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Model yang Dibandingkan

Perbandingan benchmark DeepSeek V4 Flash (high) vs DeepSeek V4 Pro (high) vs Kimi K2.6 (medium) vs GLM 5 (medium): GLM 5 (medium) unggul pada Skor dengan 7.7. DeepSeek V4 Flash (high) unggul pada Keandalan dengan 10.0. DeepSeek V4 Flash (high) memiliki Total Biaya terendah di $0.060. GLM 5 (medium) paling cepat di 33.54s.

Benchmark dihasilkan dari suite pengujian AI BENCHY pada: 2026-08-07

Peringkat
#62
Total token output
168,165
Waktu respons (rata-rata)
49.75s
Total Biaya
$0.060
Peringkat
#63
Total token output
189,181
Waktu respons (rata-rata)
79.14s
Total Biaya
$0.200
Peringkat
#88
Total token output
391,540
Waktu respons (rata-rata)
109.98s
Total Biaya
$0.746
Peringkat
#59
Total token output
124,566
Waktu respons (rata-rata)
33.54s
Total Biaya
$0.307
Model yang direkomendasikan DeepSeek V4 Flash (high)

Its score stays close to the best score here (7.7 vs 7.7), while costing about 7.0x less than model lain dalam perbandingan ini.

Perbandingan terperinci

Metrik DeepSeek V4 Flash DeepSeek V4 Flash high Rilis: 2026-04-24 DeepSeek V4 Pro DeepSeek V4 Pro high Rilis: 2026-04-24 Kimi K2.6 Kimi K2.6 medium Rilis: 2026-04-20 GLM 5 GLM 5 medium Rilis: 2026-02-12
Skor 7.7 7.7 7.2 7.7
Peringkat #62 #63 #88 #59
Keandalan 10.0 10.0 9.4 10.0
Konsistensi 8.2 7.7 8.3 8.1
Cakupan benchmark 22/22 tes · 66/66 percobaan 22/22 tes · 66/66 percobaan 22/22 tes · 66/66 percobaan 21/22 tes · 63/66 percobaan
Tes benar
Tingkat lulus per percobaan 72.7% 63.6% 63.6% 78.8%
Tes tidak stabil 5 6 4 4
Total Run 66 66 66 63
Biaya per hasil 0.402 2.000 9.821 1.668
Total Biaya $0.060 $0.200 $0.746 $0.307
Harga input $0.140 / 1M $0.435 / 1M $0.580 / 1M $0.950 / 1M
Harga output $0.280 / 1M $0.870 / 1M $2.440 / 1M $2.551 / 1M
Total token input 108,392 90,748 68,902 35,224
Token output 14,478 10,462 111,680 21,570
Token penalaran 153,687 178,719 279,860 102,996
Waktu respons (rata-rata) 49.75s 79.14s 109.98s 33.54s
Waktu respons (maks) 218.13s 416.76s 876.20s 99.85s
Waktu respons (total) 1094.41s 1740.97s 2309.56s 435.99s

Showcase generasi model

Hamster playing table tennis

Prompt: Create a detailed SVG illustration of a hamster playing table tennis.

#62 DeepSeek V4 Flash

high
Biaya
$0.003
Waktu
93.1s
Token
7,926 tok

#63 DeepSeek V4 Pro

high
Biaya
$0.023
Waktu
257.6s
Token
14,870 tok

#88 MoonshotAI: Kimi K2.6

medium
Biaya
$0.013
Waktu
103.4s
Token
3,620 tok

#59 GLM 5

medium
Biaya
$0.005
Waktu
20.7s
Token
2,068 tok

Model teratas berdasarkan skor

Skor vs Total Biaya

Waktu respons (rata-rata)

Skor vs Waktu respons (rata-rata)

Total token output

Skor vs Total token output

Rincian Kategori

Pemrograman Skor Konsistensi Tingkat lulus per percobaan Tes tidak stabil Tes benar Waktu respons (rata-rata) Token input Token output Token penalaran
DeepSeek V4 Flash 7.8 10.0 66.7% 0 50.60s 7,279 395 34,862
DeepSeek V4 Pro 6.3 8.7 33.3% 0 243.00s 5,090 383 84,580
Kimi K2.6 5.7 8.6 33.3% 0 214.42s 2,925 9,970 77,189
GLM 5 10.0 10.0 100.0% 0 74.30s 7,254 2,997 52,930

Perbandingan Cepat

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