Skip to main content
AI Choice Engine
← Benchmark sources

cursor.com · benchmark source

Cursor

Cursor’s first-party agent evals for IDE-native multi-file work. CursorBench is vendor-run from real Cursor sessions — useful inside Cursor, not a public reproducible harness.

Open cursor.com3 boards on this publisher

Coding agents

CursorBench

Cursor’s offline correctness suite for ambiguous, multi-file coding-agent tasks sourced from real Cursor sessions rather than public GitHub issues.

Why it matters

It separates frontier models on IDE-style agent work where SWE-bench and similar public suites are increasingly saturated or contaminated.

Use it when

You are choosing a model for Cursor’s agent loop and want a signal aligned with Cursor’s own product evals — then validate on your repo.

The limitation

First-party and not independently reproducible from a public harness. Scores move when Cursor refreshes the problem distribution — CursorBench 4.0 (2026-09-10) is a harder task set, so never compare its scores with 3.x.

Leaderboard snapshot

CursorBench — chart and full table

Same layout as Cursor’s public board: Cost / Tokens / Steps chart, then one full Score · Cost · Tokens · Steps table.

Local leader

Opus 5.5 Max

57.8%

Rows shown

63

Full CursorBench 4.0 table

Snapshot date

2026-10-01

Mirrored from cursor.com/cursorbench

CursorBench 4.0 score15%23%30%38%45%53%60%$0$3$6$9$12$15$18Average cost per taskOpus 5.5 Max: 57.8% · $13.43 · 218,363 tokens · 185 stepsOpus 5.5 Extra High: 56% · $6.98 · 101,083 tokens · 109 stepsOpus 5.5 High: 56% · $3.97 · 53,078 tokens · 68 stepsOpus 5.5 Medium: 52.5% · $2.91 · 37,954 tokens · 54 stepsOpus 5.5 Low: 43.7% · $1.17 · 15,811 tokens · 28 stepsSonnet 5.5 Max: 55.5% · $9.67 · 271,920 tokens · 170 stepsSonnet 5.5 Extra High: 53.1% · $3.88 · 100,158 tokens · 78 stepsSonnet 5.5 High: 47.8% · $1.67 · 37,391 tokens · 41 stepsSonnet 5.5 Medium: 39.2% · $0.70 · 16,036 tokens · 22 stepsSonnet 5.5 Low: 35.8% · $0.50 · 11,668 tokens · 18 stepsFable 5.1 Max: 51.8% · $17.28 · 117,236 tokens · 128 stepsFable 5.1 Extra High: 51.6% · $13.01 · 87,294 tokens · 101 stepsFable 5.1 High: 49.2% · $9.08 · 58,438 tokens · 77 stepsFable 5.1 Medium: 46.8% · $7.05 · 45,411 tokens · 63 stepsFable 5.1 Low: 45.1% · $5.44 · 34,795 tokens · 51 stepsOpus 5 Max: 46.6% · $11.95 · 85,384 tokens · 106 stepsOpus 5 Extra High: 46.1% · $11.43 · 80,094 tokens · 103 stepsOpus 5 High: 44.7% · $9.00 · 61,405 tokens · 86 stepsOpus 5 Medium: 43.3% · $6.94 · 45,272 tokens · 72 stepsOpus 5 Low: 40.7% · $4.87 · 31,995 tokens · 57 stepsGrok 4.7 Extra High: 46.3% · $6.01 · 70,141 tokens · 88 stepsGrok 4.7 High: 43.9% · $4.69 · 56,382 tokens · 71 stepsGrok 4.7 Medium: 41.6% · $3.49 · 36,683 tokens · 60 stepsGrok 4.7 Low: 33.1% · $1.58 · 15,677 tokens · 40 stepsGLM 5.3 Max: 42.6% · $5.05 · 96,387 tokens · 166 stepsGLM 5.3 High: 38% · $3.24 · 60,031 tokens · 114 stepsGLM 5.3 Low: 33.3% · $2.04 · 31,983 tokens · 81 stepsGPT-5.6 Sol Max: 41.7% · $8.23 · 42,944 tokens · 99 stepsGPT-5.6 Sol Extra High: 37.7% · $4.40 · 24,729 tokens · 55 stepsGPT-5.6 Sol High: 35.7% · $2.85 · 16,174 tokens · 41 stepsGPT-5.6 Sol Medium: 31.1% · $1.77 · 10,111 tokens · 32 stepsGPT-5.6 Sol Low: 24.6% · $0.87 · 4,885 tokens · 21 stepsMuse Spark 1.3 Max: 41.6% · $2.64 · 52,005 tokens · 98 stepsMuse Spark 1.3 Extra High: 37.5% · $2.10 · 40,891 tokens · 83 stepsMuse Spark 1.3 High: 33.4% · $1.66 · 30,654 tokens · 69 stepsMuse Spark 1.3 Medium: 32.6% · $1.49 · 27,255 tokens · 64 stepsMuse Spark 1.3 Low: 29.3% · $0.93 · 17,483 tokens · 47 stepsMuse Spark 1.3 Minimal: 24.3% · $0.56 · 10,620 tokens · 34 stepsGrok 4.6 Extra High: 41.4% · $6.10 · 49,814 tokens · 56 stepsGrok 4.6 High: 40.4% · $5.20 · 41,387 tokens · 48 stepsGrok 4.6 Medium: 36.1% · $3.48 · 24,893 tokens · 40 stepsGrok 4.6 Low: 33.4% · $2.25 · 16,307 tokens · 32 stepsGPT-5.6 Terra Max: 41.3% · $5.14 · 60,814 tokens · 107 stepsGPT-5.6 Terra Extra High: 33.6% · $1.81 · 23,436 tokens · 43 stepsGPT-5.6 Terra High: 30.7% · $1.11 · 13,162 tokens · 33 stepsGPT-5.6 Terra Medium: 27.6% · $0.64 · 7,307 tokens · 25 stepsGPT-5.6 Terra Low: 25.2% · $0.52 · 5,914 tokens · 23 stepsGemini 3.8 Flash High: 39.6% · $4.70 · 162,565 tokens · 324 stepsGemini 3.8 Flash Medium: 37.3% · $4.06 · 128,364 tokens · 290 stepsGLM 5.3 Flash Max: 36.8% · $0.39 · 56,410 tokens · 118 stepsGLM 5.3 Flash High: 31.1% · $0.25 · 35,104 tokens · 84 stepsGLM 5.3 Flash Low: 26.9% · $0.15 · 17,831 tokens · 58 stepsGPT-5.6 Luna Max: 35.9% · $1.03 · 87,284 tokens · 208 stepsGPT-5.6 Luna Extra High: 33% · $0.44 · 40,598 tokens · 98 stepsGPT-5.6 Luna High: 29.4% · $0.25 · 23,368 tokens · 64 stepsGPT-5.6 Luna Medium: 22.2% · $0.08 · 7,642 tokens · 32 stepsGPT-5.6 Luna Low: 16% · $0.03 · 3,288 tokens · 18 stepsSonnet 5 Max: 34.1% · $7.17 · 149,257 tokens · 140 stepsSonnet 5 Extra High: 32% · $4.55 · 83,373 tokens · 102 stepsSonnet 5 High: 30.8% · $3.48 · 61,146 tokens · 85 stepsSonnet 5 Medium: 28% · $2.31 · 39,114 tokens · 65 stepsSonnet 5 Low: 24.1% · $1.39 · 23,772 tokens · 46 stepsComposer 2.5: 27.7% · $0.68 · 17,347 tokens · 41 steps

Unlabelled to keep the cluster readable: Grok 4.6, Composer 2.5. Hover a point for its figures, or use the table below.

Better is toward the top-right (higher score, lower cost). X-axis is reversed to match Cursor’s public chart.

