1
A
claude-opus-4-6
claude-opus-4-6Anthropic
100.0
6.4K
1M
¥36 / ¥180输入/输出
对话 · 文本 · 多轮对话排行榜
基于公开偏好评测数据展示 文本 / 多轮对话 榜单，每个榜单独立排序。
多轮对话模型怎么选？
多轮对话排行榜用于回答“多轮对话哪个 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 6.4K。 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-4-7-thinkingclaude-opus-4-6-thinkingclaude-opus-4-7gemini-3.5-flash
2
Aclaude-opus-4-7-thinking
claude-opus-4-7-thinkingAnthropic
99.7
3.4K
1M
¥36 / ¥180输入/输出
3
Aclaude-opus-4-6-thinking
claude-opus-4-6-thinkingAnthropic
99.4
5.8K
1M
¥36 / ¥180输入/输出
4
Aclaude-opus-4-7
claude-opus-4-7Anthropic
99.2
3.6K
1M
¥36 / ¥180输入/输出
5
G
gemini-3.5-flash
gemini-3.5-flashGoogle
98.9
1.6K
1.05M
¥10.8 / ¥64.8输入/输出
6
Ggemini-3.1-pro-preview
gemini-3.1-pro-previewGoogle
98.6
7.5K
1.05M
¥14.4 / ¥86.4输入/输出
7
O
gpt-5.4-high
gpt-5.4-highOpenai
98.3
5.2K
1.05M
¥18 / ¥108输入/输出
8
Ggemini-3-pro
gemini-3-proGoogle
98.0
6.8K
1.05M
¥14.4 / ¥86.4输入/输出
9
A
qwen3.7-max-preview
qwen3.7-max-previewAlibaba
97.8
660
1M
¥18 / ¥54输入/输出
10
M
muse-spark
muse-sparkMeta
97.5
1.9K
-
-
11
Aqwen3.5-max-preview
qwen3.5-max-previewAlibaba
97.2
3.4K
-
-
12
Z
glm-5.1
glm-5.1Zai
96.9
2.3K
200K
¥0 / ¥0输入/输出
13
MI
mimo-v2.5-pro
mimo-v2.5-proXiaomi
96.6
2.7K
1.05M
¥7.2 / ¥21.6输入/输出
14
B
ernie-5.1
ernie-5.1Baidu
96.4
2.5K
119K
¥5.4 / ¥21.6输入/输出
15
Ggemini-3-flash
gemini-3-flashGoogle
96.1
5.3K
1.05M
¥3.6 / ¥21.6输入/输出
16
Ogpt-5.5-high
gpt-5.5-highOpenai
95.8
2.8K
1.05M
¥36 / ¥216输入/输出
17
Ogpt-5.5
gpt-5.5Openai
95.5
2.9K
1.05M
¥36 / ¥216输入/输出
18
Ogpt-5.4
gpt-5.4Openai
95.2
5.6K
1.05M
¥18 / ¥108输入/输出
19
Aclaude-opus-4-5-20251101
claude-opus-4-5-20251101Anthropic
95.0
11.7K
200K
¥36 / ¥180输入/输出
20
Aclaude-sonnet-4-5-20250929
claude-sonnet-4-5-20250929Anthropic
94.7
13.2K
200K
¥21.6 / ¥108输入/输出
21
D
deepseek-v4-pro
deepseek-v4-proDeepseek
94.4
3.1K
1M
¥3.13 / ¥6.26输入/输出
22
Aclaude-sonnet-4-6
claude-sonnet-4-6Anthropic
94.1
5K
1M
¥21.6 / ¥108输入/输出
23
Aclaude-opus-4-5-20251101-thinking-32k
claude-opus-4-5-20251101-thinking-32kAnthropic
93.8
6.5K
200K
¥108 / ¥540输入/输出
24
Ggemini-3-flash (thinking-minimal)
gemini-3-flash (thinking-minimal)Google
93.6
9.5K
1.05M
¥3.6 / ¥21.6输入/输出
25
Ogpt-5.2-chat-latest-20260210
gpt-5.2-chat-latest-20260210Openai
93.3
6K
400K
¥12.6 / ¥101输入/输出
26
X
grok-4.20-beta-0309-reasoning
grok-4.20-beta-0309-reasoningXai
93.0
5.3K
2M
¥14.4 / ¥43.2输入/输出
27
MImimo-v2-pro
mimo-v2-proXiaomi
92.7
4K
1.05M
¥7.2 / ¥21.6输入/输出
28
Xgrok-4.20-multi-agent-beta-0309
grok-4.20-multi-agent-beta-0309Xai
92.4
4.8K
2M
¥14.4 / ¥43.2输入/输出
29
Ochatgpt-4o-latest-20250326
chatgpt-4o-latest-20250326Openai
92.2
14.6K
128K
¥18 / ¥72输入/输出
30
Aqwen3.6-max-preview
qwen3.6-max-previewAlibaba
91.9
742
246K
¥9.5 / ¥56.9输入/输出
31
Xgrok-4.20-beta1
grok-4.20-beta1Xai
91.6
3.9K
2M
¥14.4 / ¥43.2输入/输出
32
Zglm-5
glm-5Zai
91.3
3.5K
205K
¥7.2 / ¥23输入/输出
33
Ggemini-2.5-pro
gemini-2.5-proGoogle
91.0
20.8K
1.05M
¥9 / ¥72输入/输出
34
Ggemma-4-31b
gemma-4-31bGoogle
90.8
1.1K
262K
¥3.24 / ¥7.2输入/输出
35
Aclaude-sonnet-4-5-20250929-thinking-32k
claude-sonnet-4-5-20250929-thinking-32kAnthropic
90.5
13.2K
200K
¥21.6 / ¥108输入/输出
36
Ddeepseek-v4-pro-thinking
deepseek-v4-pro-thinkingDeepseek
90.2
2.8K
1M
¥3.13 / ¥6.26输入/输出
37
Aqwen3-max-preview
qwen3-max-previewAlibaba
89.9
4.7K
262K
¥6.2 / ¥24.8输入/输出
38
Ogpt-5.1-high
gpt-5.1-highOpenai
89.6
7.1K
400K
¥9 / ¥72输入/输出
39
Zglm-4.7
glm-4.7Zai
89.4
1.9K
205K
¥0 / ¥0输入/输出
40
M
kimi-k2.6
kimi-k2.6Moonshot
89.1
2.7K
262K
¥6.84 / ¥28.8输入/输出
41
MImimo-v2.5
mimo-v2.5Xiaomi
88.8
2.8K
