbo-202506Stepfun
52.6
2.1K
-
-
172
CO
command-a-03-2025
command-a-03-2025Cohere
52.4
15.5K
256K
¥18 / ¥72输入/输出
173
NVllama-3.1-nemotron-ultra-253b-v1
llama-3.1-nemotron-ultra-253b-v1Nvidia
52.1
660
128K
¥4.32 / ¥13输入/输出
174
Ogpt-5-nano-high
gpt-5-nano-highOpenai
51.8
2K
400K
¥0.36 / ¥2.88输入/输出
175
Aqwen3-32b
qwen3-32bAlibaba
51.5
858
131K
¥2.07 / ¥8.26输入/输出
176
Ggemini-2.0-flash-lite-preview-02-05
gemini-2.0-flash-lite-preview-02-05Google
51.3
9.2K
1.05M
¥0.54 / ¥2.16输入/输出
177
Oo1-mini
o1-miniOpenai
51.0
21.5K
128K
¥7.92 / ¥31.7输入/输出
178
NVnvidia-nemotron-3-nano-30b-a3b-bf16
nvidia-nemotron-3-nano-30b-a3b-bf16Nvidia
50.7
4.2K
131K
¥0 / ¥0输入/输出
179
Aqwen-plus-0125
qwen-plus-0125Alibaba
50.4
2.2K
1M
¥0.83 / ¥2.07输入/输出
180
Ggemma-3-12b-it
gemma-3-12b-itGoogle
50.1
1.1K
128K
¥1.96 / ¥1.96输入/输出
181
AI
olmo-3.1-32b-instruct
olmo-3.1-32b-instructAllenai
49.9
3.2K
200K
¥14.4 / ¥57.6输入/输出
182
NVnvidia-llama-3.3-nemotron-super-49b-v1.5
nvidia-llama-3.3-nemotron-super-49b-v1.5Nvidia
49.6
807
131K
¥2.88 / ¥2.88输入/输出
183
Aqwq-32b
qwq-32bAlibaba
49.3
7.2K
131K
¥2.07 / ¥6.2输入/输出
184
Aclaude-3-5-sonnet-20241022
claude-3-5-sonnet-20241022Anthropic
49.0
31.3K
200K
¥21.6 / ¥108输入/输出
185
Ggemini-1.5-pro-002
gemini-1.5-pro-002Google
48.7
22.8K
-
-
186
NVllama-3.3-nemotron-49b-super-v1
llama-3.3-nemotron-49b-super-v1Nvidia
48.5
803
131K
¥0 / ¥0输入/输出
187
Zglm-4-plus-0111
glm-4-plus-0111Zai
48.2
2.2K
128K
¥72 / ¥72输入/输出
188
STstep-2-16k-exp-202412
step-2-16k-exp-202412Stepfun
47.9
2K
16.4K
¥37.5 / ¥118输入/输出
189
Aqwen3-30b-a3b
qwen3-30b-a3bAlibaba
47.6
6.1K
128K
¥0.79 / ¥7.78输入/输出
190
Ddeepseek-v2.5-1210
deepseek-v2.5-1210Deepseek
47.4
3K
1M
¥1.01 / ¥2.02输入/输出
191
TEhunyuan-turbo-0110
hunyuan-turbo-0110Tencent
47.1
842
-
-
192
UNyi-lightning
-
46.8
10.9K
12K
¥1.44 / ¥1.44输入/输出
193
Ogpt-4o-2024-05-13
gpt-4o-2024-05-13Openai
46.5
43.8K
128K
¥36 / ¥108输入/输出
194
TEhunyuan-large-2025-02-10
hunyuan-large-2025-02-10Tencent
46.2
1.3K
-
-
195
IB
granite-4.1-8b
granite-4.1-8bIbm
46.0
1.2K
131K
¥0.36 / ¥0.72输入/输出
196
AImolmo-2-8b
molmo-2-8bAllenai
45.7
217
-
-
197
Aqwen2.5-plus-1127
qwen2.5-plus-1127Alibaba
45.4
4.2K
-
-
198
AIolmo-3-32b-think
olmo-3-32b-thinkAllenai
45.1
1.5K
128K
¥2.16 / ¥3.24输入/输出
199
UNathene-v2-chat
-
44.8
10.2K
-
-
200
Xgrok-2-2024-08-13
