1
G
gemini-3.5-flash
gemini-3.5-flashGoogle
100.0
903
1.05M
¥10.8 / ¥64.8输入/输出
对话 · 文本 · 俄语排行榜
基于公开偏好评测数据展示 文本 / 俄语 榜单，每个榜单独立排序。
俄语模型怎么选？
俄语排行榜用于回答“俄语哪个 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 gemini-3.5-flash，厂商为 google，百分制分数 100.0，样本量 903。 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。
gemini-3.5-flashclaude-opus-4-6gemini-3.1-pro-previewgemini-3-proclaude-opus-4-6-thinking
2
A
claude-opus-4-6
claude-opus-4-6Anthropic
99.7
4K
1M
¥36 / ¥180输入/输出
3
Ggemini-3.1-pro-preview
gemini-3.1-pro-previewGoogle
99.4
4.7K
1.05M
¥14.4 / ¥86.4输入/输出
4
Ggemini-3-pro
gemini-3-proGoogle
99.1
4K
1.05M
¥14.4 / ¥86.4输入/输出
5
Aclaude-opus-4-6-thinking
claude-opus-4-6-thinkingAnthropic
98.8
3.7K
1M
¥36 / ¥180输入/输出
6
Aclaude-opus-4-7-thinking
claude-opus-4-7-thinkingAnthropic
98.4
2K
1M
¥36 / ¥180输入/输出
7
O
gpt-5.4-high
gpt-5.4-highOpenai
98.1
3.2K
1.05M
¥18 / ¥108输入/输出
8
Aclaude-opus-4-7
claude-opus-4-7Anthropic
97.8
2.2K
1M
¥36 / ¥180输入/输出
9
A
qwen3.7-max-preview
qwen3.7-max-previewAlibaba
97.5
381
1M
¥18 / ¥54输入/输出
10
Ggemini-3-flash
gemini-3-flashGoogle
97.2
3.3K
1.05M
¥3.6 / ¥21.6输入/输出
11
Ogpt-5.5-high
gpt-5.5-highOpenai
96.9
1.8K
1.05M
¥36 / ¥216输入/输出
12
Aqwen3.5-max-preview
qwen3.5-max-previewAlibaba
96.6
2.1K
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-
13
Ogpt-5.5
gpt-5.5Openai
96.3
1.7K
1.05M
¥36 / ¥216输入/输出
14
M
muse-spark
muse-sparkMeta
96.0
1.3K
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-
15
X
grok-4.20-beta-0309-reasoning
grok-4.20-beta-0309-reasoningXai
95.7
3.2K
2M
¥14.4 / ¥43.2输入/输出
16
B
ernie-5.1
ernie-5.1Baidu
95.3
1.6K
119K
¥5.4 / ¥21.6输入/输出
17
Ogpt-5.4
gpt-5.4Openai
95.0
3.3K
1.05M
¥18 / ¥108输入/输出
18
Ggemma-4-31b
gemma-4-31bGoogle
94.7
646
262K
¥3.24 / ¥7.2输入/输出
19
Ggemini-2.5-pro
gemini-2.5-proGoogle
94.4
9.8K
1.05M
¥9 / ¥72输入/输出
20
Z
glm-5.1
glm-5.1Zai
94.1
1.6K
200K
¥0 / ¥0输入/输出
21
Xgrok-4.20-multi-agent-beta-0309
grok-4.20-multi-agent-beta-0309Xai
93.8
3.2K
2M
¥14.4 / ¥43.2输入/输出
22
Ggemini-3-flash (thinking-minimal)
gemini-3-flash (thinking-minimal)Google
93.5
5.8K
1.05M
¥3.6 / ¥21.6输入/输出
23
MI
mimo-v2.5-pro
mimo-v2.5-proXiaomi
93.2
1.8K
1.05M
¥7.2 / ¥21.6输入/输出
24
B
dola-seed-2.0-pro
dola-seed-2.0-proBytedance
92.9
4.2K
-
-
25
Xgrok-4.20-beta1
grok-4.20-beta1Xai
92.5
2.6K
2M
¥14.4 / ¥43.2输入/输出
26
Aclaude-opus-4-5-20251101
claude-opus-4-5-20251101Anthropic
92.2
7K
200K
¥36 / ¥180输入/输出
27
Bernie-5.0-0110
ernie-5.0-0110Baidu
91.9
3.8K
128K
¥7.92 / ¥14.4输入/输出
28
D
deepseek-v4-pro-thinking
deepseek-v4-pro-thinkingDeepseek
91.6
1.8K
1M
¥3.13 / ¥6.26输入/输出
29
Aqwen3.6-max-preview
qwen3.6-max-previewAlibaba
91.3
472
246K
¥9.5 / ¥56.9输入/输出
30
M
kimi-k2.6
kimi-k2.6Moonshot
91.0
1.8K
262K
¥6.84 / ¥28.8输入/输出
31
Ggemma-4-26b-a4b
gemma-4-26b-a4bGoogle
90.7
679
262K
¥0.94 / ¥2.88输入/输出
32
Ddeepseek-v4-pro
deepseek-v4-proDeepseek
90.4
1.9K
1M
¥3.13 / ¥6.26输入/输出
33
Ogpt-5.2-chat-latest-20260210
gpt-5.2-chat-latest-20260210Openai
90.1
3.5K
400K
¥12.6 / ¥101输入/输出
34
Bernie-5.0-preview-1203
ernie-5.0-preview-1203Baidu
89.8
956
128K
¥7.92 / ¥14.4输入/输出
35
Ogpt-5.1-high
gpt-5.1-highOpenai
89.4
4.1K
400K
¥9 / ¥72输入/输出
36
Zglm-5
glm-5Zai
89.1
2.3K
205K
¥7.2 / ¥23输入/输出
37
Aclaude-opus-4-5-20251101-thinking-32k
claude-opus-4-5-20251101-thinking-32kAnthropic
