2026 Live Verified

AI Coding Models Leaderboard

Aggregated mirrors of 7 official benchmark boards and real-world coding task scenarios. 100% verified, objective, and zero paid placement.

7Boards
105Models ranked
4Evaluation Tasks
October 2026Period
2026-10-07Last update
โ—We fetch raw rankings from 5 public benchmark providers across 7 official boards โ€” no re-weighting, no composite score. Click "Open official board" on each card to go to the source.
๐ŸงฉTool Matrixโš”๏ธVS Compare
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๐Ÿ“Œ 7 official boards ยท mirrored 1:1

Each card previews a provider's Top 5. Click "View full" for the complete board, or jump to the official page. Data is 100% from each provider โ€” we do no aggregation or math.

LMArena Code โ˜…
Human preference blind battle coding Elo leaderboard
Coding
Metric:Coding Eloยท 53 models
  1. #1Claude Opus 5.51813.6
  2. #2GPT-6 Astra1787.6
  3. #3Claude Sonnet 5.51772.8
  4. #4GPT-6.1 Sol1757.3
  5. #5Claude Fable 5.11744.8
Official โ†—
LMArena Agent
Human preference on real agentic coding sessions
Agent
Metric:Agent Scoreยท 36 models
  1. #1Claude Fable 5.114.31
  2. #2Claude Opus 5.513.82
  3. #3Claude Sonnet 5.512.52
  4. #4GPT-6 Astra12.27
  5. #5GPT-6.1 Sol11.23
Official โ†—
CursorBench
Cursor's first-party agentic coding benchmark (v4.0)
Agent
Metric:Pass rate%ยท 12 models
  1. #1Claude Opus 5.557.8%
  2. #2Claude Fable 5.151.8%
  3. #3Claude Opus 546.6%
  4. #4Grok 4.746.3%
  5. #5GPT-5.6 Sol41.7%
Official โ†—
Artificial Analysis
Independent industry standard Intelligence Index
Overall
Metric:Intelligence Indexยท 99 models
  1. #1Claude Opus 5.557.6
  2. #2Claude Sonnet 5.556
  3. #3Claude Fable 5.153.4
  4. #4GPT-6 Astra52.7
  5. #5Gemini 4 Argon52.6
Official โ†—
Vals AI
Independent evaluations on real-world tasks in software, finance & cybersecurity
Overall
Metric:Accuracy%ยท 32 models
  1. #1Gemini 4 Argon68.9%
  2. #2Claude Sonnet 5.567.0%
  3. #3Claude Opus 5.567.0%
  4. #4Claude Fable 5.165.8%
  5. #5Claude Opus 563.7%
Official โ†—
LiveBench
Contamination-resistant coding suite (completion, generation, JS, Python, TS)
Coding
Metric:Score%ยท 46 models
  1. #1Claude Fable 5.183.4%
  2. #2Claude Opus 5.583.2%
  3. #3Claude Fable 583.0%
  4. #4GPT-6 Astra82.2%
  5. #5Muse Spark 1.381.6%
Official โ†—
LMArena Text
Chatbot Arena text and general capability Elo rating
Chat
Metric:Arena Eloยท 91 models
  1. #1Gemini 4 Argon1525.2
  2. #2Claude Opus 4.81504.7
  3. #3Claude Fable 51504.3
  4. #4Claude Opus 5.51503.7
  5. #5Claude Fable 5.11501.1
Official โ†—