1.05M
¥2.88 / ¥14.4输入/输出
42
Aclaude-opus-4-1-20250805-thinking-16k
claude-opus-4-1-20250805-thinking-16kAnthropic
88.5
8.6K
200K
¥108 / ¥540输入/输出
43
Aqwen3.5-397b-a17b
qwen3.5-397b-a17bAlibaba
88.2
5.4K
262K
¥3.1 / ¥18.6输入/输出
44
A
amazon-nova-experimental-chat-26-02-10
amazon-nova-experimental-chat-26-02-10Amazon
88.0
599
-
-
45
Mkimi-k2.5-thinking
kimi-k2.5-thinkingMoonshot
87.7
6.4K
262K
¥4.32 / ¥21.6输入/输出
46
Ogpt-4.5-preview-2025-02-27
gpt-4.5-preview-2025-02-27Openai
87.4
2.1K
8.19K
¥216 / ¥432输入/输出
47
Ddeepseek-v4-flash
deepseek-v4-flashDeepseek
87.1
3K
1M
¥1.01 / ¥2.02输入/输出
48
Aclaude-opus-4-1-20250805
claude-opus-4-1-20250805Anthropic
86.8
13.3K
200K
¥108 / ¥540输入/输出
49
B
dola-seed-2.0-pro
dola-seed-2.0-proBytedance
86.6
6.6K
-
-
50
Ggemma-4-26b-a4b
gemma-4-26b-a4bGoogle
86.3
1.1K
262K
¥0.94 / ¥2.88输入/输出
51
Xgrok-4.1
grok-4.1Xai
86.0
11.9K
200K
¥14.4 / ¥72输入/输出
52
Aqwen3-max-2025-09-23
qwen3-max-2025-09-23Alibaba
85.7
1.7K
258K
¥6.19 / ¥24.7输入/输出
53
Ogpt-5.4-mini-high
gpt-5.4-mini-highOpenai
85.4
5K
400K
¥5.4 / ¥32.4输入/输出
54
Ogpt-5.5-instant
gpt-5.5-instantOpenai
85.2
4.6K
400K
¥9 / ¥72输入/输出
55
Xgrok-4.1-thinking
grok-4.1-thinkingXai
84.9
11.7K
200K
¥14.4 / ¥72输入/输出
56
Aqwen3.6-plus
qwen3.6-plusAlibaba
84.6
3.2K
1M
¥3.6 / ¥21.6输入/输出
57
Ogpt-5.1
gpt-5.1Openai
84.3
8K
400K
¥9 / ¥72输入/输出
58
Bernie-5.0-0110
ernie-5.0-0110Baidu
84.0
5.5K
128K
¥7.92 / ¥14.4输入/输出
59
Aqwen3-235b-a22b-instruct-2507
qwen3-235b-a22b-instruct-2507Alibaba
83.8
16.6K
128K
¥2.09 / ¥8.23输入/输出
60
Ddeepseek-v4-flash-thinking
deepseek-v4-flash-thinkingDeepseek
83.5
2.9K
1M
¥1.01 / ¥2.02输入/输出
61
MA
mistral-large-3
mistral-large-3Mistral
83.2
7.3K
262K
¥3.6 / ¥10.8输入/输出
62
Aqwen3-vl-235b-a22b-instruct
qwen3-vl-235b-a22b-instructAlibaba
82.9
2K
128K
¥2.16 / ¥8.64输入/输出
63
Xgrok-4.3
grok-4.3Xai
82.6
3K
1M
¥9 / ¥18输入/输出
64
Mkimi-k2.5-instant
kimi-k2.5-instantMoonshot
82.4
1.5K
262K
¥4.32 / ¥21.6输入/输出
65
Zglm-4.6
glm-4.6Zai
82.1
5.7K
205K
¥4.32 / ¥15.8输入/输出
66
Ddeepseek-v3.2
deepseek-v3.2Deepseek
81.8
8K
128K
¥2.09 / ¥3.1输入/输出
67
Ogpt-5-chat
gpt-5-chatOpenai
81.5
5.8K
400K
¥9 / ¥72输入/输出
68
Ddeepseek-v3.2-exp
deepseek-v3.2-expDeepseek
81.2
2K
128K
¥0 / ¥0输入/输出
69
Xgrok-3-preview-02-24
grok-3-preview-02-24Xai
81.0
4.8K
1M
¥9 / ¥18输入/输出
70
Bernie-5.0-preview-1022
ernie-5.0-preview-1022Baidu
80.7
703
128K
¥7.92 / ¥14.4输入/输出
71
Ddeepseek-v3.2-thinking
deepseek-v3.2-thinkingDeepseek
80.4
6.7K
128K
¥2.09 / ¥3.1输入/输出
72
MAmistral-medium-2508
mistral-medium-2508Mistral
80.1
15.8K
262K
¥2.88 / ¥14.4输入/输出
73
TE
hunyuan-vision-1.5-thinking
hunyuan-vision-1.5-thinkingTencent
79.8
438
-
-
74
Ogpt-5.2-high
gpt-5.2-highOpenai
79.6
8.5K
400K
¥12.6 / ¥101输入/输出
75
Ggemini-3.1-flash-lite-preview
gemini-3.1-flash-lite-previewGoogle
79.3
6.3K
1.05M
¥1.8 / ¥10.8输入/输出
76
Ogpt-5.2
gpt-5.2Openai
79.0
8.8K
400K
¥12.6 / ¥101输入/输出
77
Aqwen3-next-80b-a3b-instruct
qwen3-next-80b-a3b-instructAlibaba
78.7
4.1K
131K
¥1.04 / ¥4.13输入/输出
78
Zglm-4.5
glm-4.5Zai
78.4
3.9K
131K
¥4.32 / ¥15.8输入/输出
79
Xgrok-4-fast-chat
grok-4-fast-chatXai
78.2
1.2K
2M
¥1.44 / ¥3.6输入/输出
80
Xgrok-4-0709
grok-4-0709Xai
77.9
6.6K
256K
¥21.6 / ¥108输入/输出
81
Ddeepseek-v3.1-terminus-thinking
deepseek-v3.1-terminus-thinkingDeepseek
77.6
604
128K
¥1.8 / ¥5.04输入/输出
82
Ddeepseek-v3.2-exp-thinking
deepseek-v3.2-exp-thinkingDeepseek
77.3
1.4K
128K
¥0 / ¥0输入/输出
83
TEhunyuan-hy3-preview
hunyuan-hy3-previewTencent
77.0
990
256K
¥0 / ¥0输入/输出
84
Bernie-5.0-preview-1203
ernie-5.0-preview-1203Baidu
76.8
1.5K