88.8
3.9K
200K
¥108 / ¥540输入/输出
38
Aclaude-sonnet-4-6
claude-sonnet-4-6Anthropic
88.5
3K
1M
¥21.6 / ¥108输入/输出
39
Ddeepseek-v3.1-terminus-thinking
deepseek-v3.1-terminus-thinkingDeepseek
88.2
236
128K
¥1.8 / ¥5.04输入/输出
40
Aclaude-sonnet-4-5-20250929
claude-sonnet-4-5-20250929Anthropic
87.9
7.3K
200K
¥21.6 / ¥108输入/输出
41
Xgrok-4.1-thinking
grok-4.1-thinkingXai
87.6
6.5K
200K
¥14.4 / ¥72输入/输出
42
Aqwen3.5-397b-a17b
qwen3.5-397b-a17bAlibaba
87.3
3.4K
262K
¥3.1 / ¥18.6输入/输出
43
Aqwen3.6-plus
qwen3.6-plusAlibaba
87.0
2K
1M
¥3.6 / ¥21.6输入/输出
44
Mkimi-k2.5-thinking
kimi-k2.5-thinkingMoonshot
86.6
4.2K
262K
¥4.32 / ¥21.6输入/输出
45
Ogpt-5.5-instant
gpt-5.5-instantOpenai
86.3
2.7K
400K
¥9 / ¥72输入/输出
46
Ochatgpt-4o-latest-20250326
chatgpt-4o-latest-20250326Openai
86.0
6.4K
128K
¥18 / ¥72输入/输出
47
Xgrok-4.1
grok-4.1Xai
85.7
6.3K
200K
¥14.4 / ¥72输入/输出
48
Zglm-4.7
glm-4.7Zai
85.4
1.4K
205K
¥0 / ¥0输入/输出
49
MImimo-v2-pro
mimo-v2-proXiaomi
85.1
2.6K
1.05M
¥7.2 / ¥21.6输入/输出
50
Ddeepseek-v4-flash-thinking
deepseek-v4-flash-thinkingDeepseek
84.8
1.9K
1M
¥1.01 / ¥2.02输入/输出
51
Ddeepseek-v3.1-terminus
deepseek-v3.1-terminusDeepseek
84.5
261
128K
¥1.8 / ¥5.04输入/输出
52
Ogpt-5.1
gpt-5.1Openai
84.2
4.3K
400K
¥9 / ¥72输入/输出
53
Ddeepseek-v4-flash
deepseek-v4-flashDeepseek
83.9
1.9K
1M
¥1.01 / ¥2.02输入/输出
54
Ddeepseek-r1-0528
deepseek-r1-0528Deepseek
83.5
1.3K
164K
¥3.6 / ¥15.5输入/输出
55
Xgrok-4.3
grok-4.3Xai
83.2
1.7K
1M
¥9 / ¥18输入/输出
56
Aclaude-sonnet-4-5-20250929-thinking-32k
claude-sonnet-4-5-20250929-thinking-32kAnthropic
82.9
7.4K
200K
¥21.6 / ¥108输入/输出
57
Ddeepseek-v3.2
deepseek-v3.2Deepseek
82.6
4.8K
128K
¥2.09 / ¥3.1输入/输出
58
A
amazon-nova-experimental-chat-26-02-10
amazon-nova-experimental-chat-26-02-10Amazon
82.3
379
-
-
59
Aclaude-opus-4-1-20250805
claude-opus-4-1-20250805Anthropic
82.0
5.7K
200K
¥108 / ¥540输入/输出
60
Ogpt-5.4-mini-high
gpt-5.4-mini-highOpenai
81.7
2.8K
400K
¥5.4 / ¥32.4输入/输出
61
Aqwen3-max-preview
qwen3-max-previewAlibaba
81.4
1.4K
262K
¥6.2 / ¥24.8输入/输出
62
Ogpt-5.2
gpt-5.2Openai
81.1
5K
400K
¥12.6 / ¥101输入/输出
63
Zglm-4.6
glm-4.6Zai
80.7
2.8K
205K
¥4.32 / ¥15.8输入/输出
64
Aqwen3-max-2025-09-23
qwen3-max-2025-09-23Alibaba
80.4
573
258K
¥6.19 / ¥24.7输入/输出
65
Ogpt-4.5-preview-2025-02-27
gpt-4.5-preview-2025-02-27Openai
80.1
1.4K
8.19K
¥216 / ¥432输入/输出
66
Ggemini-2.5-flash
gemini-2.5-flashGoogle
79.8
10K
1.05M
¥2.16 / ¥18输入/输出
67
Ggemini-3.1-flash-lite-preview
gemini-3.1-flash-lite-previewGoogle
79.5
3.9K
1.05M
¥1.8 / ¥10.8输入/输出
68
Xgrok-3-preview-02-24
grok-3-preview-02-24Xai
79.2
2.5K
1M
¥9 / ¥18输入/输出
69
Zglm-4.5
glm-4.5Zai
78.9
1.3K
131K
¥4.32 / ¥15.8输入/输出
70
MA
mistral-medium-2508
mistral-medium-2508Mistral
78.6
7.7K
262K
¥2.88 / ¥14.4输入/输出
71
Xgrok-4-0709
grok-4-0709Xai
78.3
2.2K
256K
¥21.6 / ¥108输入/输出
72
Aclaude-opus-4-1-20250805-thinking-16k
claude-opus-4-1-20250805-thinking-16kAnthropic
78.0
3.3K
200K
¥108 / ¥540输入/输出
73
Aqwen3-235b-a22b-instruct-2507
qwen3-235b-a22b-instruct-2507Alibaba
77.6
8.3K
128K
¥2.09 / ¥8.23输入/输出
74
Ogpt-5.2-high
gpt-5.2-highOpenai
77.3
5.2K
400K
¥12.6 / ¥101输入/输出
75
MImimo-v2-omni
mimo-v2-omniXiaomi
77.0
360
262K
¥2.88 / ¥14.4输入/输出
76
MAmistral-large-3
mistral-large-3Mistral
76.7
4.3K
262K
¥3.6 / ¥10.8输入/输出
77
Aamazon-nova-experimental-chat-12-10
