1
A
claude-opus-4-6
claude-opus-4-6Anthropic
100.0
2.6K
1M
¥36 / ¥180输入/输出
对话 · 文本 · 医疗健康排行榜
基于公开偏好评测数据展示 文本 / 医疗健康 榜单，每个榜单独立排序。
医疗健康模型怎么选？
医疗健康排行榜用于回答“医疗健康哪个 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 2.6K。 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-4-6claude-opus-4-6-thinkingclaude-opus-4-7-thinkingqwen3.5-max-previewmuse-spark
2
Aclaude-opus-4-6-thinking
claude-opus-4-6-thinkingAnthropic
99.7
2.5K
1M
¥36 / ¥180输入/输出
3
Aclaude-opus-4-7-thinking
claude-opus-4-7-thinkingAnthropic
99.4
1.5K
1M
¥36 / ¥180输入/输出
4
A
qwen3.5-max-preview
qwen3.5-max-previewAlibaba
99.1
1.4K
-
-
5
M
muse-spark
muse-sparkMeta
98.8
864
-
-
6
G
gemini-3-pro
gemini-3-proGoogle
98.5
2.5K
1.05M
¥14.4 / ¥86.4输入/输出
7
Aclaude-opus-4-7
claude-opus-4-7Anthropic
98.2
1.5K
1M
¥36 / ¥180输入/输出
8
Ggemini-3.1-pro-preview
gemini-3.1-pro-previewGoogle
97.9
3.2K
1.05M
¥14.4 / ¥86.4输入/输出
9
Ggemini-3.5-flash
gemini-3.5-flashGoogle
97.6
633
1.05M
¥10.8 / ¥64.8输入/输出
10
B
ernie-5.1
ernie-5.1Baidu
97.3
1.1K
119K
¥5.4 / ¥21.6输入/输出
11
B
dola-seed-2.0-pro
dola-seed-2.0-proBytedance
97.0
2.7K
-
-
12
Ggemini-2.5-pro
gemini-2.5-proGoogle
96.6
7.7K
1.05M
¥9 / ¥72输入/输出
13
Aqwen3.7-max-preview
qwen3.7-max-previewAlibaba
96.3
297
1M
¥18 / ¥54输入/输出
14
Bernie-5.0-preview-1203
ernie-5.0-preview-1203Baidu
96.0
679
128K
¥7.92 / ¥14.4输入/输出
15
D
deepseek-v4-pro-thinking
deepseek-v4-pro-thinkingDeepseek
95.7
1.1K
1M
¥3.13 / ¥6.26输入/输出
16
MI
mimo-v2.5-pro
mimo-v2.5-proXiaomi
95.4
1.1K
1.05M
¥7.2 / ¥21.6输入/输出
17
Z
glm-5.1
glm-5.1Zai
95.1
997
200K
¥0 / ¥0输入/输出
18
Ddeepseek-v3.2-exp-thinking
deepseek-v3.2-exp-thinkingDeepseek
94.8
438
128K
¥0 / ¥0输入/输出
19
A
amazon-nova-experimental-chat-12-10
amazon-nova-experimental-chat-12-10Amazon
94.5
230
-
-
20
Aqwen3-max-preview
qwen3-max-previewAlibaba
94.2
1.5K
262K
¥6.2 / ¥24.8输入/输出
21
Ddeepseek-v3.1-terminus-thinking
deepseek-v3.1-terminus-thinkingDeepseek
93.9
228
128K
¥1.8 / ¥5.04输入/输出
22
Ggemini-3-flash
gemini-3-flashGoogle
93.6
2.1K
1.05M
¥3.6 / ¥21.6输入/输出
23
X
grok-3-preview-02-24
grok-3-preview-02-24Xai
93.3
1.6K
1M
¥9 / ¥18输入/输出
24
Aqwen3.6-max-preview
qwen3.6-max-previewAlibaba
93.0
319
246K
¥9.5 / ¥56.9输入/输出
25
M
kimi-k2.6
kimi-k2.6Moonshot
92.7
1.1K
262K
¥6.84 / ¥28.8输入/输出
26
Zglm-4.7
glm-4.7Zai
92.4
816
205K
¥0 / ¥0输入/输出
27
Bernie-5.0-0110
ernie-5.0-0110Baidu
92.1
2.3K
128K
¥7.92 / ¥14.4输入/输出
28
M
longcat-flash-chat
longcat-flash-chatMeituan
91.8
668
128K
¥1.08 / ¥10.8输入/输出
29
Ddeepseek-v4-pro
deepseek-v4-proDeepseek
91.5
1.2K
1M
¥3.13 / ¥6.26输入/输出
30
O
gpt-5.4-high
gpt-5.4-highOpenai
91.2
2K
1.05M
¥18 / ¥108输入/输出
31
Xgrok-4.20-multi-agent-beta-0309
grok-4.20-multi-agent-beta-0309Xai
90.9
2K
2M
¥14.4 / ¥43.2输入/输出
32
Zglm-4.6
glm-4.6Zai
90.5
1.9K
205K
¥4.32 / ¥15.8输入/输出
33
Ogpt-5.1-high
gpt-5.1-highOpenai
90.2
2.5K
400K
¥9 / ¥72输入/输出
34
Zglm-5
glm-5Zai
89.9
1.6K
205K
¥7.2 / ¥23输入/输出
35
Xgrok-4.20-beta-0309-reasoning
grok-4.20-beta-0309-reasoningXai
89.6
2.1K
2M
¥14.4 / ¥43.2输入/输出
36
Aqwen3.5-397b-a17b
qwen3.5-397b-a17bAlibaba
89.3
2.4K
262K
¥3.1 / ¥18.6输入/输出
37
Aqwen3-next-80b-a3b-instruct
qwen3-next-80b-a3b-instructAlibaba
89.0
1.2K
131K
¥1.04 / ¥4.13输入/输出
38
Xgrok-4.20-beta1
grok-4.20-beta1Xai
88.7
1.8K
2M
¥14.4 / ¥43.2输入/输出
39
Xgrok-4.1-thinking
