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Trinity Large Thinking (high) vs Ling-2.6-flash

Ling-2.6-flash unggul dalam skor rata-rata dengan 4.9 vs 4.8. Ling-2.6-flash memiliki biaya benchmark lebih rendah di $0.002 vs $0.592. Ling-2.6-flash lebih cepat di 10.71s vs 75.86s, dengan tingkat keberhasilan 39.4% vs 30.3%.

Benchmark dihasilkan dari suite pengujian AI BENCHY pada: 2026-09-10

Model yang Dibandingkan

Peringkat
#288
Total token output
932,619
Waktu respons (rata-rata)
75.86s
Total Biaya
$0.592
Peringkat
#282
Total token output
14,903
Waktu respons (rata-rata)
10.71s
Total Biaya
$0.002
Model yang direkomendasikan Ling-2.6-flash

It has the best score here (4.9), while costing about 371.7x less than Trinity Large Thinking (high).

Perbandingan terperinci

Metrik Trinity Large Thinking Trinity Large Thinking high Rilis: 2026-07-28 Ling-2.6-flash Ling-2.6-flash none Rilis: 2026-04-21
Skor 4.8 4.9
Peringkat #288 #282
Keandalan 10.0 9.6
Konsistensi 7.2 9.3
Percobaan 66/66 66/66
Tes benar
Tingkat lulus per percobaan 39.4% 30.3%
Tes tidak stabil 8 2
Total Run 66 66
Biaya per hasil 12.473 0.024
Total Biaya $0.592 $0.002
Harga input $0.250 / 1M $0.010 / 1M
Harga output $0.800 / 1M $0.030 / 1M
Total token input 101,776 114,384
Token output 276,367 14,903
Token penalaran 656,252 0
Waktu respons (rata-rata) 75.86s 10.71s
Waktu respons (maks) 510.21s 36.03s
Waktu respons (total) 1668.93s 214.28s
Parameter 398B total (13B aktif) 104B total (7.4B 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.

#288 Trinity Large Thinking

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

#282 Ling-2.6-flash

none
Ling-2.6-flash is no longer available as a free model. It has transitioned to a paid model. Continue using it here: https://openrouter.ai/inclusionai/ling-2.6-flash
Biaya
$0.000
Waktu
0.0s
Token
0 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
Ling-2.6-flash 5.3 10.0 33.3% 0 11.21s 813 381 0

Perbandingan Cepat

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