amazon-nova-experimental-chat-12-10Amazon
76.4
382
-
-
78
Oo3-2025-04-16
o3-2025-04-16Openai
76.1
3.8K
200K
¥14.4 / ¥57.6输入/输出
79
TE
hunyuan-hy3-preview
hunyuan-hy3-previewTencent
75.8
562
256K
¥0 / ¥0输入/输出
80
Ddeepseek-v3.2-exp
deepseek-v3.2-expDeepseek
75.5
845
128K
¥0 / ¥0输入/输出
81
Mkimi-k2.5-instant
kimi-k2.5-instantMoonshot
75.2
865
262K
¥4.32 / ¥21.6输入/输出
82
Ddeepseek-v3.2-exp-thinking
deepseek-v3.2-exp-thinkingDeepseek
74.8
503
128K
¥0 / ¥0输入/输出
83
Ogpt-5-chat
gpt-5-chatOpenai
74.5
1.6K
400K
¥9 / ¥72输入/输出
84
Aqwen3-vl-235b-a22b-instruct
qwen3-vl-235b-a22b-instructAlibaba
74.2
717
128K
¥2.16 / ¥8.64输入/输出
85
Ddeepseek-v3.1-thinking
deepseek-v3.1-thinkingDeepseek
73.9
604
128K
¥1.44 / ¥5.04输入/输出
86
Ddeepseek-v3.1
deepseek-v3.1Deepseek
73.6
790
128K
¥1.44 / ¥5.04输入/输出
87
Ddeepseek-v3.2-thinking
deepseek-v3.2-thinkingDeepseek
73.3
4.4K
128K
¥2.09 / ¥3.1输入/输出
88
Aqwen3-next-80b-a3b-instruct
qwen3-next-80b-a3b-instructAlibaba
73.0
1.2K
131K
¥1.04 / ¥4.13输入/输出
89
Ogpt-5-high
gpt-5-highOpenai
72.7
1.7K
400K
¥9 / ¥72输入/输出
90
Ogpt-5.3-chat-latest
gpt-5.3-chat-latestOpenai
72.4
3.3K
128K
¥12.6 / ¥101输入/输出
91
Bernie-5.0-preview-1022
ernie-5.0-preview-1022Baidu
72.0
259
128K
¥7.92 / ¥14.4输入/输出
92
Aqwen3-235b-a22b-thinking-2507
qwen3-235b-a22b-thinking-2507Alibaba
71.7
438
131K
¥2.07 / ¥8.26输入/输出
93
Ggemini-2.5-flash-preview-09-2025
gemini-2.5-flash-preview-09-2025Google
71.4
2.3K
1M
¥2.16 / ¥18输入/输出
94
Aamazon-nova-experimental-chat-11-10
amazon-nova-experimental-chat-11-10Amazon
71.1
2.7K
-
-
95
MImimo-v2.5
mimo-v2.5Xiaomi
70.8
1.8K
1.05M
¥2.88 / ¥14.4输入/输出
96
Aamazon-nova-experimental-chat-26-01-10
amazon-nova-experimental-chat-26-01-10Amazon
70.5
342
-
-
97
Aqwen3.5-122b-a10b
qwen3.5-122b-a10bAlibaba
70.2
2.8K
262K
¥2.88 / ¥23输入/输出
98
Aqwen3-235b-a22b-no-thinking
qwen3-235b-a22b-no-thinkingAlibaba
69.9
2.4K
131K
¥2.07 / ¥8.26输入/输出
99
Xgrok-4-fast-reasoning
grok-4-fast-reasoningXai
69.6
1K
2M
¥1.44 / ¥3.6输入/输出
100
Mkimi-k2-thinking-turbo
kimi-k2-thinking-turboMoonshot
69.3
6.1K
262K
¥17.3 / ¥72输入/输出
101
Aclaude-opus-4-20250514-thinking-16k
claude-opus-4-20250514-thinking-16kAnthropic
68.9
2.1K
200K
¥108 / ¥540输入/输出
102
Aqwen3.5-27b
qwen3.5-27bAlibaba
68.6
2.7K
262K
¥2.16 / ¥17.3输入/输出
103
MImimo-v2-flash (non-thinking)
mimo-v2-flash (non-thinking)Xiaomi
68.3
5K
262K
¥0.72 / ¥2.16输入/输出
104
M
longcat-flash-chat
longcat-flash-chatMeituan
68.0
692
128K
¥1.08 / ¥10.8输入/输出
105
M
minimax-m2.1-preview
minimax-m2.1-previewMinimax
67.7
1.9K
205K
¥0 / ¥0输入/输出
106
TEhunyuan-t1-20250711
hunyuan-t1-20250711Tencent
67.4
259
131K
¥0 / ¥0输入/输出
107
ST
step-3.5-flash
step-3.5-flashStepfun
67.1
4K
256K
¥0.69 / ¥2.07输入/输出
108
Mlongcat-flash-chat-2602-exp
longcat-flash-chat-2602-expMeituan
66.8
2.5K
128K
¥1.08 / ¥10.8输入/输出
109
Aqwen3.5-flash
qwen3.5-flashAlibaba
66.5
3.4K
1M
¥1.24 / ¥12.4输入/输出
110
Xgrok-4-fast-chat
grok-4-fast-chatXai
66.1
408
2M
¥1.44 / ¥3.6输入/输出
111
Aclaude-opus-4-20250514
claude-opus-4-20250514Anthropic
65.8
2.8K
200K
¥108 / ¥540输入/输出
112
Xgrok-4-1-fast-reasoning
grok-4-1-fast-reasoningXai
65.5
5.7K
2M
¥1.44 / ¥3.6输入/输出
113
Aqwen3.5-35b-a3b
qwen3.5-35b-a3bAlibaba
65.2
2.9K
262K
¥1.8 / ¥14.4输入/输出
114
Ogpt-4.1-2025-04-14
gpt-4.1-2025-04-14Openai
64.9
3.1K
1.05M