grok-4.1-thinkingXai
88.4
4.2K
200K
¥14.4 / ¥72输入/输出
40
Zglm-4.5
glm-4.5Zai
88.1
1.4K
131K
¥4.32 / ¥15.8输入/输出
41
Ggemini-3-flash (thinking-minimal)
gemini-3-flash (thinking-minimal)Google
87.8
3.7K
1.05M
¥3.6 / ¥21.6输入/输出
42
MA
mistral-large-3
mistral-large-3Mistral
87.5
2.8K
262K
¥3.6 / ¥10.8输入/输出
43
Ochatgpt-4o-latest-20250326
chatgpt-4o-latest-20250326Openai
87.2
4.6K
128K
¥18 / ¥72输入/输出
44
TE
hunyuan-t1-20250711
hunyuan-t1-20250711Tencent
86.9
258
131K
¥0 / ¥0输入/输出
45
Ogpt-5.5-high
gpt-5.5-highOpenai
86.6
1.2K
1.05M
¥36 / ¥216输入/输出
46
MAmistral-medium-2508
mistral-medium-2508Mistral
86.3
5.7K
262K
¥2.88 / ¥14.4输入/输出
47
Ogpt-5.5
gpt-5.5Openai
86.0
1.2K
1.05M
¥36 / ¥216输入/输出
48
Bernie-5.0-preview-1022
ernie-5.0-preview-1022Baidu
85.7
245
128K
¥7.92 / ¥14.4输入/输出
49
Aqwen3-235b-a22b-thinking-2507
qwen3-235b-a22b-thinking-2507Alibaba
85.4
522
131K
¥2.07 / ¥8.26输入/输出
50
Aqwen3.6-plus
qwen3.6-plusAlibaba
85.1
1.2K
1M
¥3.6 / ¥21.6输入/输出
51
Mkimi-k2.5-thinking
kimi-k2.5-thinkingMoonshot
84.8
2.5K
262K
¥4.32 / ¥21.6输入/输出
52
Aamazon-nova-experimental-chat-11-10
amazon-nova-experimental-chat-11-10Amazon
84.5
1.7K
-
-
53
Ggemma-4-31b
gemma-4-31bGoogle
84.1
402
262K
¥3.24 / ¥7.2输入/输出
54
Oo3-2025-04-16
o3-2025-04-16Openai
83.8
3.3K
200K
¥14.4 / ¥57.6输入/输出
55
Ddeepseek-v3.1-terminus
deepseek-v3.1-terminusDeepseek
83.5
258
128K
¥1.8 / ¥5.04输入/输出
56
Ogpt-5.2-chat-latest-20260210
gpt-5.2-chat-latest-20260210Openai
83.2
2.3K
400K
¥12.6 / ¥101输入/输出
57
Ddeepseek-v4-flash
deepseek-v4-flashDeepseek
82.9
1.2K
1M
¥1.01 / ¥2.02输入/输出
58
Ddeepseek-v4-flash-thinking
deepseek-v4-flash-thinkingDeepseek
82.6
1.2K
1M
¥1.01 / ¥2.02输入/输出
59
Ddeepseek-r1-0528
deepseek-r1-0528Deepseek
82.3
1.2K
164K
¥3.6 / ¥15.5输入/输出
60
Aqwen3-235b-a22b-instruct-2507
qwen3-235b-a22b-instruct-2507Alibaba
82.0
5.6K
128K
¥2.09 / ¥8.23输入/输出
61
Ogpt-5.4
gpt-5.4Openai
81.7
2.1K
1.05M
¥18 / ¥108输入/输出
62
Xgrok-4.1
grok-4.1Xai
81.4
4.2K
200K
¥14.4 / ¥72输入/输出
63
Ogpt-5.1
gpt-5.1Openai
81.1
2.6K
400K
¥9 / ¥72输入/输出
64
Aclaude-opus-4-5-20251101
claude-opus-4-5-20251101Anthropic
80.8
4.3K
200K
¥36 / ¥180输入/输出
65
Aclaude-sonnet-4-6
claude-sonnet-4-6Anthropic
80.5
2K
1M
¥21.6 / ¥108输入/输出
66
Ddeepseek-v3.1-thinking
deepseek-v3.1-thinkingDeepseek
80.2
703
128K
¥1.44 / ¥5.04输入/输出
67
Aclaude-sonnet-4-5-20250929
claude-sonnet-4-5-20250929Anthropic
79.9
4.8K
200K
¥21.6 / ¥108输入/输出
68
MImimo-v2-pro
mimo-v2-proXiaomi
79.6
1.6K
1.05M
¥7.2 / ¥21.6输入/输出
69
Ddeepseek-v3.2
deepseek-v3.2Deepseek
79.3
3K
128K
¥2.09 / ¥3.1输入/输出
70
Xgrok-4-0709
grok-4-0709Xai
79.0
2.3K
256K
¥21.6 / ¥108输入/输出
71
Aqwen3-vl-235b-a22b-instruct
qwen3-vl-235b-a22b-instructAlibaba
78.7
628
128K
¥2.16 / ¥8.64输入/输出
72
Ddeepseek-v3.1
deepseek-v3.1Deepseek
78.4
938
128K
¥1.44 / ¥5.04输入/输出
73
Ggemini-3.1-flash-lite-preview
gemini-3.1-flash-lite-previewGoogle
78.0
2.5K
1.05M
¥1.8 / ¥10.8输入/输出
74
Ggemini-2.5-flash
gemini-2.5-flashGoogle
77.7
7.6K
1.05M
¥2.16 / ¥18输入/输出
75
Ddeepseek-v3.2-exp
deepseek-v3.2-expDeepseek
77.4
594
128K
¥0 / ¥0输入/输出
76
Aqwen3.5-122b-a10b
qwen3.5-122b-a10bAlibaba
77.1
1.9K
262K
¥2.88 / ¥23输入/输出
77
Ogpt-5.2
gpt-5.2Openai
76.8
3.2K
400K
¥12.6 / ¥101输入/输出
78
Aclaude-opus-4-5-20251101-thinking-32k
claude-opus-4-5-20251101-thinking-32kAnthropic
76.5
2.3K
200K