128K
¥7.92 / ¥14.4输入/输出
85
M
longcat-flash-chat-2602-exp
longcat-flash-chat-2602-expMeituan
76.5
4.2K
128K
¥1.08 / ¥10.8输入/输出
86
Aqwen3.5-122b-a10b
qwen3.5-122b-a10bAlibaba
76.2
4.5K
262K
¥2.88 / ¥23输入/输出
87
Mkimi-k2-thinking-turbo
kimi-k2-thinking-turboMoonshot
75.9
10.4K
262K
¥17.3 / ¥72输入/输出
88
Aqwen3.5-27b
qwen3.5-27bAlibaba
75.6
4.3K
262K
¥2.16 / ¥17.3输入/输出
89
Ogpt-5.3-chat-latest
gpt-5.3-chat-latestOpenai
75.4
5.7K
128K
¥12.6 / ¥101输入/输出
90
M
minimax-m2.7
minimax-m2.7Minimax
75.1
4.1K
205K
¥0 / ¥0输入/输出
91
Aclaude-haiku-4-5-20251001
claude-haiku-4-5-20251001Anthropic
74.8
13.7K
200K
¥7.2 / ¥36输入/输出
92
Ggemini-2.5-flash
gemini-2.5-flashGoogle
74.5
21.2K
1.05M
¥2.16 / ¥18输入/输出
93
Ddeepseek-v3.1-thinking
deepseek-v3.1-thinkingDeepseek
74.2
1.9K
128K
¥1.44 / ¥5.04输入/输出
94
Aqwen3-235b-a22b-thinking-2507
qwen3-235b-a22b-thinking-2507Alibaba
73.9
1.4K
131K
¥2.07 / ¥8.26输入/输出
95
Aamazon-nova-experimental-chat-12-10
amazon-nova-experimental-chat-12-10Amazon
73.7
629
-
-
96
ST
step-3.5-flash
step-3.5-flashStepfun
73.4
6.1K
256K
¥0.69 / ¥2.07输入/输出
97
Ddeepseek-r1-0528
deepseek-r1-0528Deepseek
73.1
3K
164K
¥3.6 / ¥15.5输入/输出
98
Xgrok-4-fast-reasoning
grok-4-fast-reasoningXai
72.8
3.1K
2M
¥1.44 / ¥3.6输入/输出
99
Oo3-2025-04-16
o3-2025-04-16Openai
72.5
9.9K
200K
¥14.4 / ¥57.6输入/输出
100
MImimo-v2-flash (non-thinking)
mimo-v2-flash (non-thinking)Xiaomi
72.3
7.8K
262K
¥0.72 / ¥2.16输入/输出
101
Mlongcat-flash-chat
longcat-flash-chatMeituan
72.0
2K
128K
¥1.08 / ¥10.8输入/输出
102
Ddeepseek-v3.1
deepseek-v3.1Deepseek
71.7
2.5K
128K
¥1.44 / ¥5.04输入/输出
103
Ogpt-5-high
gpt-5-highOpenai
71.4
5K
400K
¥9 / ¥72输入/输出
104
Aqwen3-235b-a22b-no-thinking
qwen3-235b-a22b-no-thinkingAlibaba
71.1
6.8K
131K
¥2.07 / ¥8.26输入/输出
105
Ogpt-4.1-2025-04-14
gpt-4.1-2025-04-14Openai
70.9
9K
1.05M
¥14.4 / ¥57.6输入/输出
106
MImimo-v2-omni
mimo-v2-omniXiaomi
70.6
482
262K
¥2.88 / ¥14.4输入/输出
107
Ggemini-2.5-flash-preview-09-2025
gemini-2.5-flash-preview-09-2025Google
70.3
5.8K
1M
¥2.16 / ¥18输入/输出
108
Aclaude-opus-4-20250514-thinking-16k
claude-opus-4-20250514-thinking-16kAnthropic
70.0
6.3K
200K
¥108 / ¥540输入/输出
109
Mminimax-m2.1-preview
minimax-m2.1-previewMinimax
69.7
2.9K
205K
¥0 / ¥0输入/输出
110
TEhunyuan-t1-20250711
hunyuan-t1-20250711Tencent
69.5
687
131K
¥0 / ¥0输入/输出
111
Xgrok-4-1-fast-reasoning
grok-4-1-fast-reasoningXai
69.2
9.8K
2M
¥1.44 / ¥3.6输入/输出
112
Ddeepseek-r1
deepseek-r1Deepseek
68.9
2.4K
164K
¥5.04 / ¥18输入/输出
113
Aqwen3.5-35b-a3b
qwen3.5-35b-a3bAlibaba
68.6
4.8K
262K
¥1.8 / ¥14.4输入/输出
114
Aqwen3-vl-235b-a22b-thinking
qwen3-vl-235b-a22b-thinkingAlibaba
68.3
1.3K
131K
¥2.06 / ¥8.26输入/输出
115
Aqwen3.5-flash
qwen3.5-flashAlibaba
68.1
5.2K
1M
¥1.24 / ¥12.4输入/输出
116
Ddeepseek-v3.1-terminus
deepseek-v3.1-terminusDeepseek
67.8
691
128K
¥1.8 / ¥5.04输入/输出
117
Ddeepseek-v3-0324
deepseek-v3-0324Deepseek
67.5
7.9K
75K
¥1.44 / ¥5.76输入/输出
118
Aclaude-opus-4-20250514
claude-opus-4-20250514Anthropic
67.2
7.7K
200K
¥108 / ¥540输入/输出
119
TEhunyuan-turbos-20250416
hunyuan-turbos-20250416Tencent
66.9
1.7K
131K
¥0 / ¥0输入/输出
120
MAmistral-medium-2505
mistral-medium-2505Mistral
66.7
5.8K
262K
¥2.88 / ¥14.4输入/输出
121
Ogpt-5.4-nano-high
gpt-5.4-nano-highOpenai
66.4
4.9K
400K
¥1.44 / ¥9输入/输出
122
Aamazon-nova-experimental-chat-26-01-10
amazon-nova-experimental-chat-26-01-10Amazon
66.1
603
-
-
123
Aqwen3-30b-a3b-instruct-2507
qwen3-30b-a3b-instruct-2507Alibaba
65.8
4.1K
262K
¥2.16 / ¥3.6输入/输出
124
Aamazon-nova-experimental-chat-11-10
amazon-nova-experimental-chat-11-10Amazon
