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Trinity Large Thinking (high) vs DeepSeek V4.1 Flash

Skor rata-rata hampir imbang di 5.7 vs 5.8. DeepSeek V4.1 Flash memiliki biaya benchmark lebih rendah di $0.123 vs $0.645. DeepSeek V4.1 Flash lebih cepat di 16.63s vs 74.52s, dengan tingkat keberhasilan 42.0% vs 36.2%.

Benchmark dihasilkan dari suite pengujian AI BENCHY pada: 2026-10-01

Model yang Dibandingkan

Peringkat
#253
Total token output
943,044
Waktu respons (rata-rata)
74.52s
Total Biaya
$0.645
Peringkat
#250
Total token output
292,779
Waktu respons (rata-rata)
16.63s
Total Biaya
$0.123
Model yang direkomendasikan DeepSeek V4.1 Flash

It has the best score here (5.8), while costing about 5.3x less than Trinity Large Thinking (high).

Perbandingan terperinci

Metrik Trinity Large Thinking Trinity Large Thinking high Rilis: 2026-07-28 DeepSeek V4.1 Flash DeepSeek V4.1 Flash none Rilis: 2026-09-10
Skor 5.7 5.8
Peringkat #253 #250
Keandalan 10.0 9.7
Konsistensi 7.3 9.1
Percobaan 69/69 69/69
Tes benar
Tingkat lulus per percobaan 42.0% 36.2%
Tes tidak stabil 8 3
Total Run 69 69
Biaya per hasil 11.289 2.806
Total Biaya $0.645 $0.123
Harga input $0.250 / 1M $0.020 / 1M
Harga output $0.800 / 1M $0.396 / 1M
Total token input 283,116 337,756
Token output 277,920 292,779
Token penalaran 665,124 0
Waktu respons (rata-rata) 74.52s 16.63s
Waktu respons (maks) 510.21s 247.66s
Waktu respons (total) 1713.90s 382.53s
Parameter 398B total (13B aktif) 748B total (16B aktif)
Ketersediaan Bobot tersedia Sumber terbuka

Showcase generasi model

Hamster playing table tennis

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

#253 Trinity Large Thinking

high
Biaya
$0.028
Waktu
130.1s
Token
34,387 tok

#250 DeepSeek V4.1 Flash

none
Biaya
$0.021
Waktu
55.4s
Token
17,181 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
Trinity Large Thinking 3.7 4.7 33.3% 2 245.04s 7,204 83,616 266,836
DeepSeek V4.1 Flash 5.5 10.0 33.3% 0 83.66s 7,284 263,438 0

Perbandingan Cepat

Ganti Pasangan Perbandingan