grok-2-2024-08-13Xai
44.6
25.7K
1M
¥9 / ¥18输入/输出
201
Aclaude-3-5-sonnet-20240620
claude-3-5-sonnet-20240620Anthropic
44.3
32.1K
200K
¥21.6 / ¥108输入/输出
202
Mllama-4-maverick-17b-128e-instruct
llama-4-maverick-17b-128e-instructMeta
44.0
10.5K
1M
¥1.8 / ¥6.26输入/输出
203
Ogpt-4o-2024-08-06
gpt-4o-2024-08-06Openai
43.7
18.3K
128K
¥18 / ¥72输入/输出
204
Ogpt-4.1-nano-2025-04-14
gpt-4.1-nano-2025-04-14Openai
43.5
2K
1.05M
¥14.4 / ¥57.6输入/输出
205
MAmistral-small-3.1-24b-instruct-2503
mistral-small-3.1-24b-instruct-2503Mistral
43.2
8K
262K
¥2.88 / ¥14.4输入/输出
206
Zglm-4-plus
glm-4-plusZai
42.9
10.7K
128K
¥54 / ¥54输入/输出
207
Aqwen-max-0919
qwen-max-0919Alibaba
42.6
6.9K
131K
¥2.48 / ¥9.91输入/输出
208
Mllama-3.1-405b-instruct-bf16
llama-3.1-405b-instruct-bf16Meta
42.3
16.2K
128K
¥0 / ¥0输入/输出
209
Mllama-3.1-405b-instruct-fp8
llama-3.1-405b-instruct-fp8Meta
42.1
23.6K
128K
¥0 / ¥0输入/输出
210
Ogpt-4o-mini-2024-07-18
gpt-4o-mini-2024-07-18Openai
41.8
26.7K
128K
¥1.08 / ¥4.32输入/输出
211
Ggemini-1.5-flash-002
gemini-1.5-flash-002Google
41.5
14.6K
2M
¥0.54 / ¥2.2输入/输出
212
MAmagistral-medium-2506
magistral-medium-2506Mistral
41.2
3.1K
128K
¥14.4 / ¥36输入/输出
213
Ggemma-3n-e4b-it
gemma-3n-e4b-itGoogle
40.9
5K
128K
¥0 / ¥0输入/输出
214
Aqwen2.5-72b-instruct
qwen2.5-72b-instructAlibaba
40.7
16.4K
131K
¥4.13 / ¥12.4输入/输出
215
Ggemini-1.5-pro-001
gemini-1.5-pro-001Google
40.4
29.8K
-
-
216
Ggemini-advanced-0514
gemini-advanced-0514Google
40.1
18.5K
-
-
217
NVllama-3.1-nemotron-70b-instruct
llama-3.1-nemotron-70b-instructNvidia
39.8
3K
128K
¥0 / ¥0输入/输出
218
Mllama-4-scout-17b-16e-instruct
llama-4-scout-17b-16e-instructMeta
39.6
7.5K
128K
¥1.44 / ¥5.62输入/输出
219
Ogpt-4-turbo-2024-04-09
gpt-4-turbo-2024-04-09Openai
39.3
36.3K
128K
¥72 / ¥216输入/输出
220
TEhunyuan-large-vision
hunyuan-large-visionTencent
39.0
1.2K
-
-
221
Ddeepseek-v2.5
deepseek-v2.5Deepseek
38.7
10.2K
1M
¥1.01 / ¥2.02输入/输出
222
MAmistral-large-2411
mistral-large-2411Mistral
38.4
11K
128K
¥14.4 / ¥43.2输入/输出
223
Aclaude-3-opus-20240229
claude-3-opus-20240229Anthropic
38.2
72K
200K
¥108 / ¥540输入/输出
224
MAmistral-large-2407
mistral-large-2407Mistral
37.9
18.3K
131K
¥14.4 / ¥43.2输入/输出
225
TEhunyuan-standard-2025-02-10
hunyuan-standard-2025-02-10Tencent
37.6
1.3K
-
-
226
Xgrok-2-mini-2024-08-13
grok-2-mini-2024-08-13Xai
37.3
21.1K
1M