¥108 / ¥540输入/输出
79
Aamazon-nova-experimental-chat-26-02-10
amazon-nova-experimental-chat-26-02-10Amazon
76.2
216
-
-
80
Mlongcat-flash-chat-2602-exp
longcat-flash-chat-2602-expMeituan
75.9
1.6K
128K
¥1.08 / ¥10.8输入/输出
81
Ggemma-4-26b-a4b
gemma-4-26b-a4bGoogle
75.6
371
262K
¥0.94 / ¥2.88输入/输出
82
Aclaude-sonnet-4-5-20250929-thinking-32k
claude-sonnet-4-5-20250929-thinking-32kAnthropic
75.3
4.8K
200K
¥21.6 / ¥108输入/输出
83
Aqwen3.5-27b
qwen3.5-27bAlibaba
75.0
1.8K
262K
¥2.16 / ¥17.3输入/输出
84
Ggemini-2.5-flash-preview-09-2025
gemini-2.5-flash-preview-09-2025Google
74.7
1.7K
1M
¥2.16 / ¥18输入/输出
85
Aqwen3.5-35b-a3b
qwen3.5-35b-a3bAlibaba
74.4
2K
262K
¥1.8 / ¥14.4输入/输出
86
Ogpt-5.2-high
gpt-5.2-highOpenai
74.1
3.2K
400K
¥12.6 / ¥101输入/输出
87
Ddeepseek-v3.2-thinking
deepseek-v3.2-thinkingDeepseek
73.8
2.6K
128K
¥2.09 / ¥3.1输入/输出
88
MImimo-v2.5
mimo-v2.5Xiaomi
73.5
1.1K
1.05M
¥2.88 / ¥14.4输入/输出
89
Xgrok-4-fast-reasoning
grok-4-fast-reasoningXai
73.2
882
2M
¥1.44 / ¥3.6输入/输出
90
Mkimi-k2-thinking-turbo
kimi-k2-thinking-turboMoonshot
72.9
3.7K
262K
¥17.3 / ¥72输入/输出
91
MImimo-v2-flash (non-thinking)
mimo-v2-flash (non-thinking)Xiaomi
72.6
3K
262K
¥0.72 / ¥2.16输入/输出
92
TEhunyuan-turbos-20250416
hunyuan-turbos-20250416Tencent
72.3
589
131K
¥0 / ¥0输入/输出
93
Aqwen3-vl-235b-a22b-thinking
qwen3-vl-235b-a22b-thinkingAlibaba
72.0
435
131K
¥2.06 / ¥8.26输入/输出
94
Ogpt-5.5-instant
gpt-5.5-instantOpenai
71.6
1.9K
400K
¥9 / ¥72输入/输出
95
Xgrok-4-fast-chat
grok-4-fast-chatXai
71.3
394
2M
¥1.44 / ¥3.6输入/输出
96
Xgrok-4-1-fast-reasoning
grok-4-1-fast-reasoningXai
71.0
3.5K
2M
¥1.44 / ¥3.6输入/输出
97
Aclaude-opus-4-1-20250805-thinking-16k
claude-opus-4-1-20250805-thinking-16kAnthropic
70.7
2.7K
200K
¥108 / ¥540输入/输出
98
Aclaude-opus-4-1-20250805
claude-opus-4-1-20250805Anthropic
70.4
4.4K
200K
¥108 / ¥540输入/输出
99
Ogpt-5-high
gpt-5-highOpenai
70.1
1.8K
400K
¥9 / ¥72输入/输出
100
TEhunyuan-hy3-preview
hunyuan-hy3-previewTencent
69.8
391
256K
¥0 / ¥0输入/输出
101
Ogpt-5-chat
gpt-5-chatOpenai
69.5
1.7K
400K
¥9 / ¥72输入/输出
102
Xgrok-4.3
grok-4.3Xai
69.2
1.2K
1M
¥9 / ¥18输入/输出
103
Ogpt-4.5-preview-2025-02-27
gpt-4.5-preview-2025-02-27Openai
68.9
589
8.19K
¥216 / ¥432输入/输出
104
ST
step-3.5-flash
step-3.5-flashStepfun
68.6
2.4K
256K
¥0.69 / ¥2.07输入/输出
105
Aqwen3.5-flash
qwen3.5-flashAlibaba
68.3
2K
1M
¥1.24 / ¥12.4输入/输出
106
Aqwen3-235b-a22b-no-thinking
qwen3-235b-a22b-no-thinkingAlibaba
68.0
2.3K
131K
¥2.07 / ¥8.26输入/输出
107
Mkimi-k2.5-instant
kimi-k2.5-instantMoonshot
67.7
541
262K
¥4.32 / ¥21.6输入/输出
108
MImimo-v2-flash (thinking)
mimo-v2-flash (thinking)Xiaomi
67.4
691
262K
¥0.72 / ¥2.16输入/输出
109
Aamazon-nova-experimental-chat-10-20
amazon-nova-experimental-chat-10-20Amazon
67.1
643
-
-
110
Aqwen3-max-2025-09-23
qwen3-max-2025-09-23Alibaba
66.8
451
258K
¥6.19 / ¥24.7输入/输出
111
Aamazon-nova-experimental-chat-26-01-10
amazon-nova-experimental-chat-26-01-10Amazon
66.5
238
-
-
112
Zglm-4.5-air
glm-4.5-airZai
66.2
1.6K
131K
¥0 / ¥0输入/输出
113
M
minimax-m2.7
minimax-m2.7Minimax
65.9
1.5K
205K
¥0 / ¥0输入/输出
114
Ogpt-5.4-mini-high
gpt-5.4-mini-highOpenai
65.5
1.9K
400K
¥5.4 / ¥32.4输入/输出
115
Aqwen3-30b-a3b-instruct-2507
qwen3-30b-a3b-instruct-2507Alibaba
65.2
1.3K
262K
¥2.16 / ¥3.6输入/输出
116
Xgrok-3-mini-high
grok-3-mini-highXai
64.9