65.5
4.1K
-
-
125
MImimo-v2-flash (thinking)
mimo-v2-flash (thinking)Xiaomi
65.3
1.9K
262K
¥0.72 / ¥2.16输入/输出
126
Aclaude-sonnet-4-20250514-thinking-32k
claude-sonnet-4-20250514-thinking-32kAnthropic
65.0
5.9K
200K
¥21.6 / ¥108输入/输出
127
Mkimi-k2-0711-preview
kimi-k2-0711-previewMoonshot
64.7
4.7K
131K
¥4.32 / ¥18输入/输出
128
Zglm-4.5-air
glm-4.5-airZai
64.4
5.1K
131K
¥0 / ¥0输入/输出
129
Oo1-preview
o1-previewOpenai
64.1
5.9K
128K
¥108 / ¥432输入/输出
130
Mminimax-m2
minimax-m2Minimax
63.9
1.1K
197K
¥0 / ¥0输入/输出
131
NV
nvidia-nemotron-3-super-120b-a12b
nvidia-nemotron-3-super-120b-a12bNvidia
63.6
1.3K
262K
¥1.44 / ¥5.76输入/输出
132
Aamazon-nova-experimental-chat-10-20
amazon-nova-experimental-chat-10-20Amazon
63.3
1.9K
-
-
133
Aqwen3-coder-480b-a35b-instruct
qwen3-coder-480b-a35b-instructAlibaba
63.0
4.4K
262K
¥6.2 / ¥24.8输入/输出
134
Ggemini-2.5-flash-lite-preview-09-2025-no-thinking
gemini-2.5-flash-lite-preview-09-2025-no-thinkingGoogle
62.7
8.2K
1.05M
¥0.72 / ¥2.88输入/输出
135
Mkimi-k2-0905-preview
kimi-k2-0905-previewMoonshot
62.5
2.1K
262K
¥4.32 / ¥18输入/输出
136
Ogpt-5-mini-high
gpt-5-mini-highOpenai
62.2
4.5K
400K
¥1.8 / ¥14.4输入/输出
137
Aqwen2.5-max
qwen2.5-maxAlibaba
61.9
4.9K
32K
¥11.5 / ¥46输入/输出
138
Aclaude-sonnet-4-20250514
claude-sonnet-4-20250514Anthropic
61.6
7.2K
200K
¥21.6 / ¥108输入/输出
139
Aqwen3-235b-a22b
qwen3-235b-a22bAlibaba
61.3
4.3K
131K
¥2.07 / ¥8.26输入/输出
140
Mminimax-m2.5
minimax-m2.5Minimax
61.1
6.4K
205K
¥0 / ¥0输入/输出
141
Ggemini-2.5-flash-lite-preview-06-17-thinking
gemini-2.5-flash-lite-preview-06-17-thinkingGoogle
60.8
5.7K
65.5K
¥0.72 / ¥2.88输入/输出
142
Zglm-4.6v
glm-4.6vZai
60.5
480
128K
¥2.16 / ¥6.48输入/输出
143
IA
mercury-2
mercury-2Inception Ai
60.2
540
128K
¥1.8 / ¥5.4输入/输出
144
Oo1-2024-12-17
o1-2024-12-17Openai
59.9
4.4K
128K
¥108 / ¥432输入/输出
145
Aamazon-nova-experimental-chat-10-09
amazon-nova-experimental-chat-10-09Amazon
59.7
481
-
-
146
Ogpt-4.1-mini-2025-04-14
gpt-4.1-mini-2025-04-14Openai
59.4
7.2K
1.05M
¥2.88 / ¥11.5输入/输出
147
UNintellect-3
-
59.1
780
131K
¥1.44 / ¥7.92输入/输出
148
Xgrok-3-mini-high
grok-3-mini-highXai
58.8
2.9K
128K
¥0 / ¥0输入/输出
149
Ggemini-2.0-flash-001
gemini-2.0-flash-001Google
58.5
6.9K
1.05M
¥1.08 / ¥4.32输入/输出
150
Oo4-mini-2025-04-16
o4-mini-2025-04-16Openai
58.3
7.9K
200K
¥7.92 / ¥31.7输入/输出
151
Ddeepseek-v3
deepseek-v3Deepseek
58.0
3.7K
128K
¥0 / ¥0输入/输出
152
Xgrok-3-mini-beta
grok-3-mini-betaXai
57.7
3.9K
1M
¥9 / ¥18输入/输出
153
Aqwen3-next-80b-a3b-thinking
qwen3-next-80b-a3b-thinkingAlibaba
57.4
2.3K
131K
¥1.04 / ¥10.3输入/输出
154
MAmistral-small-2506
mistral-small-2506Mistral
57.1
3.1K
262K
¥2.88 / ¥14.4输入/输出
155
Ggemma-3-27b-it
gemma-3-27b-itGoogle
56.9
7K
128K
¥2.15 / ¥2.15输入/输出
156
Zglm-4.7-flash
glm-4.7-flashZai
56.6
2.1K
200K
¥0 / ¥0输入/输出
157
UNtrinity-large-preview
-
56.3
5K
262K
¥1.8 / ¥6.48输入/输出
158
Ogpt-oss-120b
gpt-oss-120bOpenai
56.0
5K
131K
¥1.08 / ¥4.32输入/输出
159
Aclaude-3-7-sonnet-20250219
claude-3-7-sonnet-20250219Anthropic
55.7
7.1K
200K
¥21.6 / ¥108输入/输出
160
STstep-1o-turbo-202506
step-1o-turbo-202506Stepfun
55.5
1.4K
-
-
161
CO
command-a-03-2025
command-a-03-2025Cohere
55.2
9.5K
256K
¥18 / ¥72输入/输出
162
STstep-3
step-3Stepfun
54.9
1.1K
65.5K
¥1.8 / ¥4.68输入/输出
163
Anova-2-lite
nova-2-liteAmazon
54.6
2.1K
128K
¥2.38 / ¥19.8输入/输出
164
Aclaude-3-7-sonnet-20250219-thinking-32k
claude-3-7-sonnet-20250219-thinking-32kAnthropic
54.3
6.4K
-
-
165
Aqwen-plus-0125
qwen-plus-0125Alibaba
54.1
842
1M
¥0.83 / ¥2.07输入/输出
166
Mminimax-m1
minimax-m1Minimax