¥9 / ¥18输入/输出
227
AIolmo-3.1-32b-think
olmo-3.1-32b-thinkAllenai
37.0
2.2K
200K
¥14.4 / ¥57.6输入/输出
228
Mllama-3.3-70b-instruct
llama-3.3-70b-instructMeta
36.8
18.8K
128K
¥0 / ¥0输入/输出
229
Ogpt-4-1106-preview
gpt-4-1106-previewOpenai
36.5
34.4K
8.19K
¥216 / ¥432输入/输出
230
Aclaude-3-5-haiku-20241022
claude-3-5-haiku-20241022Anthropic
36.2
22K
200K
¥5.76 / ¥28.8输入/输出
231
Ggemma-3-4b-it
gemma-3-4b-itGoogle
35.9
1.2K
128K
¥1.44 / ¥1.44输入/输出
232
Ogpt-oss-20b
gpt-oss-20bOpenai
35.7
2.6K
131K
¥0.32 / ¥1.3输入/输出
233
IAmercury
mercuryInception Ai
35.4
569
128K
¥1.8 / ¥5.4输入/输出
234
Aamazon-nova-pro-v1.0
amazon-nova-pro-v1.0Amazon
35.1
9.5K
300K
¥5.76 / ¥23输入/输出
235
Ogpt-4-0125-preview
gpt-4-0125-previewOpenai
34.8
33.3K
8.19K
¥216 / ¥432输入/输出
236
AIllama-3.1-tulu-3-70b
llama-3.1-tulu-3-70bAllenai
34.5
1.2K
-
-
237
Mllama-3.1-70b-instruct
llama-3.1-70b-instructMeta
34.3
21.9K
131K
¥2.88 / ¥2.88输入/输出
238
UNathene-70b-0725
-
34.0
7.5K
-
-
239
Aqwen2.5-coder-32b-instruct
qwen2.5-coder-32b-instructAlibaba
33.7
2.2K
131K
¥2.07 / ¥6.2输入/输出
240
IBibm-granite-h-small
ibm-granite-h-smallIbm
33.4
1.6K
-
-
241
MAmistral-small-24b-instruct-2501
mistral-small-24b-instruct-2501Mistral
33.1
5.5K
262K
¥2.88 / ¥14.4输入/输出
242
UNjamba-1.5-large
-
32.9
3.3K
256K
¥0 / ¥0输入/输出
243
Ggemini-1.5-flash-001
gemini-1.5-flash-001Google
32.6
23.7K
2M
¥0.54 / ¥2.2输入/输出
244
UNreka-core-20240904
-
32.3
3.1K
-
-
245
Ggemma-2-27b-it
gemma-2-27b-itGoogle
32.0
29.5K
8.19K
¥0.58 / ¥0.58输入/输出
246
Aamazon-nova-lite-v1.0
amazon-nova-lite-v1.0Amazon
31.8
7.8K
300K
¥0.43 / ¥1.73输入/输出
247
NVnemotron-4-340b-instruct
nemotron-4-340b-instructNvidia
31.5
7.4K
-
-
248
Zglm-4-0520
glm-4-0520Zai
31.2
3.8K
128K
¥108 / ¥108输入/输出
249
TEhunyuan-standard-256k
hunyuan-standard-256kTencent
30.9
1.1K
-
-
250
M
phi-4
phi-4Microsoft
30.6
9.2K
128K
¥0.9 / ¥3.6输入/输出
251
Ogpt-4-0314
gpt-4-0314Openai
30.4
18.1K
8.19K
¥216 / ¥432输入/输出
252
NVllama-3.1-nemotron-51b-instruct
llama-3.1-nemotron-51b-instructNvidia
30.1
1.5K
128K
¥0 / ¥0输入/输出
253
Aclaude-3-sonnet-20240229
claude-3-sonnet-20240229Anthropic
29.8
38.8K
200K
¥21.6 / ¥108输入/输出
254
Ggemini-1.5-flash-8b-001
gemini-1.5-flash-8b-001Google
29.5
14.9K
2M
¥0.54 / ¥2.2输入/输出
255
COcommand-r-plus-08-2024
command-r-plus-08-2024Cohere
29.2
4K
128K
¥18 / ¥72输入/输出
256