LMArena CodeCoding

Metric: Coding Eloยท53 modelsยทfetched 2026-10-07

Open official board โ†—
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#ModelCoding EloValue ScoreCross-board ranksActions
#11813.6
19.4
L #2
C #1
A #1
V #3
L #2
L #4
#21787.6
7.8
L #4
Cโ€”
A #4
V #6
L #4
L #20
#31772.8
39.1
L #3
Cโ€”
A #2
V #2
L #18
L #27
#41757.3
38.1
L #5
Cโ€”
A #6
V #8
L #6
L #14
#51744.8
7.5
L #1
C #2
A #3
V #4
L #1
L #5
#6
Claude Opus 5Anthropic
1691.8
4.6
L #7
C #3
A #7
V #5
L #10
L #8
#7
GPT-6 SolOpenAI
1687.5
35.6
L #6
Cโ€”
A #10
V #11
L #12
L #36
#81678.4
37.8
L #9
Cโ€”
A #5
V #1
Lโ€”
L #1
#91672.2
44
L #21
Cโ€”
A #13
V #25
L #14
L #16
#101656.1
63.1
L #17
C #11
A #9
V #9
L #5
L #7
#11
Kimi K3Moonshot AI
1655
22.2
L #13
Cโ€”
A #16
V #23
L #11
L #9
#121638
41.7
L #15
C #4
A #12
V #13
L #20
L #46
#13
Hunyuan-T1Tencent
1631.7
479.1
L #18
Cโ€”
A #46
V #24
Lโ€”
L #38
#141624.1
7.2
L #8
Cโ€”
A #8
V #7
L #3
L #3
#15
GLM-5.3Zhipu AI
1622.3
60.5
L #22
Cโ€”
A #14
V #15
L #24
L #18
#161618.6
392.3
L #16
Cโ€”
A #22
V #20
L #7
L #25
#171617.8
11.5
L #11
C #5
A #11
V #10
L #8
L #13
#181617
40.2
L #24
C #6
A #15
V #17
L #16
L #24
#19
GLM-5.2Zhipu AI
1603
60.1
L #19
Cโ€”
A #34
Vโ€”
L #32
L #21
#201592
268.5
L #31
Cโ€”
A #33
Vโ€”
L #28
L #50
#211591.9
82
L #30
Cโ€”
A #21
V #21
L #13
L #10
#221583.3
80.1
L #20
C #7
A #20
V #14
L #27
L #6
#231582.3
601
L #23
Cโ€”
A #28
V #22
L #36
L #45
#241581.9
121.8
L #26
Cโ€”
A #30
V #27
L #19
L #32
#251557.5
13.2
L #10
Cโ€”
A #19
V #12
L #23
L #2
#261552.9
39.9
L #25
Cโ€”
A #24
V #29
L #26
L #29
#271540.9
28.7
L #12
C #9
A #27
V #18
L #25
L #33
#281537.8
75.6
L #34
Cโ€”
A #32
Vโ€”
L #31
L #15
#29
Mistral Large 3Mistral AI
1533.8
39.5
Lโ€”Cโ€”
A #26
V #26
L #37
L #57
#301522.1
20.7
Lโ€”Cโ€”
A #36
Vโ€”
L #34
L #26
#311521.5
25.5
L #28
C #8
A #18
V #16
L #17
L #30
#321519.9
238.6
L #29
C #10
A #29
V #19
L #30
L #40
#331518.9
120.6
Lโ€”Cโ€”
A #58
Vโ€”Lโ€”
L #37
#341515.1
213
L #32
Cโ€”
A #38
Vโ€”
L #33
L #23
#35
GPT-5.5OpenAI
1512.7
17.5
L #14
Cโ€”
A #25
Vโ€”
L #9
L #17
#36
Kimi K2.6Moonshot AI
1509.1
74.2
Lโ€”Cโ€”
A #43
Vโ€”
L #38
L #34
#371509.1
35
Lโ€”Cโ€”
A #35
V #28
L #29
L #19
#38
GLM-5.1Zhipu AI
1508.2
54.2
Lโ€”Cโ€”
A #44
Vโ€”Lโ€”
L #31
#39
MiniMax-M3MiniMax
1482.1
185.4
L #33
Cโ€”
A #39
V #30
L #44
L #49
#401482
224.4
Lโ€”Cโ€”
A #40
Vโ€”
L #40
L #35
#41
Kimi K2.7 CodeMoonshot AI
1473.2
47.7
Lโ€”Cโ€”
A #45
Vโ€”
L #41
Lโ€”
#42
GPT-5.4OpenAI
1465.2
28.4
L #27
Cโ€”
A #23
Vโ€”
L #15
L #22
#431446.6
45.6
L #35
Cโ€”
A #37
V #31
L #21
L #11
#441439.7
126.7
Lโ€”Cโ€”
A #53
Vโ€”
L #45
L #39
#451439.6
43.6
Lโ€”Cโ€”
A #41
Vโ€”Lโ€”
L #12
#46
GLM-4-PlusZhipu AI
1435.1
74
Lโ€”Cโ€”
A #52
Vโ€”Lโ€”
L #47
#471397.7
187.3
Lโ€”Cโ€”
A #51
Vโ€”Lโ€”
L #56
#481397.2
376.3
Lโ€”Cโ€”
A #48
V #32
L #39
L #41
#49
DeepSeek-V3DeepSeek
1362.2
543.8
Lโ€”Cโ€”
A #55
Vโ€”Lโ€”
L #54
#501356.9
65.9
Lโ€”Cโ€”
A #47
Vโ€”
L #46
L #48
#511329.7
59
Lโ€”Cโ€”
A #17
Vโ€”
L #35
L #58
#521263.3
81.2
L #36
Cโ€”
A #64
Vโ€”Lโ€”
L #52
#531227.7
23.5
Lโ€”Cโ€”
A #60
Vโ€”Lโ€”
L #42
Rank color:#1#2#3#4-5#6-10#11+

The "Cross-board ranks" column shows this model's rank on the other boards at a glance (grey = not tested there). Boards use different methodologies, so raw values are not directly comparable.

LMArena Code board: LMSYS Coding Arena Elo ratings based on real developer blind tests on challenging code prompts. Sourced directly from arena.ai/leaderboard/code and mirrored 1:1.

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๐Ÿ“Š 7 benchmark boards

LMArena Code board: LMSYS Coding Arena Elo ratings based on real developer blind tests on challenging code prompts. Sourced directly from arena.ai/leaderboard/code and mirrored 1:1.

Coding Elo53 models

LMArena Agent board: real agentic coding sessions scored by human blind votes (signal-based agent score). Sourced from arena.ai/leaderboard/agent and mirrored 1:1.

Agent Score36 models

CursorBench is Cursor's first-party agentic coding benchmark (v4.0). Tasks come from real Cursor sessions with ambiguous, multi-file requirements. Metric: pass rate (%). Mirrored from Cursor's official cursor.com/cursorbench snapshot.

Pass rate%12 models

Artificial Analysis Intelligence Index: Tracks reasoning, quality, and coding intelligence across 600+ models, continuously updated as new frontier models release.

Intelligence Index99 models

Vals AI (Vals Index): Independent benchmarks evaluating frontier AI models on economically valuable real-world tasks across software, finance, cybersecurity, and agent autonomy. Metric: Accuracy (%). Sourced directly from vals.ai and mirrored 1:1.

Accuracy%32 models

LiveBench Coding: Monthly refreshed contamination-resistant suite extracting code completion, generation, JavaScript, Python, and TypeScript performance.

Score%46 models

LMArena Text board: The global standard LMSYS Chatbot Arena tracking cross-domain text generation and complex instruction-following Elo ratings from arena.ai/leaderboard/text.

Arena Elo91 models

All rankings and numbers come directly from official sources; we only do name matching and aggregate presentation, no weighting or re-ranking. Boards use different methodologies, so do not compare raw values across boards.