¥14.4 / ¥57.6输入/输出
115
Mminimax-m2.7
minimax-m2.7Minimax
64.6
2.7K
205K
¥0 / ¥0输入/输出
116
Mkimi-k2-0905-preview
kimi-k2-0905-previewMoonshot
64.3
700
262K
¥4.32 / ¥18输入/输出
117
Aclaude-haiku-4-5-20251001
claude-haiku-4-5-20251001Anthropic
64.0
7.3K
200K
¥7.2 / ¥36输入/输出
118
Ddeepseek-v3-0324
deepseek-v3-0324Deepseek
63.7
3.1K
75K
¥1.44 / ¥5.76输入/输出
119
MImimo-v2-flash (thinking)
mimo-v2-flash (thinking)Xiaomi
63.4
1.3K
262K
¥0.72 / ¥2.16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
63.0
3.8K
1.05M
¥0.72 / ¥2.88输入/输出
121
TEhunyuan-turbos-20250416
hunyuan-turbos-20250416Tencent
62.7
919
131K
¥0 / ¥0输入/输出
122
Zglm-4.5-air
glm-4.5-airZai
62.4
1.5K
131K
¥0 / ¥0输入/输出
123
Aamazon-nova-experimental-chat-10-20
amazon-nova-experimental-chat-10-20Amazon
62.1
916
-
-
124
Ggemini-2.5-flash-lite-preview-06-17-thinking
gemini-2.5-flash-lite-preview-06-17-thinkingGoogle
61.8
1.8K
65.5K
¥0.72 / ¥2.88输入/输出
125
Ogpt-5.4-nano-high
gpt-5.4-nano-highOpenai
61.5
2.7K
400K
¥1.44 / ¥9输入/输出
126
Aqwen3-30b-a3b-instruct-2507
qwen3-30b-a3b-instruct-2507Alibaba
61.2
1.2K
262K
¥2.16 / ¥3.6输入/输出
127
Aqwen3-coder-480b-a35b-instruct
qwen3-coder-480b-a35b-instructAlibaba
60.9
1.4K
262K
¥6.2 / ¥24.8输入/输出
128
Aqwen3-vl-235b-a22b-thinking
qwen3-vl-235b-a22b-thinkingAlibaba
60.6
480
131K
¥2.06 / ¥8.26输入/输出
129
Ogpt-5-mini-high
gpt-5-mini-highOpenai
60.2
1.4K
400K
¥1.8 / ¥14.4输入/输出
130
MAmistral-medium-2505
mistral-medium-2505Mistral
59.9
2.4K
262K
¥2.88 / ¥14.4输入/输出
131
Aclaude-sonnet-4-20250514-thinking-32k
claude-sonnet-4-20250514-thinking-32kAnthropic
59.6
1.9K
200K
¥21.6 / ¥108输入/输出
132
Oo1-2024-12-17
o1-2024-12-17Openai
59.3
3.1K
128K
¥108 / ¥432输入/输出
133
Xgrok-3-mini-high
grok-3-mini-highXai
59.0
991
128K
¥0 / ¥0输入/输出
134
Mminimax-m2.5
minimax-m2.5Minimax
58.7
3.9K
205K
¥0 / ¥0输入/输出
135
Ddeepseek-r1
deepseek-r1Deepseek
58.4
1.9K
164K
¥5.04 / ¥18输入/输出
136
Ggemini-2.0-flash-001
gemini-2.0-flash-001Google
58.1
3.5K
1.05M
¥1.08 / ¥4.32输入/输出
137
Mkimi-k2-0711-preview
kimi-k2-0711-previewMoonshot
57.8
1.5K
131K
¥4.32 / ¥18输入/输出
138
Xgrok-3-mini-beta
grok-3-mini-betaXai
57.5
1.4K
1M
¥9 / ¥18输入/输出
139
Aqwen2.5-max
qwen2.5-maxAlibaba
57.1
2.8K
32K
¥11.5 / ¥46输入/输出
140
Ggemma-3-27b-it
gemma-3-27b-itGoogle
56.8
3K
128K
¥2.15 / ¥2.15输入/输出
141
Aclaude-sonnet-4-20250514
claude-sonnet-4-20250514Anthropic
56.5
2.6K
200K
¥21.6 / ¥108输入/输出
142
Zglm-4.6v
glm-4.6vZai
56.2
285
128K
¥2.16 / ¥6.48输入/输出
143
UNtrinity-large-thinking
-
55.9
2.5K
262K
¥1.8 / ¥6.48输入/输出
144
Anova-2-lite
nova-2-liteAmazon
55.6
1.2K
128K
¥2.38 / ¥19.8输入/输出
145
NV
nvidia-nemotron-3-super-120b-a12b
nvidia-nemotron-3-super-120b-a12bNvidia
55.3
806
262K
¥1.44 / ¥5.76输入/输出
146
Aqwen3-235b-a22b
qwen3-235b-a22bAlibaba
55.0
1.9K
131K
¥2.07 / ¥8.26输入/输出
147
Ogpt-oss-120b
gpt-oss-120bOpenai
54.7
1.6K
131K
¥1.08 / ¥4.32输入/输出
148
Aqwen3-next-80b-a3b-thinking
qwen3-next-80b-a3b-thinkingAlibaba
54.3
750
131K
¥1.04 / ¥10.3输入/输出
149
Zglm-4.7-flash
glm-4.7-flashZai
54.0
1.4K
200K
¥0 / ¥0输入/输出
150
UNintellect-3
-
53.7
449
131K
¥1.44 / ¥7.92输入/输出
151
Ggemma-3-12b-it
gemma-3-12b-itGoogle
53.4
285
128K
¥1.96 / ¥1.96输入/输出
152
Oo4-mini-2025-04-16
o4-mini-2025-04-16Openai
53.1
2.9K
200K
¥7.92 / ¥31.7输入/输出
153
Mminimax-m2
minimax-m2Minimax
52.8
324
197K
¥0 / ¥0输入/输出