988
128K
¥0 / ¥0输入/输出
117
Aqwen3-next-80b-a3b-thinking
qwen3-next-80b-a3b-thinkingAlibaba
64.6
721
131K
¥1.04 / ¥10.3输入/输出
118
Ogpt-5.3-chat-latest
gpt-5.3-chat-latestOpenai
64.3
2.3K
128K
¥12.6 / ¥101输入/输出
119
Ogpt-oss-120b
gpt-oss-120bOpenai
64.0
1.6K
131K
¥1.08 / ¥4.32输入/输出
120
Ggemma-3-27b-it
gemma-3-27b-itGoogle
63.7
2.4K
128K
¥2.15 / ¥2.15输入/输出
121
Zglm-4-plus-0111
glm-4-plus-0111Zai
63.4
293
128K
¥72 / ¥72输入/输出
122
Mminimax-m2.1-preview
minimax-m2.1-previewMinimax
63.1
1.1K
205K
¥0 / ¥0输入/输出
123
Ggemini-2.5-flash-lite-preview-09-2025-no-thinking
gemini-2.5-flash-lite-preview-09-2025-no-thinkingGoogle
62.8
2.5K
1.05M
¥0.72 / ¥2.88输入/输出
124
Ggemini-2.5-flash-lite-preview-06-17-thinking
gemini-2.5-flash-lite-preview-06-17-thinkingGoogle
62.5
2K
65.5K
¥0.72 / ¥2.88输入/输出
125
NV
nvidia-nemotron-3-super-120b-a12b
nvidia-nemotron-3-super-120b-a12bNvidia
62.2
479
262K
¥1.44 / ¥5.76输入/输出
126
Anova-2-lite
nova-2-liteAmazon
61.9
711
128K
¥2.38 / ¥19.8输入/输出
127
Aqwen2.5-max
qwen2.5-maxAlibaba
61.6
1.6K
32K
¥11.5 / ¥46输入/输出
128
Mkimi-k2-0905-preview
kimi-k2-0905-previewMoonshot
61.3
724
262K
¥4.32 / ¥18输入/输出
129
Ddeepseek-v3-0324
deepseek-v3-0324Deepseek
61.0
2.7K
75K
¥1.44 / ¥5.76输入/输出
130
Aclaude-haiku-4-5-20251001
claude-haiku-4-5-20251001Anthropic
60.7
4.8K
200K
¥7.2 / ¥36输入/输出
131
MAmistral-medium-2505
mistral-medium-2505Mistral
60.4
2K
262K
¥2.88 / ¥14.4输入/输出
132
Ogpt-4.1-2025-04-14
gpt-4.1-2025-04-14Openai
60.1
2.8K
1.05M
¥14.4 / ¥57.6输入/输出
133
Ogpt-5.4-nano-high
gpt-5.4-nano-highOpenai
59.8
1.9K
400K
¥1.44 / ¥9输入/输出
134
Ogpt-5-mini-high
gpt-5-mini-highOpenai
59.5
1.4K
400K
¥1.8 / ¥14.4输入/输出
135
IA
mercury-2
mercury-2Inception Ai
59.1
229
128K
¥1.8 / ¥5.4输入/输出
136
Ddeepseek-r1
deepseek-r1Deepseek
58.8
830
164K
¥5.04 / ¥18输入/输出
137
Aqwen3-32b
qwen3-32bAlibaba
58.5
212
131K
¥2.07 / ¥8.26输入/输出
138
Ggemini-2.0-flash-001
gemini-2.0-flash-001Google
58.2
2.3K
1.05M
¥1.08 / ¥4.32输入/输出
139
Mkimi-k2-0711-preview
kimi-k2-0711-previewMoonshot
57.9
1.7K
131K
¥4.32 / ¥18输入/输出
140
Mminimax-m2
minimax-m2Minimax
57.6
325
197K
¥0 / ¥0输入/输出
141
NVnvidia-llama-3.3-nemotron-super-49b-v1.5
nvidia-llama-3.3-nemotron-super-49b-v1.5Nvidia
57.3
197
131K
¥2.88 / ¥2.88输入/输出
142
Aclaude-opus-4-20250514
claude-opus-4-20250514Anthropic
57.0
2.6K
200K
¥108 / ¥540输入/输出
143
Xgrok-3-mini-beta
grok-3-mini-betaXai
56.7
1.4K
1M
¥9 / ¥18输入/输出
144
Aqwen3-235b-a22b
qwen3-235b-a22bAlibaba
56.4
1.5K
131K
¥2.07 / ¥8.26输入/输出
145
Oo4-mini-2025-04-16
o4-mini-2025-04-16Openai
56.1
2.5K
200K
¥7.92 / ¥31.7输入/输出
146
AG
ling-flash-2.0
ling-flash-2.0Ant Group
55.8
352
131K
¥1.01 / ¥4.1输入/输出
147
Mminimax-m2.5
minimax-m2.5Minimax
55.5
2.7K
205K
¥0 / ¥0输入/输出
148
UNtrinity-large-thinking
-
55.2
1.8K
262K
¥1.8 / ¥6.48输入/输出
149
STstep-3
step-3Stepfun
54.9
347
65.5K
¥1.8 / ¥4.68输入/输出
150
Mminimax-m1
minimax-m1Minimax
54.6
2.1K
1M
¥0.95 / ¥9.03输入/输出
151
Aclaude-opus-4-20250514-thinking-16k
claude-opus-4-20250514-thinking-16kAnthropic
54.3
2.2K
200K
¥108 / ¥540输入/输出
152
Oo1-2024-12-17
o1-2024-12-17Openai
54.0
1.3K
128K
¥108 / ¥432输入/输出
153
STstep-2-16k-exp-202412
step-2-16k-exp-202412Stepfun
53.7
265
16.4K
¥37.5 / ¥118输入/输出
154
NVnvidia-nemotron-3-nano-30b-a3b-bf16
nvidia-nemotron-3-nano-30b-a3b-bf16Nvidia
53.4
981
131K