53.8
5.7K
1M
¥0.95 / ¥9.03输入/输出
167
Zglm-4.5v
glm-4.5vZai
53.5
895
64K
¥4.32 / ¥13输入/输出
168
NVnvidia-llama-3.3-nemotron-super-49b-v1.5
nvidia-llama-3.3-nemotron-super-49b-v1.5Nvidia
53.2
565
131K
¥2.88 / ¥2.88输入/输出
169
Ggemma-3-12b-it
gemma-3-12b-itGoogle
52.9
471
128K
¥1.96 / ¥1.96输入/输出
170
Aqwen3-32b
qwen3-32bAlibaba
52.7
590
131K
¥2.07 / ¥8.26输入/输出
171
NVnvidia-nemotron-3-nano-30b-a3b-bf16
nvidia-nemotron-3-nano-30b-a3b-bf16Nvidia
52.4
2.6K
131K
¥0 / ¥0输入/输出
172
AG
ling-flash-2.0
ling-flash-2.0Ant Group
52.1
1.2K
131K
¥1.01 / ¥4.1输入/输出
173
Aclaude-3-5-sonnet-20241022
claude-3-5-sonnet-20241022Anthropic
51.8
16K
200K
¥21.6 / ¥108输入/输出
174
UNtrinity-large-thinking
-
51.5
4.3K
262K
¥1.8 / ¥6.48输入/输出
175
Zglm-4-plus-0111
glm-4-plus-0111Zai
51.3
851
128K
¥72 / ¥72输入/输出
176
Oo3-mini-high
o3-mini-highOpenai
51.0
2.5K
200K
¥7.92 / ¥31.7输入/输出
177
TEhunyuan-turbos-20250226
hunyuan-turbos-20250226Tencent
50.7
293
131K
¥0 / ¥0输入/输出
178
NVllama-3.1-nemotron-ultra-253b-v1
llama-3.1-nemotron-ultra-253b-v1Nvidia
50.4
374
128K
¥4.32 / ¥13输入/输出
179
NVllama-3.3-nemotron-49b-super-v1
llama-3.3-nemotron-49b-super-v1Nvidia
50.1
301
131K
¥0 / ¥0输入/输出
180
Aqwq-32b
qwq-32bAlibaba
49.9
3.8K
131K
¥2.07 / ¥6.2输入/输出
181
Oo1-mini
o1-miniOpenai
49.6
9.3K
128K
¥7.92 / ¥31.7输入/输出
182
Oo3-mini
o3-miniOpenai
49.3
9.5K
200K
¥7.92 / ¥31.7输入/输出
183
Ogpt-5-nano-high
gpt-5-nano-highOpenai
49.0
1.5K
400K
¥0.36 / ¥2.88输入/输出
184
UNyi-lightning
-
48.7
4.7K
12K
¥1.44 / ¥1.44输入/输出
185
AI
olmo-3.1-32b-instruct
olmo-3.1-32b-instructAllenai
48.5
2.2K
200K
¥14.4 / ¥57.6输入/输出
186
Aqwen3-30b-a3b
qwen3-30b-a3bAlibaba
48.2
4.5K
128K
¥0.79 / ¥7.78输入/输出
187
Ggemini-2.0-flash-lite-preview-02-05
gemini-2.0-flash-lite-preview-02-05Google
47.9
3.6K
1.05M
¥0.54 / ¥2.16输入/输出
188
TEhunyuan-turbo-0110
hunyuan-turbo-0110Tencent
47.6
323
-
-
189
Ogpt-4o-2024-05-13
gpt-4o-2024-05-13Openai
47.3
20.4K
128K
¥36 / ¥108输入/输出
190
Aqwen2.5-plus-1127
qwen2.5-plus-1127Alibaba
47.1
1.8K
-
-
191
Aclaude-3-5-sonnet-20240620
claude-3-5-sonnet-20240620Anthropic
46.8
15K
200K
¥21.6 / ¥108输入/输出
192
Mllama-3.1-405b-instruct-bf16
llama-3.1-405b-instruct-bf16Meta
46.5
6.8K
128K
¥0 / ¥0输入/输出
193
Ddeepseek-v2.5-1210
deepseek-v2.5-1210Deepseek
46.2
1.2K
1M
¥1.01 / ¥2.02输入/输出
194
Ggemini-1.5-pro-002
gemini-1.5-pro-002Google
45.9
10.1K
-
-
195
STstep-2-16k-exp-202412
step-2-16k-exp-202412Stepfun
45.7
805
16.4K
¥37.5 / ¥118输入/输出
196
AGring-flash-2.0
ring-flash-2.0Ant Group
45.4
1.2K
131K
¥1.01 / ¥4.1输入/输出
197
AIolmo-3-32b-think
olmo-3-32b-thinkAllenai
45.1
816
128K
¥2.16 / ¥3.24输入/输出
198
Xgrok-2-2024-08-13
grok-2-2024-08-13Xai
44.8
10.7K
1M
¥9 / ¥18输入/输出
199
Zglm-4-plus
glm-4-plusZai
44.5
4.8K
128K
¥54 / ¥54输入/输出
200
Mllama-4-maverick-17b-128e-instruct
llama-4-maverick-17b-128e-instructMeta
44.3
6.8K
1M
¥1.8 / ¥6.26输入/输出
201
Mllama-3.1-405b-instruct-fp8
llama-3.1-405b-instruct-fp8Meta
44.0
11.1K
128K
¥0 / ¥0输入/输出
202
UNathene-v2-chat
-
43.7
4.3K
-
-
203
Ogpt-4o-mini-2024-07-18
gpt-4o-mini-2024-07-18Openai
43.4
12.3K
128K
¥1.08 / ¥4.32输入/输出
204
TEhunyuan-large-2025-02-10
hunyuan-large-2025-02-10Tencent
43.1
510
-
-
205
IAmercury
mercuryInception Ai
42.9
337
128K
¥1.8 / ¥5.4输入/输出
206
IB
granite-4.1-8b
granite-4.1-8bIbm
42.6
581
131K
¥0.36 / ¥0.72输入/输出
207
Mllama-4-scout-17b-16e-instruct
llama-4-scout-17b-16e-instructMeta
42.3
5.3K
128K
¥1.44 / ¥5.62输入/输出
208
Mllama-3.3-70b-instruct
llama-3.3-70b-instructMeta
42.0
9.1K
128K
¥0 / ¥0输入/输出
209
Ogpt-4o-2024-08-06
gpt-4o-2024-08-06Openai