154
MAmistral-small-2506
mistral-small-2506Mistral
52.5
985
262K
¥2.88 / ¥14.4输入/输出
155
Ggemini-2.0-flash-lite-preview-02-05
gemini-2.0-flash-lite-preview-02-05Google
52.2
2.3K
1.05M
¥0.54 / ¥2.16输入/输出
156
STstep-1o-turbo-202506
step-1o-turbo-202506Stepfun
51.9
544
-
-
157
Mminimax-m1
minimax-m1Minimax
51.6
1.9K
1M
¥0.95 / ¥9.03输入/输出
158
STstep-3
step-3Stepfun
51.2
405
65.5K
¥1.8 / ¥4.68输入/输出
159
Ddeepseek-v3
deepseek-v3Deepseek
50.9
2.5K
128K
¥0 / ¥0输入/输出
160
STstep-2-16k-exp-202412
step-2-16k-exp-202412Stepfun
50.6
642
16.4K
¥37.5 / ¥118输入/输出
161
UNtrinity-large-preview
-
50.3
3.1K
262K
¥1.8 / ¥6.48输入/输出
162
Aqwen-plus-0125
qwen-plus-0125Alibaba
50.0
578
1M
¥0.83 / ¥2.07输入/输出
163
Ggemini-1.5-pro-002
gemini-1.5-pro-002Google
49.7
7.7K
-
-
164
Ogpt-4.1-mini-2025-04-14
gpt-4.1-mini-2025-04-14Openai
49.4
2.6K
1.05M
¥2.88 / ¥11.5输入/输出
165
CO
command-a-03-2025
command-a-03-2025Cohere
49.1
3.7K
256K
¥18 / ¥72输入/输出
166
Oo1-preview
o1-previewOpenai
48.8
4.5K
128K
¥108 / ¥432输入/输出
167
TEhunyuan-turbos-20250226
hunyuan-turbos-20250226Tencent
48.4
217
131K
¥0 / ¥0输入/输出
168
Zglm-4-plus-0111
glm-4-plus-0111Zai
48.1
653
128K
¥72 / ¥72输入/输出
169
Aqwen3-32b
qwen3-32bAlibaba
47.8
412
131K
¥2.07 / ¥8.26输入/输出
170
Aclaude-3-7-sonnet-20250219-thinking-32k
claude-3-7-sonnet-20250219-thinking-32kAnthropic
47.5
3K
-
-
171
Aclaude-3-7-sonnet-20250219
claude-3-7-sonnet-20250219Anthropic
47.2
3.2K
200K
¥21.6 / ¥108输入/输出
172
AG
ling-flash-2.0
ling-flash-2.0Ant Group
46.9
375
131K
¥1.01 / ¥4.1输入/输出
173
TEhunyuan-turbo-0110
hunyuan-turbo-0110Tencent
46.6
266
-
-
174
Aclaude-3-5-sonnet-20241022
claude-3-5-sonnet-20241022Anthropic
46.3
9.9K
200K
¥21.6 / ¥108输入/输出
175
Oo3-mini-high
o3-mini-highOpenai
46.0
1.7K
200K
¥7.92 / ¥31.7输入/输出
176
IA
mercury-2
mercury-2Inception Ai
45.7
360
128K
¥1.8 / ¥5.4输入/输出
177
Oo3-mini
o3-miniOpenai
45.3
4.4K
200K
¥7.92 / ¥31.7输入/输出
178
Ggemma-3n-e4b-it
gemma-3n-e4b-itGoogle
45.0
1.4K
128K
¥0 / ¥0输入/输出
179
Ogpt-5-nano-high
gpt-5-nano-highOpenai
44.7
483
400K
¥0.36 / ¥2.88输入/输出
180
NVnvidia-nemotron-3-nano-30b-a3b-bf16
nvidia-nemotron-3-nano-30b-a3b-bf16Nvidia
44.4
1.7K
131K
¥0 / ¥0输入/输出
181
Zglm-4.5v
glm-4.5vZai
44.1
318
64K
¥4.32 / ¥13输入/输出
182
Ggemma-3-4b-it
gemma-3-4b-itGoogle
43.8
307
128K
¥1.44 / ¥1.44输入/输出
183
Aqwq-32b
qwq-32bAlibaba
43.5
1.9K
131K
¥2.07 / ¥6.2输入/输出
184
Aqwen3-30b-a3b
qwen3-30b-a3bAlibaba
43.2
1.9K
128K
¥0.79 / ¥7.78输入/输出
185
Ddeepseek-v2.5-1210
deepseek-v2.5-1210Deepseek
42.9
1K
1M
¥1.01 / ¥2.02输入/输出
186
Ggemini-1.5-flash-002
gemini-1.5-flash-002Google
42.5
5.1K
2M
¥0.54 / ¥2.2输入/输出
187
Mllama-4-maverick-17b-128e-instruct
llama-4-maverick-17b-128e-instructMeta
42.2
2.7K
1M
¥1.8 / ¥6.26输入/输出
188
Xgrok-2-2024-08-13
grok-2-2024-08-13Xai
41.9
8.7K
1M
¥9 / ¥18输入/输出
189
Ogpt-4o-2024-05-13
gpt-4o-2024-05-13Openai
41.6
13.9K
128K
¥36 / ¥108输入/输出
190
NVllama-3.1-nemotron-ultra-253b-v1
llama-3.1-nemotron-ultra-253b-v1Nvidia
41.3
303
128K
¥4.32 / ¥13输入/输出
191
Oo1-mini
o1-miniOpenai
41.0
7.4K
128K
¥7.92 / ¥31.7输入/输出
192
Ggemini-advanced-0514
gemini-advanced-0514Google
40.7
5.9K
-
-
193
Aclaude-3-5-sonnet-20240620
claude-3-5-sonnet-20240620Anthropic
40.4
10K
200K
¥21.6 / ¥108输入/输出
194
UNathene-v2-chat
-
40.1
3.4K
-
-
195
Aclaude-3-opus-20240229