¥0 / ¥0输入/输出
155
Aqwen-plus-0125
qwen-plus-0125Alibaba
53.0
315
1M
¥0.83 / ¥2.07输入/输出
156
UNtrinity-large-preview
-
52.7
2.1K
262K
¥1.8 / ¥6.48输入/输出
157
Zglm-4.5v
glm-4.5vZai
52.4
238
64K
¥4.32 / ¥13输入/输出
158
STstep-1o-turbo-202506
step-1o-turbo-202506Stepfun
52.1
605
-
-
159
Zglm-4.7-flash
glm-4.7-flashZai
51.8
804
200K
¥0 / ¥0输入/输出
160
Aqwen3-coder-480b-a35b-instruct
qwen3-coder-480b-a35b-instructAlibaba
51.5
1.5K
262K
¥6.2 / ¥24.8输入/输出
161
Ggemini-2.0-flash-lite-preview-02-05
gemini-2.0-flash-lite-preview-02-05Google
51.2
1.1K
1.05M
¥0.54 / ¥2.16输入/输出
162
MAmistral-small-2506
mistral-small-2506Mistral
50.9
1.1K
262K
¥2.88 / ¥14.4输入/输出
163
Ddeepseek-v3
deepseek-v3Deepseek
50.6
1.1K
128K
¥0 / ¥0输入/输出
164
Ggemma-3-4b-it
gemma-3-4b-itGoogle
50.3
197
128K
¥1.44 / ¥1.44输入/输出
165
Aqwq-32b
qwq-32bAlibaba
50.0
1.4K
131K
¥2.07 / ¥6.2输入/输出
166
TEhunyuan-large-2025-02-10
hunyuan-large-2025-02-10Tencent
49.7
212
-
-
167
Ggemma-3-12b-it
gemma-3-12b-itGoogle
49.4
155
128K
¥1.96 / ¥1.96输入/输出
168
CO
command-a-03-2025
command-a-03-2025Cohere
49.1
3.1K
256K
¥18 / ¥72输入/输出
169
AGring-flash-2.0
ring-flash-2.0Ant Group
48.8
384
131K
¥1.01 / ¥4.1输入/输出
170
Ogpt-5-nano-high
gpt-5-nano-highOpenai
48.5
480
400K
¥0.36 / ¥2.88输入/输出
171
Aclaude-sonnet-4-20250514
claude-sonnet-4-20250514Anthropic
48.2
2.4K
200K
¥21.6 / ¥108输入/输出
172
Oo3-mini-high
o3-mini-highOpenai
47.9
824
200K
¥7.92 / ¥31.7输入/输出
173
UNintellect-3
-
47.6
315
131K
¥1.44 / ¥7.92输入/输出
174
Ogpt-4.1-mini-2025-04-14
gpt-4.1-mini-2025-04-14Openai
47.3
2.3K
1.05M
¥2.88 / ¥11.5输入/输出
175
Aclaude-sonnet-4-20250514-thinking-32k
claude-sonnet-4-20250514-thinking-32kAnthropic
47.0
2.2K
200K
¥21.6 / ¥108输入/输出
176
Ggemma-3n-e4b-it
gemma-3n-e4b-itGoogle
46.6
1.3K
128K
¥0 / ¥0输入/输出
177
Aqwen3-30b-a3b
qwen3-30b-a3bAlibaba
46.3
1.6K
128K
¥0.79 / ¥7.78输入/输出
178
Ogpt-oss-20b
gpt-oss-20bOpenai
46.0
561
131K
¥0.32 / ¥1.3输入/输出
179
AI
olmo-3-32b-think
olmo-3-32b-thinkAllenai
45.7
315
128K
¥2.16 / ¥3.24输入/输出
180
TEhunyuan-standard-2025-02-10
hunyuan-standard-2025-02-10Tencent
45.4
247
-
-
181
IB
granite-4.1-8b
granite-4.1-8bIbm
45.1
280
131K
¥0.36 / ¥0.72输入/输出
182
Oo1-preview
o1-previewOpenai
44.8
1.7K
128K
¥108 / ¥432输入/输出
183
Xgrok-2-2024-08-13
grok-2-2024-08-13Xai
44.5
3.2K
1M
¥9 / ¥18输入/输出
184
UNyi-lightning
-
44.2
1.5K
12K
¥1.44 / ¥1.44输入/输出
185
Ggemini-1.5-pro-002
gemini-1.5-pro-002Google
43.9
2.7K
-
-
186
Aqwen2.5-plus-1127
qwen2.5-plus-1127Alibaba
43.6
474
-
-
187
NVllama-3.1-nemotron-70b-instruct
llama-3.1-nemotron-70b-instructNvidia
43.3
392
128K
¥0 / ¥0输入/输出
188
Oo3-mini
o3-miniOpenai
43.0
3K
200K
¥7.92 / ¥31.7输入/输出
189
Xgrok-2-mini-2024-08-13
grok-2-mini-2024-08-13Xai
42.7
2.6K
1M
¥9 / ¥18输入/输出
190
Oo1-mini
o1-miniOpenai
42.4
2.6K
128K
¥7.92 / ¥31.7输入/输出
191
UNathene-v2-chat
-
42.1
1.2K
-
-
192
Ddeepseek-v2.5-1210
deepseek-v2.5-1210Deepseek
41.8
291
1M
¥1.01 / ¥2.02输入/输出
193
Ggemini-1.5-flash-002
gemini-1.5-flash-002Google
41.5
1.7K
2M
¥0.54 / ¥2.2输入/输出
194
Zglm-4-plus
glm-4-plusZai
41.2
1.5K
128K
¥54 / ¥54输入/输出
195
AIolmo-3.1-32b-instruct
olmo-3.1-32b-instructAllenai
40.9
805
200K
¥14.4 / ¥57.6输入/输出
196
Aclaude-3-7-sonnet-20250219-thinking-32k
claude-3-7-sonnet-20250219-thinking-32kAnthropic
40.5
2.3K
-
-
197
Mllama-3.1-405b-instruct-bf16
