- Peringkat
- #193
- Total token output
- 180,597
- Waktu respons (rata-rata)
- 7.61s
- Total Biaya
- $0.039
Mercury 2.5 Preview (high) vs GLM 5.3 (low)
Skor rata-rata hampir imbang di 6.5 vs 6.5. Mercury 2.5 Preview (high) memiliki biaya benchmark lebih rendah di $0.039 vs $0.473. Mercury 2.5 Preview (high) lebih cepat di 7.61s vs 15.28s, dengan tingkat keberhasilan 65.2% vs 63.8%.
Model yang Dibandingkan
- Peringkat
- #195
- Total token output
- 28,602
- Waktu respons (rata-rata)
- 15.28s
- Total Biaya
- $0.473
Model yang direkomendasikan
Mercury 2.5 Preview (high)
It has the best score here (6.5), while costing about 12.4x less than GLM 5.3 (low).
Perbandingan terperinci
| Metrik | Mercury 2.5 Preview Mercury 2.5 Preview high | GLM 5.3 GLM 5.3 low |
|---|---|---|
| Skor | 6.5 | 6.5 |
| Peringkat | #193 | #195 |
| Keandalan | 9.9 | 10.0 |
| Konsistensi | 8.0 | 8.3 |
| Percobaan | 69/69 | 69/69 |
| Tes benar | ||
| Tingkat lulus per percobaan | 65.2% | 63.8% |
| Tes tidak stabil | 6 | 5 |
| Total Run | 69 | 69 |
| Biaya per hasil | 0.319 | 3.936 |
| Total Biaya | $0.039 | $0.473 |
| Harga input | $0.000 / 1M | $1.400 / 1M |
| Harga output | $0.000 / 1M | $4.400 / 1M |
| Total token input | 298,512 | 247,436 |
| Token output | 3,178 | 11,005 |
| Token penalaran | 177,419 | 17,597 |
| Waktu respons (rata-rata) | 7.61s | 15.28s |
| Waktu respons (maks) | 86.84s | 83.60s |
| Waktu respons (total) | 175.08s | 351.49s |
| Parameter | ~100B | 744B total (40B aktif) |
| Ketersediaan | Tertutup | Tertutup |
Showcase generasi model
Hamster playing table tennis
Prompt: Create a detailed SVG illustration of a hamster playing table tennis.
#193 Mercury 2.5 Preview
high- Biaya
- $0.001
- Waktu
- 4.5s
- Token
- 3,851 tok
#195 GLM 5.3
low- Biaya
- $0.007
- Waktu
- 28.4s
- Token
- 1,599 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 |
|---|---|---|---|---|---|---|---|---|---|
| Mercury 2.5 Preview | 6.1 | 3.1 | 66.7% | 1 | 86.84s | 182,753 | 616 | 16,476 | |
| GLM 5.3 | 5.2 | 3.2 | 33.3% | 1 | 51.27s | 142,447 | 2,473 | 1,321 |
| Trik anti-AI | Skor | Konsistensi | Tingkat lulus per percobaan | Tes tidak stabil | Tes benar | Waktu respons (rata-rata) | Token input | Token output | Token penalaran |
|---|---|---|---|---|---|---|---|---|---|
| Mercury 2.5 Preview | 10.0 | 10.0 | 100.0% | 0 | 1.09s | 785 | 181 | 7,008 | |
| GLM 5.3 | 6.9 | 7.9 | 66.7% | 1 | 4.16s | 639 | 266 | 249 |
| Pemrograman | Skor | Konsistensi | Tingkat lulus per percobaan | Tes tidak stabil | Tes benar | Waktu respons (rata-rata) | Token input | Token output | Token penalaran |
|---|---|---|---|---|---|---|---|---|---|
| Mercury 2.5 Preview | 6.7 | 7.8 | 55.6% | 1 | 6.13s | 7,751 | 485 | 42,569 | |
| GLM 5.3 | 6.2 | 6.9 | 55.6% | 1 | 21.02s | 7,317 | 368 | 6,764 |