41.7
8.2K
128K
¥18 / ¥72输入/输出
210
Ggemma-3n-e4b-it
gemma-3n-e4b-itGoogle
41.5
3.4K
128K
¥0 / ¥0输入/输出
211
Aqwen-max-0919
qwen-max-0919Alibaba
41.2
3.1K
131K
¥2.48 / ¥9.91输入/输出
212
Ogpt-4.1-nano-2025-04-14
gpt-4.1-nano-2025-04-14Openai
40.9
1K
1.05M
¥14.4 / ¥57.6输入/输出
213
NVllama-3.1-nemotron-70b-instruct
llama-3.1-nemotron-70b-instructNvidia
40.6
1.2K
128K
¥0 / ¥0输入/输出
214
Aclaude-3-opus-20240229
claude-3-opus-20240229Anthropic
40.3
31.1K
200K
¥108 / ¥540输入/输出
215
MAmagistral-medium-2506
magistral-medium-2506Mistral
40.1
1.7K
128K
¥14.4 / ¥36输入/输出
216
TEhunyuan-standard-2025-02-10
hunyuan-standard-2025-02-10Tencent
39.8
570
-
-
217
Aqwen2.5-72b-instruct
qwen2.5-72b-instructAlibaba
39.5
7.3K
131K
¥4.13 / ¥12.4输入/输出
218
Ogpt-oss-20b
gpt-oss-20bOpenai
39.2
1.8K
131K
¥0.32 / ¥1.3输入/输出
219
MAmistral-small-3.1-24b-instruct-2503
mistral-small-3.1-24b-instruct-2503Mistral
38.9
5.6K
262K
¥2.88 / ¥14.4输入/输出
220
Ggemini-advanced-0514
gemini-advanced-0514Google
38.7
7.8K
-
-
221
Ggemini-1.5-pro-001
gemini-1.5-pro-001Google
38.4
13.7K
-
-
222
Ogpt-4-turbo-2024-04-09
gpt-4-turbo-2024-04-09Openai
38.1
15.3K
128K
¥72 / ¥216输入/输出
223
Xgrok-2-mini-2024-08-13
grok-2-mini-2024-08-13Xai
37.8
9.4K
1M
¥9 / ¥18输入/输出
224
Aclaude-3-5-haiku-20241022
claude-3-5-haiku-20241022Anthropic
37.5
11.5K
200K
¥5.76 / ¥28.8输入/输出
225
Ddeepseek-v2.5
deepseek-v2.5Deepseek
37.3
4.5K
1M
¥1.01 / ¥2.02输入/输出
226
MAmistral-large-2411
mistral-large-2411Mistral
37.0
4.4K
128K
¥14.4 / ¥43.2输入/输出
227
MAmistral-large-2407
mistral-large-2407Mistral
36.7
8.3K
131K
¥14.4 / ¥43.2输入/输出
228
UNathene-70b-0725
-
36.4
3.3K
-
-
229
Ogpt-4-1106-preview
gpt-4-1106-previewOpenai
36.1
14.9K
8.19K
¥216 / ¥432输入/输出
230
Mllama-3.1-70b-instruct
llama-3.1-70b-instructMeta
35.9
10.4K
131K
¥2.88 / ¥2.88输入/输出
231
Ggemma-3-4b-it
gemma-3-4b-itGoogle
35.6
565
128K
¥1.44 / ¥1.44输入/输出
232
TEhunyuan-large-vision
hunyuan-large-visionTencent
35.3
964
-
-
233
Ggemini-1.5-flash-002
gemini-1.5-flash-002Google
35.0
6.3K
2M
¥0.54 / ¥2.2输入/输出
234
AIllama-3.1-tulu-3-70b
llama-3.1-tulu-3-70bAllenai
34.7
537
-
-
235
AIolmo-3.1-32b-think
olmo-3.1-32b-thinkAllenai
34.5
1.2K
200K
¥14.4 / ¥57.6输入/输出
236
Ogpt-4-0125-preview
gpt-4-0125-previewOpenai
34.2
14.4K
8.19K
¥216 / ¥432输入/输出
237
IBibm-granite-h-small
ibm-granite-h-smallIbm
33.9
974
-
-
238
Aamazon-nova-pro-v1.0
amazon-nova-pro-v1.0Amazon
33.6
4.1K
300K
¥5.76 / ¥23输入/输出
239
Ggemini-1.5-flash-001
gemini-1.5-flash-001Google
33.3
11.1K
2M
¥0.54 / ¥2.2输入/输出
240
Aclaude-3-sonnet-20240229
claude-3-sonnet-20240229Anthropic
33.1
17.1K
200K
¥21.6 / ¥108输入/输出
241
NVllama-3.1-nemotron-51b-instruct
llama-3.1-nemotron-51b-instructNvidia
32.8
781
128K
¥0 / ¥0输入/输出
242
UNreka-core-20240904
-
32.5
1.3K
-
-
243
Ggemma-2-27b-it
gemma-2-27b-itGoogle
32.2
13.6K
8.19K
¥0.58 / ¥0.58输入/输出
244
Mllama-3-70b-instruct
llama-3-70b-instructMeta
31.9
21.4K
8.19K
¥3.67 / ¥5.33输入/输出
245
Aqwen2.5-coder-32b-instruct
qwen2.5-coder-32b-instructAlibaba
31.7
1K
131K
¥2.07 / ¥6.2输入/输出
246
AIolmo-2-0325-32b-instruct
olmo-2-0325-32b-instructAllenai
31.4
363
-
-
247
UNjamba-1.5-large
-
31.1
1.6K
256K
¥0 / ¥0输入/输出
248
UNgemma-2-9b-it-simpo
-
30.8
1.7K
8.19K
¥1.44 / ¥1.44输入/输出
249
Zglm-4-0520
glm-4-0520Zai
30.5
1.6K
128K
¥108 / ¥108输入/输出
250
MAmistral-small-24b-instruct-2501
mistral-small-24b-instruct-2501Mistral
30.3
2.2K
262K
¥2.88 / ¥14.4输入/输出
251
NVnemotron-4-340b-instruct
nemotron-4-340b-instructNvidia
30.0
3.1K
-
-
252
COcommand-r-plus-08-2024
command-r-plus-08-2024Cohere