llama-3.1-405b-instruct-bf16Meta
40.2
1.9K
128K
¥0 / ¥0输入/输出
198
Ogpt-4o-mini-2024-07-18
gpt-4o-mini-2024-07-18Openai
39.9
3.4K
128K
¥1.08 / ¥4.32输入/输出
199
UNreka-core-20240904
-
39.6
364
-
-
200
Ogpt-4o-2024-05-13
gpt-4o-2024-05-13Openai
39.3
6K
128K
¥36 / ¥108输入/输出
201
Mllama-4-maverick-17b-128e-instruct
llama-4-maverick-17b-128e-instructMeta
39.0
2.3K
1M
¥1.8 / ¥6.26输入/输出
202
Ogpt-4.1-nano-2025-04-14
gpt-4.1-nano-2025-04-14Openai
38.7
302
1.05M
¥14.4 / ¥57.6输入/输出
203
Mllama-4-scout-17b-16e-instruct
llama-4-scout-17b-16e-instructMeta
38.4
1.8K
128K
¥1.44 / ¥5.62输入/输出
204
Mllama-3.3-70b-instruct
llama-3.3-70b-instructMeta
38.1
2.7K
128K
¥0 / ¥0输入/输出
205
UNathene-70b-0725
-
37.8
1K
-
-
206
Mllama-3.1-405b-instruct-fp8
llama-3.1-405b-instruct-fp8Meta
37.5
3.1K
128K
¥0 / ¥0输入/输出
207
MAmistral-small-3.1-24b-instruct-2503
mistral-small-3.1-24b-instruct-2503Mistral
37.2
2K
262K
¥2.88 / ¥14.4输入/输出
208
AIolmo-3.1-32b-think
olmo-3.1-32b-thinkAllenai
36.9
595
200K
¥14.4 / ¥57.6输入/输出
209
Aamazon-nova-pro-v1.0
amazon-nova-pro-v1.0Amazon
36.6
1.1K
300K
¥5.76 / ¥23输入/输出
210
Aclaude-3-7-sonnet-20250219
claude-3-7-sonnet-20250219Anthropic
36.3
2.3K
200K
¥21.6 / ¥108输入/输出
211
Ddeepseek-v2.5
deepseek-v2.5Deepseek
36.0
1.2K
1M
¥1.01 / ¥2.02输入/输出
212
Aqwen-max-0919
qwen-max-0919Alibaba
35.7
933
131K
¥2.48 / ¥9.91输入/输出
213
Aqwen2.5-72b-instruct
qwen2.5-72b-instructAlibaba
35.4
2K
131K
¥4.13 / ¥12.4输入/输出
214
Mllama-3.1-70b-instruct
llama-3.1-70b-instructMeta
35.1
2.8K
131K
¥2.88 / ¥2.88输入/输出
215
Aclaude-3-5-sonnet-20241022
claude-3-5-sonnet-20241022Anthropic
34.8
4.6K
200K
¥21.6 / ¥108输入/输出
216
MAmistral-large-2411
mistral-large-2411Mistral
34.5
1.2K
128K
¥14.4 / ¥43.2输入/输出
217
Ogpt-4o-2024-08-06
gpt-4o-2024-08-06Openai
34.1
2.2K
128K
¥18 / ¥72输入/输出
218
Ggemini-advanced-0514
gemini-advanced-0514Google
33.8
2.7K
-
-
219
MAmagistral-medium-2506
magistral-medium-2506Mistral
33.5
781
128K
¥14.4 / ¥36输入/输出
220
MAmistral-large-2407
mistral-large-2407Mistral
33.2
2.4K
131K
¥14.4 / ¥43.2输入/输出
221
Aclaude-3-5-sonnet-20240620
claude-3-5-sonnet-20240620Anthropic
32.9
4.5K
200K
¥21.6 / ¥108输入/输出
222
Ogpt-4-turbo-2024-04-09
gpt-4-turbo-2024-04-09Openai
32.6
5K
128K
¥72 / ¥216输入/输出
223
COcommand-r-plus-08-2024
command-r-plus-08-2024Cohere
32.3
547
128K
¥18 / ¥72输入/输出
224
Ogpt-4-0125-preview
gpt-4-0125-previewOpenai
32.0
5.2K
8.19K
¥216 / ¥432输入/输出
225
Aclaude-3-opus-20240229
claude-3-opus-20240229Anthropic
31.7
10.3K
200K
¥108 / ¥540输入/输出
226
TEhunyuan-large-vision
hunyuan-large-visionTencent
31.4
366
-
-
227
Aclaude-3-5-haiku-20241022
claude-3-5-haiku-20241022Anthropic
31.1
3.7K
200K
¥5.76 / ¥28.8输入/输出
228
Ogpt-4-1106-preview
gpt-4-1106-previewOpenai
30.8
5.5K
8.19K
¥216 / ¥432输入/输出
229
COc4ai-aya-expanse-32b
c4ai-aya-expanse-32bCohere
30.5
1.4K
-
-
230
UNgemma-2-9b-it-simpo
-
30.2
516
8.19K
¥1.44 / ¥1.44输入/输出
231
IBibm-granite-h-small
ibm-granite-h-smallIbm
29.9
254
-
-
232
MAmistral-small-24b-instruct-2501
mistral-small-24b-instruct-2501Mistral
29.6
654
262K
¥2.88 / ¥14.4输入/输出
233
Mllama-3-70b-instruct
llama-3-70b-instructMeta
29.3
8.3K
8.19K
¥3.67 / ¥5.33输入/输出
234
Ggemini-1.5-flash-8b-001
gemini-1.5-flash-8b-001Google
29.0
1.8K
2M
¥0.54 / ¥2.2输入/输出
235
Aamazon-nova-lite-v1.0
