- Peringkat
- #80
- Total token output
- 67,842
- Waktu respons (rata-rata)
- 16.72s
- Total Biaya
- $3.490
Claude Opus 4.8 (medium) vs GLM 5.2 (high)
GLM 5.2 (high) unggul dalam skor rata-rata dengan 8.4 vs 8.3. GLM 5.2 (high) memiliki biaya benchmark lebih rendah di $1.620 vs $3.490. Claude Opus 4.8 (medium) lebih cepat di 16.72s vs 69.11s, dengan tingkat keberhasilan 82.6% vs 71.0%.
Model yang Dibandingkan
- Peringkat
- #75
- Total token output
- 382,582
- Waktu respons (rata-rata)
- 69.11s
- Total Biaya
- $1.620
Model yang direkomendasikan
Claude Opus 4.8 (medium)
Its score stays close to the best score here (8.3 vs 8.4), while responding about 4.1x faster than GLM 5.2 (high).
Perbandingan terperinci
| Metrik | Claude Opus 4.8 Claude Opus 4.8 medium | GLM 5.2 GLM 5.2 high |
|---|---|---|
| Skor | 8.3 | 8.4 |
| Peringkat | #80 | #75 |
| Keandalan | 10.0 | 10.0 |
| Konsistensi | 9.0 | 8.6 |
| Percobaan | 69/69 | 69/69 |
| Tes benar | ||
| Tingkat lulus per percobaan | 82.6% | 71.0% |
| Tes tidak stabil | 3 | 3 |
| Total Run | 69 | 69 |
| Biaya per hasil | 20.527 | 7.314 |
| Total Biaya | $3.490 | $1.620 |
| Harga input | $5.000 / 1M | $0.325 / 1M |
| Harga output | $25.000 / 1M | $3.990 / 1M |
| Total token input | 360,294 | 288,913 |
| Token output | 43,441 | 79,462 |
| Token penalaran | 24,401 | 303,120 |
| Waktu respons (rata-rata) | 16.72s | 69.11s |
| Waktu respons (maks) | 99.37s | 599.43s |
| Waktu respons (total) | 384.66s | 1589.43s |
| Parameter | ~5T total (~500B 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.
#80 Claude Opus 4.8
medium- Biaya
- $0.057
- Waktu
- 23.1s
- Token
- 2,412 tok
#75 GLM 5.2
high
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 |
|---|---|---|---|---|---|---|---|---|---|
| Claude Opus 4.8 | 6.1 | 3.1 | 66.7% | 1 | 99.37s | 221,846 | 2,676 | 13,239 | |
| GLM 5.2 | 10.0 | 10.0 | 100.0% | 0 | 52.45s | 205,091 | 7,422 | 10,505 |
| Trik anti-AI | Skor | Konsistensi | Tingkat lulus per percobaan | Tes tidak stabil | Tes benar | Waktu respons (rata-rata) | Token input | Token output | Token penalaran |
|---|---|---|---|---|---|---|---|---|---|
| Claude Opus 4.8 | 10.0 | 10.0 | 100.0% | 0 | 3.95s | 834 | 1,179 | 478 | |
| GLM 5.2 | 10.0 | 10.0 | 100.0% | 0 | 5.80s | 639 | 406 | 2,660 |
| Pemrograman | Skor | Konsistensi | Tingkat lulus per percobaan | Tes tidak stabil | Tes benar | Waktu respons (rata-rata) | Token input | Token output | Token penalaran |
|---|---|---|---|---|---|---|---|---|---|
| Claude Opus 4.8 | 10.0 | 10.0 | 100.0% | 0 | 15.33s | 10,590 | 9,945 | 1,381 | |
| GLM 5.2 | 6.4 | 8.6 | 33.3% | 0 | 73.03s | 5,124 | 2,302 | 22,546 |
| Gabungan | Skor | Konsistensi | Tingkat lulus per percobaan | Tes tidak stabil | Tes benar | Waktu respons (rata-rata) | Token input | Token output | Token penalaran |
