- Peringkat
- #121
- Total token output
- 432,850
- Waktu respons (rata-rata)
- 124.87s
- Total Biaya
- $1.448
Seed-2.0-Code (high) vs GLM 5.1 (medium)
GLM 5.1 (medium) unggul dalam skor rata-rata dengan 7.5 vs 7.5. GLM 5.1 (medium) memiliki biaya benchmark lebih rendah di $1.066 vs $1.448. GLM 5.1 (medium) lebih cepat di 66.38s vs 124.87s, dengan tingkat keberhasilan 65.2% vs 66.7%.
Model yang Dibandingkan
- Peringkat
- #119
- Total token output
- 248,708
- Waktu respons (rata-rata)
- 66.38s
- Total Biaya
- $1.066
Model yang direkomendasikan
GLM 5.1 (medium)
It has the best score here (7.5), while responding about 1.9x faster than Seed-2.0-Code (high).
Perbandingan terperinci
| Metrik | Seed-2.0-Code Seed-2.0-Code high | GLM 5.1 GLM 5.1 medium |
|---|---|---|
| Skor | 7.5 | 7.5 |
| Peringkat | #121 | #119 |
| Keandalan | 9.0 | 9.2 |
| Konsistensi | 7.9 | 8.4 |
| Percobaan | 69/69 | 69/69 |
| Tes benar | ||
| Tingkat lulus per percobaan | 65.2% | 66.7% |
| Tes tidak stabil | 5 | 4 |
| Total Run | 69 | 69 |
| Biaya per hasil | 12.061 | 9.004 |
| Total Biaya | $1.448 | $1.066 |
| Harga input | $0.500 / 1M | $0.965 / 1M |
| Harga output | $3.000 / 1M | $3.032 / 1M |
| Total token input | 297,321 | 331,577 |
| Token output | 8,997 | 17,919 |
| Token penalaran | 423,853 | 230,789 |
| Waktu respons (rata-rata) | 124.87s | 66.38s |
| Waktu respons (maks) | 675.30s | 308.75s |
| Waktu respons (total) | 2871.96s | 1460.31s |
| Parameter | ~200B total (~20B aktif) | 744B total (40B 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
#119 GLM 5.1
medium
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 | |
| GLM 5.1 | 10.0 | 10.0 | 100.0% | 0 | 225.59s | 248,985 | 1,830 | 30,989 |
| 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 | |
| GLM 5.1 | 10.0 | 10.0 | 100.0% | 0 | 8.31s | 555 | 401 | 5,122 |
| 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 | |
| GLM 5.1 | 4.6 | 3.7 | 44.5% | 2 | 109.63s | 5,702 | 4,871 | 37,826 |
| 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 | |
| GLM 5.1 | 9.8 | 10.0 | 100.0% | 0 | 175.93s | 66,926 | 4,761 | 65,248 |
| 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 | |
| GLM 5.1 | 10.0 | 10.0 | 100.0% | 0 | 9.33s | 7,107 | 991 | 4,552 |
| 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 | |
| GLM 5.1 | 3.0 | 10.0 | 0.0% | 0 | 113.95s | 458 | 969 | 74,651 |
| 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 | |
| GLM 5.1 | 10.0 | 10.0 | 100.0% | 0 | 20.95s | 477 | 2,875 | 2,875 |
| 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 | |
| GLM 5.1 | 6.4 | 5.8 | 66.7% | 1 | 7.47s | 634 | 204 | 1,617 |
| 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 | |
| GLM 5.1 | 8.2 | 7.2 | 88.9% | 1 | 31.64s | 609 | 935 | 5,730 |
| 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 | |
| GLM 5.1 | 3.0 | 10.0 | 0.0% | 0 | 0ms | 0 | 0 | 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 | |
| GLM 5.1 | 3.0 | 10.0 | 0.0% | 0 | 29.40s | 124 | 82 | 2,179 |
Perbandingan Cepat
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