amazon-nova-lite-v1.0Amazon
28.7
872
300K
¥0.43 / ¥1.73输入/输出
236
Ggemini-1.5-pro-001
gemini-1.5-pro-001Google
28.4
4.4K
-
-
237
COcommand-r-08-2024
command-r-08-2024Cohere
28.0
500
128K
¥18 / ¥72输入/输出
238
Aamazon-nova-micro-v1.0
amazon-nova-micro-v1.0Amazon
27.7
952
128K
¥0.25 / ¥1.01输入/输出
239
COcommand-r-plus
command-r-plusCohere
27.4
4.2K
128K
¥18 / ¥72输入/输出
240
Zglm-4-0520
glm-4-0520Zai
27.1
554
128K
¥108 / ¥108输入/输出
241
COc4ai-aya-expanse-8b
c4ai-aya-expanse-8bCohere
26.8
470
-
-
242
M
phi-4
phi-4Microsoft
26.5
1K
128K
¥0.9 / ¥3.6输入/输出
243
UNreka-flash-20240904
-
26.2
390
65.5K
¥0.72 / ¥1.44输入/输出
244
Ggemma-2-27b-it
gemma-2-27b-itGoogle
25.9
3.9K
8.19K
¥0.58 / ¥0.58输入/输出
245
UNjamba-1.5-large
-
25.6
474
256K
¥0 / ¥0输入/输出
246
NVnemotron-4-340b-instruct
nemotron-4-340b-instructNvidia
25.3
1.1K
-
-
247
Aclaude-3-sonnet-20240229
claude-3-sonnet-20240229Anthropic
25.0
5.9K
200K
¥21.6 / ¥108输入/输出
248
NVllama-3.1-nemotron-51b-instruct
llama-3.1-nemotron-51b-instructNvidia
24.7
213
128K
¥0 / ¥0输入/输出
249
Aqwen2.5-coder-32b-instruct
qwen2.5-coder-32b-instructAlibaba
24.4
221
131K
¥2.07 / ¥6.2输入/输出
250
Ggemini-1.5-flash-001
gemini-1.5-flash-001Google
24.1
3.5K
2M
¥0.54 / ¥2.2输入/输出
251
AIolmo-2-0325-32b-instruct
olmo-2-0325-32b-instructAllenai
23.8
204
-
-
252
Mllama-3.1-8b-instruct
llama-3.1-8b-instructMeta
23.5
2.6K
131K
¥0.79 / ¥0.79输入/输出
253
UNjamba-1.5-mini
-
23.2
486
256K
¥0 / ¥0输入/输出
254
MAministral-8b-2410
ministral-8b-2410Mistral
22.9
280
128K
¥0.72 / ¥0.72输入/输出
255
Aqwen2-72b-instruct
qwen2-72b-instructAlibaba
22.6
2.1K
131K
¥4.13 / ¥12.4输入/输出
256
Ggemma-2-9b-it
gemma-2-9b-itGoogle
22.3
2.8K
8.19K
¥1.44 / ¥1.44输入/输出
257
Aclaude-3-haiku-20240307
claude-3-haiku-20240307Anthropic
22.0
6.4K
200K
¥1.8 / ¥9输入/输出
258
UNyi-1.5-34b-chat
-
21.6
1.3K
-
-
259
COcommand-r
command-rCohere
21.3
2.9K
128K
¥18 / ¥72输入/输出
260
UNinternlm2_5-20b-chat
-
21.0
548
-
-
261
Mllama-3-8b-instruct
llama-3-8b-instructMeta
20.7
5.4K
8.19K
¥0.29 / ¥0.29输入/输出
262
UNreka-flash-21b-20240226
-
20.4
1.3K
-
-
263
Aqwen1.5-110b-chat
qwen1.5-110b-chatAlibaba
20.1
1.4K
-
-
264
Ogpt-4-0314
gpt-4-0314Openai
19.8
2.9K
8.19K
¥216 / ¥432输入/输出
265
Ggemma-2-2b-it
gemma-2-2b-itGoogle
19.5
2.3K
128K
¥0 / ¥0输入/输出
266
UNreka-flash-21b-20240226-online
-
19.2
818
-
-
267
Aqwen1.5-72b-chat
qwen1.5-72b-chatAlibaba
18.9
2.4K
-
-
268
Ggemini-pro-dev-api
gemini-pro-dev-apiGoogle
18.6
1.1K
1.05M
¥14.4 / ¥86.4输入/输出
269
Ddeepseek-coder-v2
deepseek-coder-v2Deepseek
18.3
847
1M
¥1.01 / ¥2.02输入/输出
270
MAmistral-large-2402
mistral-large-2402Mistral
18.0
3.4K
262K
¥2.88 / ¥14.4输入/输出
271
MAmistral-medium
mistral-mediumMistral
17.7
1.9K
262K
¥2.88 / ¥14.4输入/输出
272
UNstarling-lm-7b-beta
-
17.4
853
200K
¥5.4 / ¥18.7输入/输出
273
Ogpt-4-0613
gpt-4-0613Openai
17.1
4.8K
8.19K
¥216 / ¥432输入/输出
274
MAmixtral-8x22b-instruct-v0.1
mixtral-8x22b-instruct-v0.1Mistral
16.8
2.8K
64K
¥14.4 / ¥43.2输入/输出
275
Mphi-3-medium-4k-instruct
phi-3-medium-4k-instructMicrosoft
16.5
1.3K
4.1K
¥1.22 / ¥4.9输入/输出
276
Ggemini-pro
gemini-proGoogle
16.2
262
1.05M
¥14.4 / ¥86.4输入/输出
277
UNstarling-lm-7b-alpha
-
15.9
568
200K
¥5.4 / ¥18.7输入/输出
278
Aqwen1.5-32b-chat
qwen1.5-32b-chatAlibaba
15.5
1.2K
-
-
279
UNzephyr-orpo-141b-A35b-v0.1
-
15.2
284
200K
¥108 / ¥432输入/输出
280