29.7
1.8K
128K
¥18 / ¥72输入/输出
253
Ogpt-4-0314
gpt-4-0314Openai
29.4
8K
8.19K
¥216 / ¥432输入/输出
254
M
phi-4
phi-4Microsoft
29.1
3.5K
128K
¥0.9 / ¥3.6输入/输出
255
Aamazon-nova-lite-v1.0
amazon-nova-lite-v1.0Amazon
28.9
3.2K
300K
¥0.43 / ¥1.73输入/输出
256
Aqwen2-72b-instruct
qwen2-72b-instructAlibaba
28.6
6.7K
131K
¥4.13 / ¥12.4输入/输出
257
Ggemma-2-9b-it
gemma-2-9b-itGoogle
28.3
9.7K
8.19K
¥1.44 / ¥1.44输入/输出
258
COcommand-r-plus
command-r-plusCohere
28.0
12.1K
128K
¥18 / ¥72输入/输出
259
COc4ai-aya-expanse-32b
c4ai-aya-expanse-32bCohere
27.7
5.2K
-
-
260
Aclaude-3-haiku-20240307
claude-3-haiku-20240307Anthropic
27.5
19.3K
200K
¥1.8 / ¥9输入/输出
261
UNreka-flash-20240904
-
27.2
1.3K
65.5K
¥0.72 / ¥1.44输入/输出
262
Ggemini-1.5-flash-8b-001
gemini-1.5-flash-8b-001Google
26.9
6.7K
2M
¥0.54 / ¥2.2输入/输出
263
Ogpt-4-0613
gpt-4-0613Openai
26.6
13.2K
8.19K
¥216 / ¥432输入/输出
264
Aamazon-nova-micro-v1.0
amazon-nova-micro-v1.0Amazon
26.3
3.1K
128K
¥0.25 / ¥1.01输入/输出
265
Ddeepseek-coder-v2
deepseek-coder-v2Deepseek
26.1
2.7K
1M
¥1.01 / ¥2.02输入/输出
266
TEhunyuan-standard-256k
hunyuan-standard-256kTencent
25.8
532
-
-
267
MAmistral-large-2402
mistral-large-2402Mistral
25.5
9.5K
262K
¥2.88 / ¥14.4输入/输出
268
Mllama-3.1-8b-instruct
llama-3.1-8b-instructMeta
25.2
8.9K
131K
¥0.79 / ¥0.79输入/输出
269
MAministral-8b-2410
ministral-8b-2410Mistral
24.9
916
128K
¥0.72 / ¥0.72输入/输出
270
COcommand-r-08-2024
command-r-08-2024Cohere
24.6
1.9K
128K
¥18 / ¥72输入/输出
271
Aqwen1.5-72b-chat
qwen1.5-72b-chatAlibaba
24.4
5.5K
-
-
272
Aqwen1.5-110b-chat
qwen1.5-110b-chatAlibaba
24.1
3.7K
-
-
273
COc4ai-aya-expanse-8b
c4ai-aya-expanse-8bCohere
23.8
1.7K
-
-
274
UNjamba-1.5-mini
-
23.5
1.6K
256K
¥0 / ¥0输入/输出
275
AIllama-3.1-tulu-3-8b
llama-3.1-tulu-3-8bAllenai
23.2
520
-
-
276
UNyi-1.5-34b-chat
-
23.0
3.4K
-
-
277
Mllama-3-8b-instruct
llama-3-8b-instructMeta
22.7
14.8K
8.19K
¥0.29 / ¥0.29输入/输出
278
UNreka-flash-21b-20240226-online
-
22.4
2K
-
-
279
COcommand-r
command-rCohere
22.1
8.3K
128K
¥18 / ¥72输入/输出
280
MAmistral-medium
mistral-mediumMistral
21.8
4.6K
262K
¥2.88 / ¥14.4输入/输出
281
UNreka-flash-21b-20240226
-
21.6
3.4K
-
-
282
Aqwq-32b-preview
qwq-32b-previewAlibaba
21.3
487
131K
¥2.07 / ¥6.2输入/输出
283
Aqwen1.5-32b-chat
qwen1.5-32b-chatAlibaba
21.0
3.1K
-
-
284
Ggemini-pro
gemini-proGoogle
20.7
641
1.05M
¥14.4 / ¥86.4输入/输出
285
UNinternlm2_5-20b-chat
-
20.4
1.8K
-
-
286
MAmixtral-8x22b-instruct-v0.1
mixtral-8x22b-instruct-v0.1Mistral
20.2
7.8K
64K
¥14.4 / ¥43.2输入/输出
287
Ggemini-pro-dev-api
gemini-pro-dev-apiGoogle
19.9
2.5K
1.05M
¥14.4 / ¥86.4输入/输出
288
Ggemma-2-2b-it
gemma-2-2b-itGoogle
19.6
7.9K
128K
¥0 / ¥0输入/输出
289
Ogpt-3.5-turbo-0125
gpt-3.5-turbo-0125Openai
19.3
10.3K
16.4K
¥3.6 / ¥10.8输入/输出
290
MAmixtral-8x7b-instruct-v0.1
mixtral-8x7b-instruct-v0.1Mistral
19.0
10.9K
32K
¥5.04 / ¥5.04输入/输出
291
UNyi-34b-chat
-
18.8
1.9K
-
-
292
UNstarling-lm-7b-beta
-
18.5
2.2K
200K
¥5.4 / ¥18.7输入/输出
293
UNdbrx-instruct-preview
-
18.2
4.9K
-
-
294
Aqwen1.5-14b-chat
qwen1.5-14b-chatAlibaba
17.9
2.6K
-
-
295
Mwizardlm-70b
wizardlm-70bMicrosoft
17.6
1.2K
-
-
296
IBgranite-3.1-8b-instruct
granite-3.1-8b-instructIbm
17.4
551
-
-
297
Mllama-3.2-3b-instruct
llama-3.2-3b-instructMeta
17.1
1.3K
131K
¥0.22 / ¥0.35输入/输出
298
UNzephyr-orpo-141b-A35b-v0.1
-
16.8
683
200K
¥108 / ¥432输入/输出
299
IBgranite-3.1-2b-instruct
granite-3.1-2b-instructIbm
16.5
579
-
-
300
UNopenchat-3.5-0106
-
16.2
1.8K
-
-
301
Mllama-2-70b-chat
llama-2-70b-chatMeta
16.0
5.5K
-
-
302
Mphi-3-medium-4k-instruct
