- Peringkat
- #121
- Total token output
- 432,850
- Waktu respons (rata-rata)
- 124.87s
- Total Biaya
- $1.448
Seed-2.0-Code (high) vs DeepSeek V4 Pro 0423
Seed-2.0-Code (high) unggul dalam skor rata-rata dengan 7.5 vs 7.4. DeepSeek V4 Pro 0423 memiliki biaya benchmark lebih rendah di $0.311 vs $1.448. DeepSeek V4 Pro 0423 lebih cepat di 14.05s vs 124.87s, dengan tingkat keberhasilan 65.2% vs 49.3%.
Model yang Dibandingkan
- Peringkat
- #129
- Total token output
- 46,004
- Waktu respons (rata-rata)
- 14.05s
- Total Biaya
- $0.311
Model yang direkomendasikan
DeepSeek V4 Pro 0423
Its score stays close to the best score here (7.4 vs 7.5), while costing about 4.7x less than Seed-2.0-Code (high).
Perbandingan terperinci
| Metrik | Seed-2.0-Code Seed-2.0-Code high | DeepSeek V4 Pro 0423 DeepSeek V4 Pro 0423 none |
|---|---|---|
| Skor | 7.5 | 7.4 |
| Peringkat | #121 | #129 |
| Keandalan | 9.0 | 10.0 |
| Konsistensi | 7.9 | 8.7 |
| Percobaan | 69/69 | 69/69 |
| Tes benar | ||
| Tingkat lulus per percobaan | 65.2% | 49.3% |
| Tes tidak stabil | 5 | 4 |
| Total Run | 69 | 69 |
| Biaya per hasil | 12.061 | 2.341 |
| Total Biaya | $1.448 | $0.311 |
| Harga input | $0.500 / 1M | $0.783 / 1M |
| Harga output | $3.000 / 1M | $1.566 / 1M |
| Total token input | 297,321 | 304,186 |
| Token output | 8,997 | 46,004 |
| Token penalaran | 423,853 | 0 |
| Waktu respons (rata-rata) | 124.87s | 14.05s |
| Waktu respons (maks) | 675.30s | 119.44s |
| Waktu respons (total) | 2871.96s | 323.17s |
| Parameter | ~200B total (~20B aktif) | 1.6T total (49B aktif) |
| Ketersediaan | Tertutup | Sumber terbuka |
Showcase generasi model
Hamster playing table tennis
Prompt: Create a detailed SVG illustration of a hamster playing table tennis.
#121 Seed-2.0-Code
high- Biaya
- $0.037
- Waktu
- 183.6s
- Token
- 12,388 tok
#129 DeepSeek V4 Pro 0423
none
Reached the allocated time limit (300 seconds) without receiving showcase output.
- Biaya
- $0.000
- Waktu
- 300.0s
- 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
| Tugas agen | Skor | Konsistensi | Tingkat lulus per percobaan | Tes tidak stabil | Tes benar | Waktu respons (rata-rata) | Token input | Token output | Token penalaran |
|---|---|---|---|---|---|---|---|---|---|
| Seed-2.0-Code | 10.0 | 10.0 | 100.0% | 0 | 139.94s | 215,351 | 1,811 | 20,464 | |
| DeepSeek V4 Pro 0423 | 10.0 | 10.0 | 100.0% | 0 | 65.50s | 156,108 | 10,457 | 0 |
| Trik anti-AI | Skor | Konsistensi | Tingkat lulus per percobaan | Tes tidak stabil | Tes benar | Waktu respons (rata-rata) | Token input | Token output | Token penalaran |
|---|---|---|---|---|---|---|---|---|---|
| Seed-2.0-Code | 8.3 | 10.0 | 75.0% | 0 | 35.07s | 906 | 1,204 | 17,533 | |
| DeepSeek V4 Pro 0423 | 3.2 | 6.1 | 16.7% | 2 | 4.02s | 540 | 1,168 | 0 |
| Pemrograman | Skor | Konsistensi | Tingkat lulus per percobaan | Tes tidak stabil | Tes benar | Waktu respons (rata-rata) | Token input | Token output | Token penalaran |
|---|---|---|---|---|---|---|---|---|---|
| Seed-2.0-Code | 6.2 | 6.5 | 55.6% | 1 | 266.74s | 6,750 | 432 | 124,956 | |
| DeepSeek V4 Pro 0423 | 5.6 | 10.0 | 33.3% | 0 | 13.38s | 7,275 | 5,500 | 0 |