claude-3-opus-20240229Anthropic
39.8
21.1K
200K
¥108 / ¥540输入/输出
196
Ggemini-1.5-pro-001
gemini-1.5-pro-001Google
39.4
9.4K
-
-
197
AI
olmo-3.1-32b-instruct
olmo-3.1-32b-instructAllenai
39.1
1.4K
200K
¥14.4 / ¥57.6输入/输出
198
Ogpt-4o-mini-2024-07-18
gpt-4o-mini-2024-07-18Openai
38.8
8.3K
128K
¥1.08 / ¥4.32输入/输出
199
Zglm-4-plus
glm-4-plusZai
38.5
3.9K
128K
¥54 / ¥54输入/输出
200
Aqwen-max-0919
qwen-max-0919Alibaba
38.2
2.4K
131K
¥2.48 / ¥9.91输入/输出
201
Ogpt-4o-2024-08-06
gpt-4o-2024-08-06Openai
37.9
5.5K
128K
¥18 / ¥72输入/输出
202
Aqwen2.5-plus-1127
qwen2.5-plus-1127Alibaba
37.6
1.4K
-
-
203
NVllama-3.3-nemotron-49b-super-v1
llama-3.3-nemotron-49b-super-v1Nvidia
37.3
263
131K
¥0 / ¥0输入/输出
204
Ogpt-oss-20b
gpt-oss-20bOpenai
37.0
607
131K
¥0.32 / ¥1.3输入/输出
205
TEhunyuan-large-2025-02-10
hunyuan-large-2025-02-10Tencent
36.6
374
-
-
206
Mllama-4-scout-17b-16e-instruct
llama-4-scout-17b-16e-instructMeta
36.3
1.9K
128K
¥1.44 / ¥5.62输入/输出
207
Mllama-3.1-405b-instruct-fp8
llama-3.1-405b-instruct-fp8Meta
36.0
7.7K
128K
¥0 / ¥0输入/输出
208
MAmistral-small-3.1-24b-instruct-2503
mistral-small-3.1-24b-instruct-2503Mistral
35.7
2K
262K
¥2.88 / ¥14.4输入/输出
209
Aqwen2.5-72b-instruct
qwen2.5-72b-instructAlibaba
35.4
5.8K
131K
¥4.13 / ¥12.4输入/输出
210
Ogpt-4.1-nano-2025-04-14
gpt-4.1-nano-2025-04-14Openai
35.1
702
1.05M
¥14.4 / ¥57.6输入/输出
211
Xgrok-2-mini-2024-08-13
grok-2-mini-2024-08-13Xai
34.8
7.2K
1M
¥9 / ¥18输入/输出
212
Ogpt-4-turbo-2024-04-09
gpt-4-turbo-2024-04-09Openai
34.5
9.9K
128K
¥72 / ¥216输入/输出
213
TEhunyuan-standard-2025-02-10
hunyuan-standard-2025-02-10Tencent
34.2
379
-
-
214
MAmistral-large-2407
mistral-large-2407Mistral
33.9
5.7K
131K
¥14.4 / ¥43.2输入/输出
215
AIolmo-3-32b-think
olmo-3-32b-thinkAllenai
33.5
500
128K
¥2.16 / ¥3.24输入/输出
216
Mllama-3.1-405b-instruct-bf16
llama-3.1-405b-instruct-bf16Meta
33.2
4.9K
128K
¥0 / ¥0输入/输出
217
UNyi-lightning
-
32.9
4.2K
12K
¥1.44 / ¥1.44输入/输出
218
Aclaude-3-5-haiku-20241022
claude-3-5-haiku-20241022Anthropic
32.6
6.2K
200K
¥5.76 / ¥28.8输入/输出
219
Ddeepseek-v2.5
deepseek-v2.5Deepseek
32.3
3.5K
1M
¥1.01 / ¥2.02输入/输出
220
MAmistral-large-2411
mistral-large-2411Mistral
32.0
3.3K
128K
¥14.4 / ¥43.2输入/输出
221
Ogpt-4-1106-preview
gpt-4-1106-previewOpenai
31.7
7.1K
8.19K
¥216 / ¥432输入/输出
222
Mllama-3.3-70b-instruct
llama-3.3-70b-instructMeta
31.4
5.4K
128K
¥0 / ¥0输入/输出
223
IB
granite-4.1-8b
granite-4.1-8bIbm
31.1
400
131K
¥0.36 / ¥0.72输入/输出
224
UNathene-70b-0725
-
30.7
1.9K
-
-
225
UNreka-core-20240904
-
30.4
976
-
-
226
AIllama-3.1-tulu-3-70b
llama-3.1-tulu-3-70bAllenai
30.1
366
-
-
227
TEhunyuan-large-vision
hunyuan-large-visionTencent
29.8
358
-
-
228
Ogpt-4-0125-preview
gpt-4-0125-previewOpenai
29.5
8.4K
8.19K
¥216 / ¥432输入/输出
229
Aamazon-nova-pro-v1.0
amazon-nova-pro-v1.0Amazon
29.2
3K
300K
¥5.76 / ¥23输入/输出
230
Ggemini-1.5-flash-001
gemini-1.5-flash-001Google
28.9
7.5K
2M
¥0.54 / ¥2.2输入/输出
231
Ggemini-1.5-flash-8b-001
gemini-1.5-flash-8b-001Google
28.6
5.3K
2M
¥0.54 / ¥2.2输入/输出
232
Ggemma-2-27b-it
gemma-2-27b-itGoogle
28.3
9.7K
8.19K
¥0.58 / ¥0.58输入/输出
233
Mllama-3.1-70b-instruct
llama-3.1-70b-instructMeta
28.0
7.3K
131K
¥2.88 / ¥2.88输入/输出
234
Aqwen2.5-coder-32b-instruct
qwen2.5-coder-32b-instructAlibaba
27.6
822
131K
¥2.07 / ¥6.2输入/输出
235
COcommand-r-plus-08-2024
