Navigasi
AD
Track all your projects in one dashboard. Get 📊stats, 🔥heatmaps and 👀recordings in one self-hosted dashboard.
uxwizz.com

Trinity Large Thinking (low) vs DeepSeek V4 Flash 0731

Trinity Large Thinking (low) unggul dalam skor rata-rata dengan 6.3 vs 6.2. DeepSeek V4 Flash 0731 memiliki biaya benchmark lebih rendah di $0.055 vs $0.700. DeepSeek V4 Flash 0731 lebih cepat di 27.42s vs 95.16s, dengan tingkat keberhasilan 47.8% vs 30.4%.

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

Model yang Dibandingkan

Peringkat
#222
Total token output
842,200
Waktu respons (rata-rata)
95.16s
Total Biaya
$0.700
Peringkat
#228
Total token output
39,789
Waktu respons (rata-rata)
27.42s
Total Biaya
$0.055
Model yang direkomendasikan DeepSeek V4 Flash 0731

Its score stays close to the best score here (6.2 vs 6.3), while costing about 12.9x less than Trinity Large Thinking (low).

Perbandingan terperinci

Metrik Trinity Large Thinking Trinity Large Thinking low Rilis: 2026-07-28 DeepSeek V4 Flash 0731 DeepSeek V4 Flash 0731 none Rilis: 2026-08-01
Skor 6.3 6.2
Peringkat #222 #228
Keandalan 10.0 10.0
Konsistensi 8.1 8.7
Percobaan 69/69 69/69
Tes benar
Tingkat lulus per percobaan 47.8% 30.4%
Tes tidak stabil 6 4
Total Run 69 69
Biaya per hasil 9.163 0.826
Total Biaya $0.700 $0.055
Harga input $0.250 / 1M $0.010 / 1M
Harga output $0.800 / 1M $1.280 / 1M
Total token input 347,980 349,876
Token output 121,898 39,789
Token penalaran 720,302 0
Waktu respons (rata-rata) 95.16s 27.42s
Waktu respons (maks) 540.96s 387.15s
Waktu respons (total) 2188.74s 630.70s
Parameter 398B total (13B aktif) 284B total (13B aktif)
Ketersediaan Bobot tersedia Tertutup

Showcase generasi model

Hamster playing table tennis

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

#222 Trinity Large Thinking

low
Biaya
$0.021
Waktu
173.2s
Token
24,586 tok

#228 DeepSeek V4 Flash 0731

none
Biaya
$0.004
Waktu
198.4s
Token
14,316 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 5.3 10.0 33.3% 0 344.45s 5,441 27,039 217,241
DeepSeek V4 Flash 0731 4.3 10.0 0.0% 0 1.72s 7,275 505 0

Perbandingan Cepat

Ganti Pasangan Perbandingan