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DeepSeek V3.2 vs Ling-2.6-flash

DeepSeek V3.2 unggul dalam skor rata-rata dengan 5.0 vs 4.9. Ling-2.6-flash memiliki biaya benchmark lebih rendah di $0.002 vs $0.054. Ling-2.6-flash lebih cepat di 10.71s vs 17.89s, dengan tingkat keberhasilan 36.4% vs 30.3%.

Benchmark dihasilkan dari suite pengujian AI BENCHY pada: 2026-09-04

Peringkat
#267
Total token output
42,099
Waktu respons (rata-rata)
17.89s
Total Biaya
$0.054
Peringkat
#271
Total token output
14,903
Waktu respons (rata-rata)
10.71s
Total Biaya
$0.002
Model yang direkomendasikan Ling-2.6-flash

Its score stays close to the best score here (4.9 vs 5.0), while costing about 33.6x less than DeepSeek V3.2.

Perbandingan terperinci

Metrik DeepSeek V3.2 DeepSeek V3.2 none Rilis: 2025-12-01 Ling-2.6-flash Ling-2.6-flash none Rilis: 2026-04-21
Skor 5.0 4.9
Peringkat #267 #271
Keandalan 10.0 9.6
Konsistensi 8.1 9.3
Percobaan 66/66 66/66
Tes benar
Tingkat lulus per percobaan 36.4% 30.3%
Tes tidak stabil 5 2
Total Run 66 66
Biaya per hasil 0.870 0.024
Total Biaya $0.054 $0.002
Harga input $0.269 / 1M $0.010 / 1M
Harga output $0.400 / 1M $0.030 / 1M
Total token input 135,831 114,384
Token output 42,099 14,903
Token penalaran 0 0
Waktu respons (rata-rata) 17.89s 10.71s
Waktu respons (maks) 115.89s 36.03s
Waktu respons (total) 393.53s 214.28s
Parameter 671B total (37B aktif) 104B total (7.4B aktif)
Ketersediaan Sumber terbuka Sumber terbuka

Showcase generasi model

Hamster playing table tennis

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

#267 DeepSeek V3.2

none
Biaya
$0.002
Waktu
7.0s
Token
1,046 tok

#271 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
DeepSeek V3.2 3.1 6.9 11.1% 1 14.54s 7,279 4,528 0
Ling-2.6-flash 5.3 10.0 33.3% 0 11.21s 813 381 0

Perbandingan Cepat

Ganti Pasangan Perbandingan