COc4ai-aya-expanse-32b
c4ai-aya-expanse-32bCohere
29.0
11.3K
-
-
257
Mllama-3-70b-instruct
llama-3-70b-instructMeta
28.7
56.6K
8.19K
¥3.67 / ¥5.33输入/输出
258
UNgemma-2-9b-it-simpo
-
28.4
3.7K
8.19K
¥1.44 / ¥1.44输入/输出
259
Ogpt-4-0613
gpt-4-0613Openai
28.1
29.7K
8.19K
¥216 / ¥432输入/输出
260
AIolmo-2-0325-32b-instruct
olmo-2-0325-32b-instructAllenai
27.9
1.1K
-
-
261
UNreka-flash-20240904
-
27.6
3.2K
65.5K
¥0.72 / ¥1.44输入/输出
262
Aqwen2-72b-instruct
qwen2-72b-instructAlibaba
27.3
14.2K
131K
¥4.13 / ¥12.4输入/输出
263
Ddeepseek-coder-v2
deepseek-coder-v2Deepseek
27.0
5.6K
1M
¥1.01 / ¥2.02输入/输出
264
COcommand-r-plus
command-r-plusCohere
26.7
28.1K
128K
¥18 / ¥72输入/输出
265
Ggemma-2-9b-it
gemma-2-9b-itGoogle
26.5
21.4K
8.19K
¥1.44 / ¥1.44输入/输出
266
AIllama-3.1-tulu-3-8b
llama-3.1-tulu-3-8bAllenai
26.2
1.2K
-
-
267
Aamazon-nova-micro-v1.0
amazon-nova-micro-v1.0Amazon
25.9
7.7K
128K
¥0.25 / ¥1.01输入/输出
268
Aclaude-3-haiku-20240307
claude-3-haiku-20240307Anthropic
25.6
43K
200K
¥1.8 / ¥9输入/输出
269
MAmistral-large-2402
mistral-large-2402Mistral
25.3
21.5K
262K
¥2.88 / ¥14.4输入/输出
270
COcommand-r-08-2024
command-r-08-2024Cohere
25.1
4.2K
128K
¥18 / ¥72输入/输出
271
MAministral-8b-2410
ministral-8b-2410Mistral
24.8
1.9K
128K
¥0.72 / ¥0.72输入/输出
272
Mllama-3.1-8b-instruct
llama-3.1-8b-instructMeta
24.5
19.8K
131K
¥0.79 / ¥0.79输入/输出
273
Aqwen1.5-110b-chat
qwen1.5-110b-chatAlibaba
24.2
9.5K
-
-
274
Aqwq-32b-preview
qwq-32b-previewAlibaba
24.0
1.3K
131K
¥2.07 / ¥6.2输入/输出
275
COc4ai-aya-expanse-8b
c4ai-aya-expanse-8bCohere
23.7
4K
-
-
276
MAmistral-medium
mistral-mediumMistral
23.4
11.5K
262K
¥2.88 / ¥14.4输入/输出
277
UNjamba-1.5-mini
-
23.1
3.3K
256K
¥0 / ¥0输入/输出
278
MAmixtral-8x22b-instruct-v0.1
mixtral-8x22b-instruct-v0.1Mistral
22.8
18.5K
64K
¥14.4 / ¥43.2输入/输出
279
Aqwen1.5-72b-chat
qwen1.5-72b-chatAlibaba
22.6
13.8K
-
-
280
UNyi-1.5-34b-chat
-
22.3
9K
-
-
281
UNinternlm2_5-20b-chat
-
22.0
4.1K
-
-
282
IBgranite-3.1-8b-instruct
granite-3.1-8b-instructIbm
21.7
1.3K
-
-
283
UNreka-flash-21b-20240226-online
-
21.4
5.6K
-
-
284
Mllama-3-8b-instruct
llama-3-8b-instructMeta
21.2
37.7K
8.19K
¥0.29 / ¥0.29输入/输出
285
COcommand-r
command-rCohere
20.9
19.1K
128K
¥18 / ¥72输入/输出
286
UNreka-flash-21b-20240226
-
20.6
9K
-
-
287
Ogpt-3.5-turbo-0125
gpt-3.5-turbo-0125Openai
20.3
23.5K