command-r-plus-08-2024Cohere
27.3
1.4K
128K
¥18 / ¥72输入/输出
236
MAmagistral-medium-2506
magistral-medium-2506Mistral
27.0
764
128K
¥14.4 / ¥36输入/输出
237
COc4ai-aya-expanse-32b
c4ai-aya-expanse-32bCohere
26.7
3.9K
-
-
238
NVllama-3.1-nemotron-70b-instruct
llama-3.1-nemotron-70b-instructNvidia
26.4
1.1K
128K
¥0 / ¥0输入/输出
239
Aclaude-3-sonnet-20240229
claude-3-sonnet-20240229Anthropic
26.1
10.8K
200K
¥21.6 / ¥108输入/输出
240
UNgemma-2-9b-it-simpo
-
25.8
1.1K
8.19K
¥1.44 / ¥1.44输入/输出
241
AGring-flash-2.0
ring-flash-2.0Ant Group
25.5
381
131K
¥1.01 / ¥4.1输入/输出
242
NVnemotron-4-340b-instruct
nemotron-4-340b-instructNvidia
25.2
2.5K
-
-
243
MAmistral-small-24b-instruct-2501
mistral-small-24b-instruct-2501Mistral
24.8
1.4K
262K
¥2.88 / ¥14.4输入/输出
244
Aamazon-nova-lite-v1.0
amazon-nova-lite-v1.0Amazon
24.5
2.5K
300K
¥0.43 / ¥1.73输入/输出
245
Zglm-4-0520
glm-4-0520Zai
24.2
1.3K
128K
¥108 / ¥108输入/输出
246
UNreka-flash-20240904
-
23.9
1K
65.5K
¥0.72 / ¥1.44输入/输出
247
M
phi-4
phi-4Microsoft
23.6
2.6K
128K
¥0.9 / ¥3.6输入/输出
248
COcommand-r-plus
command-r-plusCohere
23.3
7.8K
128K
¥18 / ¥72输入/输出
249
Aclaude-3-haiku-20240307
claude-3-haiku-20240307Anthropic
23.0
12K
200K
¥1.8 / ¥9输入/输出
250
Ggemma-2-9b-it
gemma-2-9b-itGoogle
22.7
6.7K
8.19K
¥1.44 / ¥1.44输入/输出
251
COc4ai-aya-expanse-8b
c4ai-aya-expanse-8bCohere
22.4
1.5K
-
-
252
UNjamba-1.5-large
-
22.0
998
256K
¥0 / ¥0输入/输出
253
Ogpt-4-0314
gpt-4-0314Openai
21.7
3.6K
8.19K
¥216 / ¥432输入/输出
254
MAministral-8b-2410
ministral-8b-2410Mistral
21.4
760
128K
¥0.72 / ¥0.72输入/输出
255
AIllama-3.1-tulu-3-8b
llama-3.1-tulu-3-8bAllenai
21.1
418
-
-
256
AIolmo-3.1-32b-think
olmo-3.1-32b-thinkAllenai
20.8
904
200K
¥14.4 / ¥57.6输入/输出
257
Ddeepseek-coder-v2
deepseek-coder-v2Deepseek
20.5
1.8K
1M
¥1.01 / ¥2.02输入/输出
258
AIolmo-2-0325-32b-instruct
olmo-2-0325-32b-instructAllenai
20.2
304
-
-
259
NVllama-3.1-nemotron-51b-instruct
llama-3.1-nemotron-51b-instructNvidia
19.9
605
128K
¥0 / ¥0输入/输出
260
Ggemini-pro-dev-api
gemini-pro-dev-apiGoogle
19.6
953
1.05M
¥14.4 / ¥86.4输入/输出
261
Aamazon-nova-micro-v1.0
amazon-nova-micro-v1.0Amazon
19.3
2.5K
128K
¥0.25 / ¥1.01输入/输出
262
IBibm-granite-h-small
ibm-granite-h-smallIbm
18.9
323
-
-
263
MAmistral-large-2402
mistral-large-2402Mistral
18.6
5.5K
262K
¥2.88 / ¥14.4输入/输出
264
COcommand-r-08-2024
command-r-08-2024Cohere
18.3
1.4K
128K
¥18 / ¥72输入/输出
265
Ogpt-4-0613
gpt-4-0613Openai
18.0
6K
8.19K
¥216 / ¥432输入/输出
266
Aqwen2-72b-instruct
qwen2-72b-instructAlibaba
17.7
4.6K
131K
¥4.13 / ¥12.4输入/输出
267
MAmistral-medium
mistral-mediumMistral
17.4
1.8K
262K
¥2.88 / ¥14.4输入/输出
268
UNreka-flash-21b-20240226-online
-
17.1
1.3K
-
-
269
UNreka-flash-21b-20240226
-
16.8
2.3K
-
-
270
Mllama-3-70b-instruct
llama-3-70b-instructMeta
16.5
15K
8.19K
¥3.67 / ¥5.33输入/输出
271
TEhunyuan-standard-256k
hunyuan-standard-256kTencent
16.1
444
-
-
272
Mllama-3.1-8b-instruct
llama-3.1-8b-instructMeta
15.8
6.6K
131K
¥0.79 / ¥0.79输入/输出
273
MAmixtral-8x22b-instruct-v0.1
mixtral-8x22b-instruct-v0.1Mistral
15.5
4.9K
64K
¥14.4 / ¥43.2输入/输出
274
COcommand-r
command-rCohere
15.2
5.3K
128K
¥18 / ¥72输入/输出
275
UNjamba-1.5-mini
-
14.9
998
256K
¥0 / ¥0输入/输出
276
Mwizardlm-70b
wizardlm-70bMicrosoft
14.6
172
-
-
277
Mphi-3-medium-4k-instruct
phi-3-medium-4k-instructMicrosoft
