Spend less and ship more with your models.

Move work to more efficient frontier models without giving up quality. Lower your spend or get more done for the same budget.

Calculate savings

Input your current expenses to see your savings

Model allocation

Split work across models. Adjust each model independently. Or

Total: 100%
Opus 5 Max ($8.23/task)($8.23/task)
Fable 5.1 Max ($9.64/task)($9.64/task)
GPT-5.6 Sol Max ($5.69/task)($5.69/task)
Grok 4.6 Extra High ($2.81/task)($2.81/task)
Composer 2.5 ($0.44/task)($0.44/task)

~$6.23 per task (35.4% cheaper than Fable 5.1 Max)

$0

saved per month

($318,828 per year)

Spend reduction35.4%
New annual spend$581,172
was $900,000
New cost per task$6.23
was $9.64
Get your team's estimate

*Modeled on CursorBench cost per task. Cost view reprices the same tasks. Tasks view keeps your budget fixed. Actual results depend on your workload.

CursorBench 3.2

The calculator reads costs directly from the graph and leaderboard below, shared with cursor.com/evals.

A scatter and line chart comparing Fable 5.1, Fable 5, Opus 5, Opus 4.8, Grok 4.6, GPT-5.6 Sol, GPT-5.6 Terra, GPT-5.6 Luna, GPT-5.5, Sonnet 5, Muse Spark 1.3, GLM 5.2, Composer 2.5, Gemini 3.8 Flash, Gemini 3.7 Flash, Kimi K3, and Kimi K2.7 Code scores against average cost per task.75%CursorBench 3.2 score70%65%60%55%50%45%$10$5$0Average cost per taskGrok 4.6Fable 5.1Gemini 3.8 FlashOpus 5Muse Spark 1.3Kimi K3GPT-5.6 SolSonnet 5Composer 2.5GPT-5.6 TerraGPT-5.6 Luna
Model
1Fable 5.1 Max73.4%$9.6472,06070
2Fable 5.1 Extra High72.8%$6.9651,34955
3Grok 4.6 Extra High70.8%$2.8141,13646
4Fable 5 Max70.5%$17.32103,52572
5Opus 5 Max70.0%$8.2361,83878
6Grok 4.6 High69.9%$2.3432,44939
7Fable 5.1 High69.4%$4.8033,15344
8Opus 5 Extra High69.3%$7.3554,23972
9Gemini 3.8 Flash High69.2%$2.3881,524161
10Fable 5 Extra High68.4%$11.7364,97156
11Fable 5.1 Medium68.0%$3.5323,80136
12Muse Spark 1.3 Max67.9%$1.3133,03448
13GPT-5.6 Sol Max67.2%$5.6928,32048
14Grok 4.6 Medium67.1%$1.2817,94229
15Gemini 3.8 Flash Medium67.0%$1.9361,603136
16Opus 5 High66.7%$3.9127,93248
17Fable 5 High66.5%$8.7743,74748
18Fable 5.1 Low66.2%$2.9019,52231
19Fable 5 Medium65.2%$6.8030,36641
20GPT-5.6 Terra Max64.9%$2.3132,96947
21GPT-5.6 Sol Extra High64.5%$3.8819,69938
22Opus 5 Medium64.3%$3.2923,61244
23Muse Spark 1.3 Extra High63.9%$1.0527,85543
24GPT-5.6 Sol High63.5%$2.7913,86732
25Opus 5 Low62.8%$2.5518,52937
26Opus 4.8 Max62.3%$5.7771,41144
27Fable 5 Low62.1%$4.4618,18231
28Muse Spark 1.3 High61.7%$0.8421,03033
29Gemini 3.7 Flash High61.6%$1.2038,44899
30Sonnet 5 Max61.5%$4.3092,88286
31GPT-5.6 Luna Max61.1%$0.3987,97361
32Grok 4.6 Low61.0%$0.7010,65823
33Muse Spark 1.3 Medium60.8%$0.7718,63532
34Kimi K3 Max60.8%$2.7038,42857
35GPT-5.6 Sol Medium60.0%$1.959,74727
36Kimi K3 High59.7%$1.8926,84647
37Opus 4.8 Extra High59.4%$4.5051,12140
38GPT-5.6 Terra Extra High59.2%$1.1516,08929
39Gemini 3.7 Flash Medium59.0%$0.9530,95382
40Sonnet 5 Extra High58.7%$2.7752,87167
41GPT-5.5 High58.4%$2.0512,18328
42GPT-5.5 Extra High58.4%$2.8517,53432
43Opus 4.8 High58.0%$3.1533,54833
44GPT-5.6 Luna Extra High57.7%$0.2322,48048
45Sonnet 5 High56.9%$2.1339,48357
46GPT-5.6 Luna High56.8%$0.1615,14140
47Opus 4.8 Medium56.1%$2.8128,38432
48Composer 2.556.1%$0.4414,28633
49Muse Spark 1.3 Low55.0%$0.4512,18123
50GLM 5.2 Max55.0%$1.7635,94658
51GPT-5.6 Terra High54.2%$0.719,46823
52GPT-5.5 Medium53.8%$1.518,52225
53Gemini 3.7 Flash Low53.8%$0.7420,59468
54Opus 4.8 Low53.1%$2.0219,62427
55GPT-5.6 Sol Low52.6%$1.015,10419
56Sonnet 5 Medium52.4%$1.4426,20046
57GLM 5.2 High51.5%$1.1921,82949
58Kimi K3 Low50.5%$0.9913,00733
59GPT-5.6 Terra Medium50.3%$0.496,22220
60Kimi K2.7 Code49.7%$1.4331,24758
61Muse Spark 1.3 Minimal48.6%$0.277,75716
62GPT-5.6 Luna Medium47.7%$0.087,09528
63Sonnet 5 Low47.7%$0.8716,26933
64GPT-5.6 Terra Low46.9%$0.425,31219
65GPT-5.5 Low46.6%$0.985,16820
66GPT-5.6 Luna Low37.6%$0.033,20917

Avg cost per task is computed by applying each model's published per-million-token pricing (input, cache read, cache write, and output) to the tokens it used on each task. Results are subject to variance. Small score differences may not be statistically meaningful.