#58 DeepSeek V4 Pro
none
SVG tidak valid
- Biaya
- $0.000
- Waktu
- 300.0s
- Token
- 0 tok
AI BENCHY Compare
DeepSeek: DeepSeek V4 Pro vs Z.ai: GLM 5V Turbo
Ringkasan
Perbandingan benchmark DeepSeek V4 Pro vs GLM 5V Turbo: GLM 5V Turbo unggul dalam skor rata-rata dengan 7.3 vs 7.2. DeepSeek V4 Pro memiliki biaya benchmark lebih rendah di $0.034 vs $0.457. DeepSeek V4 Pro lebih cepat di 6.41s vs 23.08s, dengan tingkat keberhasilan 52.4% vs 68.3%.
Model yang direkomendasikan: DeepSeek V4 Pro - Its score stays close to the best score here (7.2 vs 7.3), while costing about 13.7x less than GLM 5V Turbo.
Benchmark dihasilkan dari suite pengujian AI BENCHY pada: 2026-06-18
| Metrik | DeepSeek V4 Pro DeepSeek V4 Pro none | GLM 5V Turbo GLM 5V Turbo medium |
|---|---|---|
| Skor | 7.2 | 7.3 |
| Peringkat | #58 | #56 |
| Keandalan | 9.9 | 10.0 |
| Konsistensi | 8.8 | 7.9 |
| Tes benar | ||
| Tingkat lulus per percobaan | 52.4% | 68.3% |
| Tes tidak stabil | 3 | 6 |
| Total Run | 63 | 63 |
| Biaya per hasil | 0.333 | 4.151 |
| Total Biaya | $0.034 | $0.457 |
| Harga input | $0.435 / 1M | $1.200 / 1M |
| Harga output | $0.870 / 1M | $4.000 / 1M |
| Total token input | 53,558 | 44,615 |
| Token output | 11,424 | 2,347 |
| Token penalaran | 0 | 98,415 |
| Waktu respons (rata-rata) | 6.41s | 23.08s |
| Waktu respons (maks) | 30.09s | 95.88s |
| Waktu respons (total) | 134.66s | 484.63s |
Showcase generasi
Hamster playing table tennis
Prompt: Create a detailed SVG illustration of a hamster playing table tennis.
#56 GLM 5V Turbo
medium
SVG tidak valid
- 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
| Trik anti-AI | Skor | Konsistensi | Tingkat lulus per percobaan | Tes tidak stabil | Tes benar | Waktu respons (rata-rata) | Token input | Token output | Token penalaran |
|---|---|---|---|---|---|---|---|---|---|
| DeepSeek V4 Pro | 3.2 | 6.1 | 16.7% | 2 | 4.02s | 540 | 1,168 | 0 | |
| GLM 5V Turbo | 7.2 | 6.1 | 75.0% | 2 | 10.76s | 555 | 587 | 7,872 |
| Pemrograman | Skor | Konsistensi | Tingkat lulus per percobaan | Tes tidak stabil | Tes benar | Waktu respons (rata-rata) | Token input | Token output | Token penalaran |
|---|---|---|---|---|---|---|---|---|---|
| DeepSeek V4 Pro | 5.6 | 10.0 | 33.3% | 0 | 13.38s | 7,275 | 5,500 | 0 | |
| GLM 5V Turbo | 6.0 | 7.2 | 55.6% | 1 | 63.38s | 7,256 | 440 | 37,873 |
| Gabungan | Skor | Konsistensi | Tingkat lulus per percobaan | Tes tidak stabil | Tes benar | Waktu respons (rata-rata) | Token input | Token output | Token penalaran |
|---|---|---|---|---|---|---|---|---|---|
| DeepSeek V4 Pro | 9.5 | 10.0 | 100.0% | 0 | 23.74s | 27,529 | 2,235 | 0 | |
| GLM 5V Turbo | 6.9 | 3.8 | 66.7% | 1 | 15.06s | 18,533 | 403 | 2,523 |
| 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 |
|---|---|---|---|---|---|---|---|---|---|
| DeepSeek V4 Pro | 10.0 | 10.0 | 100.0% | 0 | 4.61s | 7,568 | 200 | 0 | |
| GLM 5V Turbo | 10.0 | 10.0 | 100.0% | 0 | 9.60s | 7,107 | 236 | 4,333 |
| Spesifik domain | Skor | Konsistensi | Tingkat lulus per percobaan | Tes tidak stabil | Tes benar | Waktu respons (rata-rata) | Token input | Token output | Token penalaran |
|---|---|---|---|---|---|---|---|---|---|
| DeepSeek V4 Pro | 5.3 | 10.0 | 33.3% | 0 | 3.72s | 666 | 24 | 0 | |
| GLM 5V Turbo | 5.3 | 7.2 | 44.4% | 1 | 38.15s | 687 | 32 | 29,035 |
| Kecerdasan umum | Skor | Konsistensi | Tingkat lulus per percobaan | Tes tidak stabil | Tes benar | Waktu respons (rata-rata) | Token input | Token output | Token penalaran |
|---|---|---|---|---|---|---|---|---|---|
| DeepSeek V4 Pro | 5.0 | 10.0 | 0.0% | 0 | 2.05s | 471 | 126 | 0 | |
| GLM 5V Turbo | 10.0 | 10.0 | 100.0% | 0 | 11.09s | 477 | 131 | 2,183 |
| Kepatuhan instruksi | Skor | Konsistensi | Tingkat lulus per percobaan | Tes tidak stabil | Tes benar | Waktu respons (rata-rata) | Token input | Token output | Token penalaran |
|---|---|---|---|---|---|---|---|---|---|
| DeepSeek V4 Pro | 6.3 | 5.8 | 66.7% | 1 | 4.12s | 627 | 713 | 0 | |
| GLM 5V Turbo | 9.9 | 10.0 | 100.0% | 0 | 3.74s | 636 | 72 | 1,813 |
| Pemecahan teka-teki | Skor | Konsistensi | Tingkat lulus per percobaan | Tes tidak stabil | Tes benar | Waktu respons (rata-rata) | Token input | Token output | Token penalaran |
|---|---|---|---|---|---|---|---|---|---|
| DeepSeek V4 Pro | 10.0 | 10.0 | 100.0% | 0 | 3.61s | 594 | 442 | 0 | |
| GLM 5V Turbo | 7.7 | 10.0 | 66.7% | 0 | 10.24s | 609 | 131 | 4,496 |
| Pemanggilan alat | Skor | Konsistensi | Tingkat lulus per percobaan | Tes tidak stabil | Tes benar | Waktu respons (rata-rata) | Token input | Token output | Token penalaran |
|---|---|---|---|---|---|---|---|---|---|
| DeepSeek V4 Pro | 10.0 | 10.0 | 100.0% | 0 | 7.40s | 8,105 | 328 | 0 | |
| GLM 5V Turbo | 7.0 | 3.7 | 66.7% | 1 | 12.53s | 8,569 | 293 | 765 |
| Pengetahuan umum | Skor | Konsistensi | Tingkat lulus per percobaan | Tes tidak stabil | Tes benar | Waktu respons (rata-rata) | Token input | Token output | Token penalaran |
|---|---|---|---|---|---|---|---|---|---|
| DeepSeek V4 Pro | 3.0 | 10.0 | 0.0% | 0 | 5.76s | 183 | 688 | 0 | |
| GLM 5V Turbo | 3.0 | 10.0 | 0.0% | 0 | 40.96s | 186 | 22 | 7,522 |
Perbandingan Cepat
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