CursorBench 4.0 full leaderboard with score, cost, tokens, and steps per task
#ModelScoreCost / taskTokens / taskSteps / task
1Opus 5.5 Max57.8%$13.43218,363185
2Opus 5.5 Extra High56.0%$6.98101,083109
3Opus 5.5 High56.0%$3.9753,07868
4Sonnet 5.5 Max55.5%$9.67271,920170
5Sonnet 5.5 Extra High53.1%$3.88100,15878
6Opus 5.5 Medium52.5%$2.9137,95454
7Fable 5.1 Max51.8%$17.28117,236128
8Fable 5.1 Extra High51.6%$13.0187,294101
9Fable 5.1 High49.2%$9.0858,43877
10Sonnet 5.5 High47.8%$1.6737,39141
11Fable 5.1 Medium46.8%$7.0545,41163
12Opus 5 Max46.6%$11.9585,384106
13Grok 4.7 Extra High46.3%$6.0170,14188
14Opus 5 Extra High46.1%$11.4380,094103
15Fable 5.1 Low45.1%$5.4434,79551
16Opus 5 High44.7%$9.0061,40586
17Grok 4.7 High43.9%$4.6956,38271
18Opus 5.5 Low43.7%$1.1715,81128
19Opus 5 Medium43.3%$6.9445,27272
20GLM 5.3 Max42.6%$5.0596,387166
21GPT-5.6 Sol Max41.7%$8.2342,94499
22Grok 4.7 Medium41.6%$3.4936,68360
23Muse Spark 1.3 Max41.6%$2.6452,00598
24Grok 4.6 Extra High41.4%$6.1049,81456
25GPT-5.6 Terra Max41.3%$5.1460,814107
26Opus 5 Low40.7%$4.8731,99557
27Grok 4.6 High40.4%$5.2041,38748
28Gemini 3.8 Flash High39.6%$4.70162,565324
29Sonnet 5.5 Medium39.2%$0.7016,03622
30GLM 5.3 High38.0%$3.2460,031114
31GPT-5.6 Sol Extra High37.7%$4.4024,72955
32Muse Spark 1.3 Extra High37.5%$2.1040,89183
33Gemini 3.8 Flash Medium37.3%$4.06128,364290
34GLM 5.3 Flash Max36.8%$0.3956,410118
35Grok 4.6 Medium36.1%$3.4824,89340
36GPT-5.6 Luna Max35.9%$1.0387,284208
37Sonnet 5.5 Low35.8%$0.5011,66818
38GPT-5.6 Sol High35.7%$2.8516,17441
39Sonnet 5 Max34.1%$7.17149,257140
40GPT-5.6 Terra Extra High33.6%$1.8123,43643
41Grok 4.6 Low33.4%$2.2516,30732
42Muse Spark 1.3 High33.4%$1.6630,65469
43GLM 5.3 Low33.3%$2.0431,98381
44Grok 4.7 Low33.1%$1.5815,67740
45GPT-5.6 Luna Extra High33.0%$0.4440,59898
46Muse Spark 1.3 Medium32.6%$1.4927,25564
47Sonnet 5 Extra High32.0%$4.5583,373102
48GPT-5.6 Sol Medium31.1%$1.7710,11132
49GLM 5.3 Flash High31.1%$0.2535,10484
50Sonnet 5 High30.8%$3.4861,14685
51GPT-5.6 Terra High30.7%$1.1113,16233
52GPT-5.6 Luna High29.4%$0.2523,36864
53Muse Spark 1.3 Low29.3%$0.9317,48347
54Sonnet 5 Medium28.0%$2.3139,11465
55Composer 2.527.7%$0.6817,34741
56GPT-5.6 Terra Medium27.6%$0.647,30725
57GLM 5.3 Flash Low26.9%$0.1517,83158
58GPT-5.6 Terra Low25.2%$0.525,91423
59GPT-5.6 Sol Low24.6%$0.874,88521
60Muse Spark 1.3 Minimal24.3%$0.5610,62034
61Sonnet 5 Low24.1%$1.3923,77246
62GPT-5.6 Luna Medium22.2%$0.087,64232
63GPT-5.6 Luna Low16.0%$0.033,28818

Avg cost / task applies each model’s published per-million-token pricing to tokens used on each task. This snapshot has no row-level training-data disclosure markers. Small score gaps may not be statistically meaningful — confirm on cursor.com/cursorbench.

Evidence in this catalog

Where CursorBench fits

Closest verified examples we currently carry. A missing score is not a zero.

Model examples

  • Published source observation captured 2026-10-01. Source-specific result; no independent rerun or universal capability verdict.

  • Published source observation captured 2026-10-01. Source-specific result; no independent rerun or universal capability verdict.

  • Published source observation captured 2026-10-01. Source-specific result; no independent rerun or universal capability verdict.

Harness examples

  • CursorIDE agent harness

    CursorBench scores models inside Cursor’s agent loop, not bare API chat.

Open this board on CursorBench (live)