phi-3-medium-4k-instructMicrosoft
15.7
3.8K
4.1K
¥1.22 / ¥4.9输入/输出
303
UNtulu-2-dpo-70b
-
15.4
827
-
-
304
UNopenchat-3.5
-
15.1
1.2K
-
-
305
UNstarling-lm-7b-alpha
-
14.8
1.3K
200K
¥5.4 / ¥18.7输入/输出
306
Ddeepseek-llm-67b-chat
deepseek-llm-67b-chatDeepseek
14.6
620
1M
¥1.01 / ¥2.02输入/输出
307
UNnous-hermes-2-mixtral-8x7b-dpo
-
14.3
467
1M
¥36 / ¥180输入/输出
308
UNvicuna-33b
-
14.0
3.1K
-
-
309
Ogpt-3.5-turbo-1106
gpt-3.5-turbo-1106Openai
13.7
2.4K
16.4K
¥7.2 / ¥14.4输入/输出
310
UNsnowflake-arctic-instruct
-
13.4
4K
-
-
311
Mphi-3-small-8k-instruct
phi-3-small-8k-instructMicrosoft
13.2
3.1K
8.19K
¥1.08 / ¥4.32输入/输出
312
UNopenhermes-2.5-mistral-7b
-
12.9
722
1M
¥36 / ¥180输入/输出
313
IBgranite-3.0-8b-instruct
granite-3.0-8b-instructIbm
12.6
1.1K
-
-
314
MAmistral-7b-instruct-v0.2
mistral-7b-instruct-v0.2Mistral
12.3
2.6K
262K
¥2.88 / ¥14.4输入/输出
315
Aqwen1.5-7b-chat
qwen1.5-7b-chatAlibaba
12.0
589
-
-
316
NVllama2-70b-steerlm-chat
llama2-70b-steerlm-chatNvidia
11.8
451
-
-
317
UNmpt-30b-chat
-
11.5
341
-
-
318
IBgranite-3.0-2b-instruct
granite-3.0-2b-instructIbm
11.2
1.2K
-
-
319
Mllama-2-13b-chat
llama-2-13b-chatMeta
10.9
2.6K
-
-
320
Mphi-3-mini-4k-instruct-june-2024
phi-3-mini-4k-instruct-june-2024Microsoft
10.6
1.8K
4.1K
¥0.94 / ¥3.74输入/输出
321
Mwizardlm-13b
wizardlm-13bMicrosoft
10.4
983
-
-
322
UNsolar-10.7b-instruct-v1.0
-
10.1
601
128K
¥0 / ¥0输入/输出
323
Ggemma-1.1-7b-it
gemma-1.1-7b-itGoogle
9.8
3.6K
-
-
324
UNzephyr-7b-beta
-
9.5
1.6K
-
-
325
UNvicuna-13b
-
9.2
2.6K
-
-
326
Mllama-3.2-1b-instruct
llama-3.2-1b-instructMeta
9.0
1.2K
16.4K
¥0.07 / ¥0.08输入/输出
327
Mllama-2-7b-chat
llama-2-7b-chatMeta
8.7
1.9K
128K
¥4.03 / ¥48输入/输出
328
Aqwen-14b-chat
qwen-14b-chatAlibaba
8.4
753
32.8K
¥1.04 / ¥3.1输入/输出
329
UNdolphin-2.2.1-mistral-7b
-
8.1
208
262K
¥2.88 / ¥14.4输入/输出
330
Mphi-3-mini-4k-instruct
phi-3-mini-4k-instructMicrosoft
7.8
2.9K
4.1K
¥0.94 / ¥3.74输入/输出
331
UNzephyr-7b-alpha
-
7.6
283
-
-
332
Mcodellama-34b-instruct
codellama-34b-instructMeta
7.3
1.2K
-
-
333
UNfalcon-180b-chat
-
7.0
207
-
-
334
MAmistral-7b-instruct
mistral-7b-instructMistral
6.7
1.3K
262K
¥2.88 / ¥14.4输入/输出
335
UNstripedhyena-nous-7b
-
6.4
738
-
-
336
AIolmo-7b-instruct
olmo-7b-instructAllenai
6.2
537
-
-
337
UNguanaco-33b
-
5.9
331
200K
¥14.4 / ¥57.6输入/输出
338
Gpalm-2
palm-2Google
5.6
1.2K
-
-
339
UNsmollm2-1.7b-instruct
-
5.3
339
-
-
340
Mphi-3-mini-128k-instruct
phi-3-mini-128k-instructMicrosoft
5.0
2.5K
128K
¥0.94 / ¥3.74输入/输出
341
UNvicuna-7b
-
4.8
935
-
-
342
Aqwen1.5-4b-chat
qwen1.5-4b-chatAlibaba
4.5
1.1K
-
-
343
Ggemma-7b-it
gemma-7b-itGoogle
4.2
1.3K
-
-
344
UNchatglm3-6b
-
3.9
637
200K
¥5.4 / ¥18.7输入/输出
345
Ggemma-1.1-2b-it
gemma-1.1-2b-itGoogle
3.6
1.5K
-
-
346
Ggemma-2b-it
gemma-2b-itGoogle
3.4
768
-
-
347
UNgpt4all-13b-snoozy
-
3.1
253
1M
¥36 / ¥216输入/输出
348
UNkoala-13b
-
2.8
792
-
-
349
UNchatglm2-6b
-
2.5
369
200K
¥5.4 / ¥18.7输入/输出
350
UNmpt-7b-chat
-
2.2
466
-
-
351
UNRWKV-4-Raven-14B
-
2.0
556
-
-
352
UNalpaca-13b
-
1.7
653
-
-
353
UNoasst-pythia-12b
-
1.4
683
-
-
354
UNchatglm-6b
-
1.1
492
200K
¥5.4 / ¥18.7输入/输出
355
UNfastchat-t5-3b
-
0.8
387
-
-
356
UNstablelm-tuned-alpha-7b
-
0.6
354
-
-
357
Mllama-13b
llama-13bMeta
0.3
247
-
-
358
UNdolly-v2-12b
-
0.0
356
-
-
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 6.4K。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
多轮对话常见问题
多轮对话排行榜看什么指标？
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。
多轮对话模型应该怎么选？
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。