| Gabungan | Skor | Konsistensi | Tingkat lulus per percobaan | Tes tidak stabil | Tes benar | Waktu respons (rata-rata) | Token input | Token output | Token penalaran |
|---|---|---|---|---|---|---|---|---|---|
| Mercury 2.5 Preview | 3.8 | 1.6 | 50.0% | 2 | 14.36s | 95,789 | 765 | 54,789 | |
| GLM 5.3 | 3.8 | 5.8 | 33.3% | 1 | 53.02s | 80,209 | 6,729 | 5,209 |
| 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 |
|---|---|---|---|---|---|---|---|---|---|
| Mercury 2.5 Preview | 10.0 | 10.0 | 100.0% | 0 | 2.24s | 8,292 | 560 | 8,522 | |
| GLM 5.3 | 10.0 | 10.0 | 100.0% | 0 | 3.42s | 7,149 | 210 | 56 |
| Spesifik domain | Skor | Konsistensi | Tingkat lulus per percobaan | Tes tidak stabil | Tes benar | Waktu respons (rata-rata) | Token input | Token output | Token penalaran |
|---|---|---|---|---|---|---|---|---|---|
| Mercury 2.5 Preview | 2.9 | 4.4 | 22.2% | 2 | 5.68s | 857 | 67 | 25,958 | |
| GLM 5.3 | 5.3 | 10.0 | 33.3% | 0 | 19.23s | 759 | 35 | 3,384 |
| Kecerdasan umum | Skor | Konsistensi | Tingkat lulus per percobaan | Tes tidak stabil | Tes benar | Waktu respons (rata-rata) | Token input | Token output | Token penalaran |
|---|---|---|---|---|---|---|---|---|---|
| Mercury 2.5 Preview | 5.1 | 10.0 | 0.0% | 0 | 1.88s | 542 | 94 | 3,300 | |
| GLM 5.3 | 4.1 | 2.7 | 33.3% | 1 | 4.70s | 498 | 163 | 0 |
| Kepatuhan instruksi | Skor | Konsistensi | Tingkat lulus per percobaan | Tes tidak stabil | Tes benar | Waktu respons (rata-rata) | Token input | Token output | Token penalaran |
|---|---|---|---|---|---|---|---|---|---|
| Mercury 2.5 Preview | 9.8 | 10.0 | 100.0% | 0 | 1.05s | 741 | 94 | 3,777 | |
| GLM 5.3 | 10.0 | 10.0 | 100.0% | 0 | 3.40s | 678 | 72 | 81 |
| Pemecahan teka-teki | Skor | Konsistensi | Tingkat lulus per percobaan | Tes tidak stabil | Tes benar | Waktu respons (rata-rata) | Token input | Token output | Token penalaran |
|---|---|---|---|---|---|---|---|---|---|
| Mercury 2.5 Preview | 10.0 | 10.0 | 100.0% | 0 | 1.21s | 774 | 292 | 6,066 | |
| GLM 5.3 | 10.0 | 10.0 | 100.0% | 0 | 4.20s | 672 | 389 | 225 |
| Pemanggilan alat | Skor | Konsistensi | Tingkat lulus per percobaan | Tes tidak stabil | Tes benar | Waktu respons (rata-rata) | Token input | Token output | Token penalaran |
|---|---|---|---|---|---|---|---|---|---|
| Mercury 2.5 Preview | 3.0 | 10.0 | 0.0% | 0 | 2.25s | 0 | 0 | 0 | |
| GLM 5.3 | 10.0 | 10.0 | 100.0% | 0 | 18.45s | 6,861 | 231 | 0 |
| Pengetahuan umum | Skor | Konsistensi | Tingkat lulus per percobaan | Tes tidak stabil | Tes benar | Waktu respons (rata-rata) | Token input | Token output | Token penalaran |
|---|---|---|---|---|---|---|---|---|---|
| Mercury 2.5 Preview | 3.0 | 10.0 | 0.0% | 0 | 5.41s | 228 | 24 | 8,954 | |
| GLM 5.3 | 3.0 | 10.0 | 0.0% | 0 | 7.42s | 207 | 69 | 308 |
Perbandingan Cepat
Ganti Pasangan Perbandingan
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