16.4K
¥3.6 / ¥10.8输入/输出
288
UNzephyr-orpo-141b-A35b-v0.1
-
20.1
1.6K
200K
¥108 / ¥432输入/输出
289
Ggemma-2-2b-it
gemma-2-2b-itGoogle
19.8
18.2K
128K
¥0 / ¥0输入/输出
290
IBgranite-3.1-2b-instruct
granite-3.1-2b-instructIbm
19.5
1.3K
-
-
291
Aqwen1.5-32b-chat
qwen1.5-32b-chatAlibaba
19.2
7.7K
-
-
292
Ggemini-pro-dev-api
gemini-pro-dev-apiGoogle
18.9
5.9K
1.05M
¥14.4 / ¥86.4输入/输出
293
Mphi-3-medium-4k-instruct
phi-3-medium-4k-instructMicrosoft
18.7
9.4K
4.1K
¥1.22 / ¥4.9输入/输出
294
UNdbrx-instruct-preview
-
18.4
11.3K
-
-
295
UNtulu-2-dpo-70b
-
18.1
2K
-
-
296
Ggemini-pro
gemini-proGoogle
17.8
1.9K
1.05M
¥14.4 / ¥86.4输入/输出
297
MAmixtral-8x7b-instruct-v0.1
mixtral-8x7b-instruct-v0.1Mistral
17.5
25K
32K
¥5.04 / ¥5.04输入/输出
298
Aqwen1.5-14b-chat
qwen1.5-14b-chatAlibaba
17.3
6.2K
-
-
299
UNstarling-lm-7b-beta
-
17.0
5.8K
200K
¥5.4 / ¥18.7输入/输出
300
Mwizardlm-70b
wizardlm-70bMicrosoft
16.7
2.7K
-
-
301
Ogpt-3.5-turbo-1106
gpt-3.5-turbo-1106Openai
16.4
5.2K
16.4K
¥7.2 / ¥14.4输入/输出
302
UNyi-34b-chat
-
16.2
5.1K
-
-
303
Mllama-3.2-3b-instruct
llama-3.2-3b-instructMeta
15.9
3.2K
131K
¥0.22 / ¥0.35输入/输出
304
IBgranite-3.0-8b-instruct
granite-3.0-8b-instructIbm
15.6
2.6K
-
-
305
Mphi-3-small-8k-instruct
phi-3-small-8k-instructMicrosoft
15.3
6.6K
8.19K
¥1.08 / ¥4.32输入/输出
306
Ddeepseek-llm-67b-chat
deepseek-llm-67b-chatDeepseek
15.0
1.5K
1M
¥1.01 / ¥2.02输入/输出
307
UNopenchat-3.5-0106
-
14.8
4.4K
-
-
308
Mllama-2-70b-chat
llama-2-70b-chatMeta
14.5
12.6K
-
-
309
UNopenhermes-2.5-mistral-7b
-
14.2
1.6K
1M
¥36 / ¥180输入/输出
310
UNopenchat-3.5
-
13.9
2.4K
-
-
311
UNstarling-lm-7b-alpha
-
13.6
3.3K
200K
¥5.4 / ¥18.7输入/输出
312
UNsnowflake-arctic-instruct
-
13.4
11.7K
-
-
313
UNvicuna-33b
-
13.1
7K
-
-
314
NVllama2-70b-steerlm-chat
llama2-70b-steerlm-chatNvidia
12.8
1.1K
-
-
315
MAmistral-7b-instruct-v0.2
mistral-7b-instruct-v0.2Mistral
12.5
6.7K
262K
¥2.88 / ¥14.4输入/输出
316
Aqwen1.5-7b-chat
qwen1.5-7b-chatAlibaba
12.3
1.7K
-
-
317
Mphi-3-mini-4k-instruct-june-2024
phi-3-mini-4k-instruct-june-2024Microsoft
12.0
4.4K
4.1K
¥0.94 / ¥3.74输入/输出
318
Ggemma-1.1-7b-it
gemma-1.1-7b-itGoogle
11.7
8.9K
-
-
319
UNnous-hermes-2-mixtral-8x7b-dpo
-
11.4
1.4K
1M
¥36 / ¥180输入/输出
320
IBgranite-3.0-2b-instruct
granite-3.0-2b-instructIbm
11.1
2.7K
-
-
321
UNmpt-30b-chat
-
10.9
718
-
-
322