Aqwen1.5-14b-chat
qwen1.5-14b-chatAlibaba
14.9
939
-
-
281
Mllama-3.2-3b-instruct
llama-3.2-3b-instructMeta
14.6
441
131K
¥0.22 / ¥0.35输入/输出
282
UNyi-34b-chat
-
14.3
824
-
-
283
Mphi-3-small-8k-instruct
phi-3-small-8k-instructMicrosoft
14.0
977
8.19K
¥1.08 / ¥4.32输入/输出
284
Mwizardlm-70b
wizardlm-70bMicrosoft
13.7
385
-
-
285
MAmixtral-8x7b-instruct-v0.1
mixtral-8x7b-instruct-v0.1Mistral
13.4
4.1K
32K
¥5.04 / ¥5.04输入/输出
286
Mllama-2-70b-chat
llama-2-70b-chatMeta
13.1
2.2K
-
-
287
Ogpt-3.5-turbo-0125
gpt-3.5-turbo-0125Openai
12.8
3.8K
16.4K
¥3.6 / ¥10.8输入/输出
288
UNopenchat-3.5-0106
-
12.5
743
-
-
289
Ggemma-1.1-7b-it
gemma-1.1-7b-itGoogle
12.2
1.3K
-
-
290
Mllama-2-13b-chat
llama-2-13b-chatMeta
11.9
970
-
-
291
MAmistral-7b-instruct-v0.2
mistral-7b-instruct-v0.2Mistral
11.6
1.1K
262K
¥2.88 / ¥14.4输入/输出
292
UNdbrx-instruct-preview
-
11.3
1.7K
-
-
293
UNopenchat-3.5
-
11.0
426
-
-
294
Mwizardlm-13b
wizardlm-13bMicrosoft
10.7
323
-
-
295
UNsnowflake-arctic-instruct
-
10.4
1.6K
-
-
296
Ddeepseek-llm-67b-chat
deepseek-llm-67b-chatDeepseek
10.1
385
1M
¥1.01 / ¥2.02输入/输出
297
UNvicuna-33b
-
9.8
1.2K
-
-
298
UNtulu-2-dpo-70b
-
9.5
348
-
-
299
IBgranite-3.0-8b-instruct
granite-3.0-8b-instructIbm
9.1
356
-
-
300
UNnous-hermes-2-mixtral-8x7b-dpo
-
8.8
266
1M
¥36 / ¥180输入/输出
301
Aqwen1.5-7b-chat
qwen1.5-7b-chatAlibaba
8.5
266
-
-
302
UNopenhermes-2.5-mistral-7b
-
8.2
285
1M
¥36 / ¥180输入/输出
303
UNsolar-10.7b-instruct-v1.0
-
7.9
210
128K
¥0 / ¥0输入/输出
304
Mphi-3-mini-4k-instruct-june-2024
phi-3-mini-4k-instruct-june-2024Microsoft
7.6
653
4.1K
¥0.94 / ¥3.74输入/输出
305
Mllama-2-7b-chat
llama-2-7b-chatMeta
7.3
764
128K
¥4.03 / ¥48输入/输出
306
AIolmo-7b-instruct
olmo-7b-instructAllenai
7.0
339
-
-
307
Mphi-3-mini-4k-instruct
phi-3-mini-4k-instructMicrosoft
6.7
1.1K
4.1K
¥0.94 / ¥3.74输入/输出
308
Ggemma-7b-it
gemma-7b-itGoogle
6.4
538
-
-
309
UNzephyr-7b-beta
-
6.1
580
-
-
310
Mcodellama-34b-instruct
codellama-34b-instructMeta
5.8
340
-
-
311
UNvicuna-13b
-
5.5
884
-
-
312
Mllama-3.2-1b-instruct
llama-3.2-1b-instructMeta
5.2
445
16.4K
¥0.07 / ¥0.08输入/输出
313
Aqwen-14b-chat
qwen-14b-chatAlibaba
4.9
268
32.8K
¥1.04 / ¥3.1输入/输出
314
Ogpt-3.5-turbo-1106
gpt-3.5-turbo-1106Openai
4.6
906
16.4K
¥7.2 / ¥14.4输入/输出
315
IBgranite-3.0-2b-instruct
granite-3.0-2b-instructIbm
4.3
380
-
-
316
UNvicuna-7b
-
4.0
291
-
-
317
Mphi-3-mini-128k-instruct
phi-3-mini-128k-instructMicrosoft
3.7
1.1K
128K
¥0.94 / ¥3.74输入/输出
318
MAmistral-7b-instruct
mistral-7b-instructMistral
3.4
477
262K
¥2.88 / ¥14.4输入/输出
319
Ggemma-1.1-2b-it
gemma-1.1-2b-itGoogle
3.0
628
-
-
320
UNstripedhyena-nous-7b
-
2.7
327
-
-
321
Gpalm-2
palm-2Google
2.4
303
-
-
322
UNkoala-13b
-
2.1
253
-
-
323
Aqwen1.5-4b-chat
qwen1.5-4b-chatAlibaba
1.8
433
-
-
324
UNRWKV-4-Raven-14B
-
1.5
177
-
-
325
Ggemma-2b-it
gemma-2b-itGoogle
1.2
292
-
-
326
UNchatglm3-6b
-
0.9
253
200K
¥5.4 / ¥18.7输入/输出
327
UNchatglm-6b
-
0.6
193
200K
¥5.4 / ¥18.7输入/输出
328
UNalpaca-13b
-
0.3
212
-
-
329
UNoasst-pythia-12b
-
0.0
201
-
-
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 2.6K。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
医疗健康常见问题
医疗健康排行榜看什么指标？
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。
医疗健康模型应该怎么选？
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。