14.3
3K
4.1K
¥1.22 / ¥4.9输入/输出
278
Ogpt-3.5-turbo-0125
gpt-3.5-turbo-0125Openai
14.0
5.4K
16.4K
¥3.6 / ¥10.8输入/输出
279
Aqwen1.5-110b-chat
qwen1.5-110b-chatAlibaba
13.7
2.9K
-
-
280
Ggemma-2-2b-it
gemma-2-2b-itGoogle
13.4
6K
128K
¥0 / ¥0输入/输出
281
UNzephyr-orpo-141b-A35b-v0.1
-
13.0
407
200K
¥108 / ¥432输入/输出
282
Aqwq-32b-preview
qwq-32b-previewAlibaba
12.7
527
131K
¥2.07 / ¥6.2输入/输出
283
Mphi-3-small-8k-instruct
phi-3-small-8k-instructMicrosoft
12.4
2.2K
8.19K
¥1.08 / ¥4.32输入/输出
284
Mllama-3-8b-instruct
llama-3-8b-instructMeta
12.1
10K
8.19K
¥0.29 / ¥0.29输入/输出
285
UNinternlm2_5-20b-chat
-
11.8
1.4K
-
-
286
UNopenchat-3.5
-
11.5
187
-
-
287
Aqwen1.5-72b-chat
qwen1.5-72b-chatAlibaba
11.2
2.7K
-
-
288
UNsnowflake-arctic-instruct
-
10.9
2.8K
-
-
289
UNstarling-lm-7b-beta
-
10.6
1.4K
200K
¥5.4 / ¥18.7输入/输出
290
UNstarling-lm-7b-alpha
-
10.2
410
200K
¥5.4 / ¥18.7输入/输出
291
IBgranite-3.1-8b-instruct
granite-3.1-8b-instructIbm
9.9
467
-
-
292
UNyi-1.5-34b-chat
-
9.6
3.2K
-
-
293
MAmixtral-8x7b-instruct-v0.1
mixtral-8x7b-instruct-v0.1Mistral
9.3
5.2K
32K
¥5.04 / ¥5.04输入/输出
294
UNopenchat-3.5-0106
-
9.0
790
-
-
295
Mllama-2-70b-chat
llama-2-70b-chatMeta
8.7
2K
-
-
296
UNvicuna-33b
-
8.4
703
-
-
297
UNdbrx-instruct-preview
-
8.1
3K
-
-
298
Ogpt-3.5-turbo-1106
gpt-3.5-turbo-1106Openai
7.8
400
16.4K
¥7.2 / ¥14.4输入/输出
299
Aqwen1.5-32b-chat
qwen1.5-32b-chatAlibaba
7.5
2.2K
-
-
300
IBgranite-3.1-2b-instruct
granite-3.1-2b-instructIbm
7.1
464
-
-
301
UNzephyr-7b-beta
-
6.8
202
-
-
302
IBgranite-3.0-8b-instruct
granite-3.0-8b-instructIbm
6.5
954
-
-
303
Mllama-2-13b-chat
llama-2-13b-chatMeta
6.2
783
-
-
304
UNyi-34b-chat
-
5.9
789
-
-
305
Ggemma-1.1-7b-it
gemma-1.1-7b-itGoogle
5.6
2.7K
-
-
306
Aqwen1.5-14b-chat
qwen1.5-14b-chatAlibaba
5.3
1.7K
-
-
307
IBgranite-3.0-2b-instruct
granite-3.0-2b-instructIbm
5.0
1.1K
-
-
308
UNvicuna-13b
-
4.7
448
-
-
309
Mphi-3-mini-4k-instruct
phi-3-mini-4k-instructMicrosoft
4.3
2.8K
4.1K
¥0.94 / ¥3.74输入/输出
310
Mphi-3-mini-4k-instruct-june-2024
phi-3-mini-4k-instruct-june-2024Microsoft
4.0
1.4K
4.1K
¥0.94 / ¥3.74输入/输出
311
MAmistral-7b-instruct-v0.2
mistral-7b-instruct-v0.2Mistral
3.7
1.2K
262K
¥2.88 / ¥14.4输入/输出
312
Aqwen1.5-7b-chat
qwen1.5-7b-chatAlibaba
3.4
296
-
-
313
Mphi-3-mini-128k-instruct
phi-3-mini-128k-instructMicrosoft
3.1
1.8K
128K
¥0.94 / ¥3.74输入/输出
314
MAmistral-7b-instruct
mistral-7b-instructMistral
2.8
175
262K
¥2.88 / ¥14.4输入/输出
315
Mllama-2-7b-chat
llama-2-7b-chatMeta
2.5
580
128K
¥4.03 / ¥48输入/输出
316
Ggemma-7b-it
gemma-7b-itGoogle
2.2
629
-
-
317
Ggemma-1.1-2b-it
gemma-1.1-2b-itGoogle
1.9
1.2K
-
-
318
UNsmollm2-1.7b-instruct
-
1.6
410
-
-
319
Aqwen1.5-4b-chat
qwen1.5-4b-chatAlibaba
1.2
564
-
-
320
Mllama-3.2-3b-instruct
llama-3.2-3b-instructMeta
0.9
933
131K
¥0.22 / ¥0.35输入/输出
321
AIolmo-7b-instruct
olmo-7b-instructAllenai
0.6
497
-
-
322
Mllama-3.2-1b-instruct
llama-3.2-1b-instructMeta
0.3
953
16.4K
¥0.07 / ¥0.08输入/输出
323
Ggemma-2b-it
gemma-2b-itGoogle
0.0
300
-
-
gemini-3.5-flash 为什么排第一
gemini-3.5-flash 当前排名第 1，厂商为 google，百分制分数 100.0，样本量 903。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
俄语常见问题
俄语排行榜看什么指标？
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。
俄语模型应该怎么选？
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。