| Gabungan | Skor | Konsistensi | Tingkat lulus per percobaan | Tes tidak stabil | Tes benar | Waktu respons (rata-rata) | Token input | Token output | Token penalaran |
|---|---|---|---|---|---|---|---|---|---|
| Seed-2.0-Code | 7.3 | 5.8 | 83.3% | 1 | 144.87s | 57,003 | 4,295 | 26,889 | |
| DeepSeek V4 Pro 0423 | 7.9 | 6.9 | 66.7% | 1 | 71.59s | 122,040 | 26,362 | 0 |
| Parsing dan ekstraksi data | Skor | Konsistensi | Tingkat lulus per percobaan | Tes tidak stabil | Tes benar | Waktu respons (rata-rata) | Token input | Token output | Token penalaran |
|---|---|---|---|---|---|---|---|---|---|
| Seed-2.0-Code | 10.0 | 10.0 | 100.0% | 0 | 24.28s | 8,034 | 246 | 4,782 | |
| DeepSeek V4 Pro 0423 | 10.0 | 10.0 | 100.0% | 0 | 4.61s | 7,568 | 200 | 0 |
| Spesifik domain | Skor | Konsistensi | Tingkat lulus per percobaan | Tes tidak stabil | Tes benar | Waktu respons (rata-rata) | Token input | Token output | Token penalaran |
|---|---|---|---|---|---|---|---|---|---|
| Seed-2.0-Code | 3.5 | 4.4 | 33.3% | 2 | 419.73s | 828 | 10 | 212,349 | |
| DeepSeek V4 Pro 0423 | 3.0 | 10.0 | 0.0% | 0 | 4.91s | 675 | 20 | 0 |
| Kecerdasan umum | Skor | Konsistensi | Tingkat lulus per percobaan | Tes tidak stabil | Tes benar | Waktu respons (rata-rata) | Token input | Token output | Token penalaran |
|---|---|---|---|---|---|---|---|---|---|
| Seed-2.0-Code | 4.6 | 7.8 | 0.0% | 0 | 36.45s | 382 | 131 | 2,577 | |
| DeepSeek V4 Pro 0423 | 5.0 | 10.0 | 0.0% | 0 | 2.05s | 471 | 126 | 0 |
| Kepatuhan instruksi | Skor | Konsistensi | Tingkat lulus per percobaan | Tes tidak stabil | Tes benar | Waktu respons (rata-rata) | Token input | Token output | Token penalaran |
|---|---|---|---|---|---|---|---|---|---|
| Seed-2.0-Code | 9.8 | 10.0 | 100.0% | 0 | 11.26s | 816 | 72 | 2,661 | |
| DeepSeek V4 Pro 0423 | 6.3 | 5.8 | 66.7% | 1 | 4.12s | 627 | 713 | 0 |
| Pemecahan teka-teki | Skor | Konsistensi | Tingkat lulus per percobaan | Tes tidak stabil | Tes benar | Waktu respons (rata-rata) | Token input | Token output | Token penalaran |
|---|---|---|---|---|---|---|---|---|---|
| Seed-2.0-Code | 7.8 | 9.3 | 66.7% | 0 | 15.91s | 786 | 585 | 4,473 | |
| DeepSeek V4 Pro 0423 | 10.0 | 10.0 | 100.0% | 0 | 3.61s | 594 | 442 | 0 |
| Pemanggilan alat | Skor | Konsistensi | Tingkat lulus per percobaan | Tes tidak stabil | Tes benar | Waktu respons (rata-rata) | Token input | Token output | Token penalaran |
|---|---|---|---|---|---|---|---|---|---|
| Seed-2.0-Code | 4.7 | 1.6 | 66.7% | 1 | 35.09s | 6,198 | 196 | 644 | |
| DeepSeek V4 Pro 0423 | 10.0 | 10.0 | 100.0% | 0 | 7.40s | 8,105 | 328 | 0 |
| Pengetahuan umum | Skor | Konsistensi | Tingkat lulus per percobaan | Tes tidak stabil | Tes benar | Waktu respons (rata-rata) | Token input | Token output | Token penalaran |
|---|---|---|---|---|---|---|---|---|---|
| Seed-2.0-Code | 3.0 | 10.0 | 0.0% | 0 | 52.23s | 267 | 15 | 6,525 | |
| DeepSeek V4 Pro 0423 | 3.0 | 10.0 | 0.0% | 0 | 5.76s | 183 | 688 | 0 |
Perbandingan Cepat
Ganti Pasangan Perbandingan
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