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Showdown Leaderboard - LLMs

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Real people. Real conversations. Real rankings.

Showdown ranks AI models based on how they perform in real-world use— not synthetic tests or lab settings. Votes are blind, optional, and organic, so rankings reflect authentic preferences.Methodology & Technical Report→
0 promptsReal conversation prompts compared across models through pairwise votes.
0 usersFrom 80+ countries and 70+ languages, spanning all backgrounds and professions.

SEAL Leaderboard - LLMs

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1

gemini-2.5-pro

gemini-2.5-pro
7878
1128.38
-5.73 +5.45
1

gemini-3-pro-preview

gemini-3-pro-preview
5675
1124.45
-5.39 +6.48
2

claude-sonnet-4-5-20250929

claude-sonnet-4-5-20250929
9810
1117.49
-4.2 +4.33
3

claude-sonnet-4-5-20250929 (Thinking)

claude-sonnet-4-5-20250929 (Thinking)
9385
1110.68
-4.4 +5.52
4

gpt-5-chat

gpt-5-chat
11212
1106.91
-5.12 +5.14
4

qwen3-235b-a22b-2507-v1

qwen3-235b-a22b-2507-v1
9606
1106.44
-3.4 +3.67
7

claude-opus-4-1-20250805

claude-opus-4-1-20250805
12337
1084.25
-4.69 +4.52
7

claude-opus-4-1-20250805 (Thinking)

claude-opus-4-1-20250805 (Thinking)
10680
1075.72
-4.01 +4.13
8

claude-haiku-4-5-20251001 (Thinking)

claude-haiku-4-5-20251001 (Thinking)
3979
1071.05
-7.16 +5.87
8

claude-sonnet-4-20250514

claude-sonnet-4-20250514
17627
1070.56
-3.37 +4.12
8

gemini-2.5-flash

gemini-2.5-flash
8040
1069.42
-5.42 +4.29
8

claude-haiku-4-5-20251001

claude-haiku-4-5-20251001
4100
1068.38
-5.61 +5.7
10

claude-sonnet-4-20250514 (Thinking)

claude-sonnet-4-20250514 (Thinking)
13829
1062.97
-4.12 +3.53
14

deepseek-r1-0528

deepseek-r1-0528
7385
1052.05
-5.09 +5.44
15

o3-2025-04-16-medium

o3-2025-04-16-medium*
18194
1043.66
-2.9 +3.27
16

gpt-5-2025-08-07-medium

gpt-5-2025-08-07-medium*
14340
1014.70
-4.06 +4.62
17

o4-mini-2025-04-16-medium

o4-mini-2025-04-16-medium*
18067
1000.43
-3.54 +3.27
17

llama4-maverick-instruct-basic

llama4-maverick-instruct-basic
12442
1000.00
-4.26 +5.21
* This model’s API does not consistently return Markdown-formatted responses. Since raw outputs are used in head-to-head comparisons, this may affect its ranking.

Performance Comparison Across Language Models

Win Rate vs. Each Model iconWin Rate vs. Each Model
Battle Count vs. Each Model iconBattle Count vs. Each Model
Confidence Intervals iconConfidence Intervals
Average Win Rate iconAverage Win Rate
Prompt Distribution iconPrompt Distribution

Win Rate vs. Each Model

Win Rate vs Each Model

Battle Count vs. Each Model

Battle Count vs. Each Model

Confidence

Confidence Intervals

Average Win Rate

Average Win Rate

Prompt Distribution

Prompt Distribution

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