|---|---|---|---|---|---|---|---|---|---|
| Claude Opus 4.8 | 9.9 | 10.0 | 100.0% | 0 | 54.29s | 101,005 | 19,531 | 4,762 | |
| GLM 5.2 | 10.0 | 10.0 | 100.0% | 0 | 321.47s | 61,516 | 18,824 | 63,861 |
| 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 |
|---|---|---|---|---|---|---|---|---|---|
| Claude Opus 4.8 | 7.1 | 5.6 | 83.3% | 1 | 12.29s | 10,503 | 481 | 312 | |
| GLM 5.2 | 10.0 | 10.0 | 100.0% | 0 | 5.81s | 7,143 | 435 | 1,414 |
| Spesifik domain | Skor | Konsistensi | Tingkat lulus per percobaan | Tes tidak stabil | Tes benar | Waktu respons (rata-rata) | Token input | Token output | Token penalaran |
|---|---|---|---|---|---|---|---|---|---|
| Claude Opus 4.8 | 3.6 | 7.2 | 22.2% | 1 | 18.11s | 972 | 7,476 | 2,987 | |
| GLM 5.2 | 3.1 | 6.5 | 11.1% | 1 | 126.85s | 560 | 49,045 | 157,522 |
| Kecerdasan umum | Skor | Konsistensi | Tingkat lulus per percobaan | Tes tidak stabil | Tes benar | Waktu respons (rata-rata) | Token input | Token output | Token penalaran |
|---|---|---|---|---|---|---|---|---|---|
| Claude Opus 4.8 | 10.0 | 10.0 | 100.0% | 0 | 2.46s | 708 | 237 | 0 | |
| GLM 5.2 | 10.0 | 10.0 | 100.0% | 0 | 12.90s | 498 | 63 | 1,743 |
| Kepatuhan instruksi | Skor | Konsistensi | Tingkat lulus per percobaan | Tes tidak stabil | Tes benar | Waktu respons (rata-rata) | Token input | Token output | Token penalaran |
|---|---|---|---|---|---|---|---|---|---|
| Claude Opus 4.8 | 10.0 | 10.0 | 100.0% | 0 | 3.32s | 909 | 373 | 320 | |
| GLM 5.2 | 10.0 | 10.0 | 100.0% | 0 | 4.26s | 678 | 151 | 1,210 |
| Pemecahan teka-teki | Skor | Konsistensi | Tingkat lulus per percobaan | Tes tidak stabil | Tes benar | Waktu respons (rata-rata) | Token input | Token output | Token penalaran |
|---|---|---|---|---|---|---|---|---|---|
| Claude Opus 4.8 | 10.0 | 10.0 | 100.0% | 0 | 3.95s | 894 | 791 | 483 | |
| GLM 5.2 | 6.0 | 4.6 | 66.7% | 2 | 33.71s | 665 | 568 | 22,392 |
| Pemanggilan alat | Skor | Konsistensi | Tingkat lulus per percobaan | Tes tidak stabil | Tes benar | Waktu respons (rata-rata) | Token input | Token output | Token penalaran |
|---|---|---|---|---|---|---|---|---|---|
| Claude Opus 4.8 | 10.0 | 10.0 | 100.0% | 0 | 8.96s | 11,775 | 301 | 225 | |
| GLM 5.2 | 10.0 | 10.0 | 100.0% | 0 | 9.25s | 6,861 | 246 | 503 |
| Pengetahuan umum | Skor | Konsistensi | Tingkat lulus per percobaan | Tes tidak stabil | Tes benar | Waktu respons (rata-rata) | Token input | Token output | Token penalaran |
|---|---|---|---|---|---|---|---|---|---|
| Claude Opus 4.8 | 3.0 | 10.0 | 0.0% | 0 | 6.14s | 258 | 451 | 214 | |
| GLM 5.2 | 3.0 | 10.0 | 0.0% | 0 | 127.82s | 138 | 0 | 18,764 |
Perbandingan Cepat
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