UNdolphin-2.2.1-mistral-7b
-
10.6
497
262K
¥2.88 / ¥14.4输入/输出
323
Mphi-3-mini-4k-instruct
phi-3-mini-4k-instructMicrosoft
10.3
7.6K
4.1K
¥0.94 / ¥3.74输入/输出
324
Mwizardlm-13b
wizardlm-13bMicrosoft
10.0
2K
-
-
325
UNfalcon-180b-chat
-
9.7
389
-
-
326
UNsolar-10.7b-instruct-v1.0
-
9.5
1.2K
128K
¥0 / ¥0输入/输出
327
Mllama-2-13b-chat
llama-2-13b-chatMeta
9.2
6.1K
-
-
328
UNvicuna-13b
-
8.9
5.7K
-
-
329
UNzephyr-7b-alpha
-
8.6
534
-
-
330
UNzephyr-7b-beta
-
8.4
3.1K
-
-
331
Aqwen-14b-chat
qwen-14b-chatAlibaba
8.1
1.5K
32.8K
¥1.04 / ¥3.1输入/输出
332
Mllama-3.2-1b-instruct
llama-3.2-1b-instructMeta
7.8
3.2K
16.4K
¥0.07 / ¥0.08输入/输出
333
UNsmollm2-1.7b-instruct
-
7.5
859
-
-
334
Mcodellama-34b-instruct
codellama-34b-instructMeta
7.2
2.3K
-
-
335
Mcodellama-70b-instruct
codellama-70b-instructMeta
7.0
358
-
-
336
Mphi-3-mini-128k-instruct
phi-3-mini-128k-instructMicrosoft
6.7
7.4K
128K
¥0.94 / ¥3.74输入/输出
337
Ggemma-7b-it
gemma-7b-itGoogle
6.4
2.8K
-
-
338
UNstripedhyena-nous-7b
-
6.1
1.7K
-
-
339
Gpalm-2
palm-2Google
5.8
2.5K
-
-
340
Mllama-2-7b-chat
llama-2-7b-chatMeta
5.6
4.5K
128K
¥4.03 / ¥48输入/输出
341
MAmistral-7b-instruct
mistral-7b-instructMistral
5.3
2.8K
262K
¥2.88 / ¥14.4输入/输出
342
UNvicuna-7b
-
5.0
2K
-
-
343
Ggemma-1.1-2b-it
gemma-1.1-2b-itGoogle
4.7
3.9K
-
-
344
UNguanaco-33b
-
4.5
777
200K
¥14.4 / ¥57.6输入/输出
345
Aqwen1.5-4b-chat
qwen1.5-4b-chatAlibaba
4.2
2.6K
-
-
346
AIolmo-7b-instruct
olmo-7b-instructAllenai
3.9
1.9K
-
-
347
Ggemma-2b-it
gemma-2b-itGoogle
3.6
1.5K
-
-
348
UNchatglm3-6b
-
3.3
1.3K
200K
¥5.4 / ¥18.7输入/输出
349
UNgpt4all-13b-snoozy
-
3.1
483
1M
¥36 / ¥216输入/输出
350
UNkoala-13b
-
2.8
1.9K
-
-
351
UNmpt-7b-chat
-
2.5
1.1K
-
-
352
UNchatglm2-6b
-
2.2
762
200K
¥5.4 / ¥18.7输入/输出
353
UNchatglm-6b
-
1.9
1.3K
200K
¥5.4 / ¥18.7输入/输出
354
UNalpaca-13b
-
1.7
1.5K
-
-
355
UNoasst-pythia-12b
-
1.4
1.7K
-
-
356
UNRWKV-4-Raven-14B
-
1.1
1.4K
-
-
357
UNfastchat-t5-3b
-
0.8
1.1K
-
-
358
UNstablelm-tuned-alpha-7b
-
0.6
814
-
-
359
UNdolly-v2-12b
-
0.3
899
-
-
360
Mllama-13b
llama-13bMeta
0.0
584
-
-
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 10K。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
指令遵循常见问题
指令遵循排行榜看什么指标？
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。
指令遵循模型应该怎么选？
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。