- Peringkat
- #106
- Total token output
- 211,343
- Waktu respons (rata-rata)
- 91.29s
- Total Biaya
- $0.149
DeepSeek V4 Pro 0423 (high) vs GLM 5.2 (medium)
GLM 5.2 (medium) unggul dalam skor rata-rata dengan 8.2 vs 8.1. DeepSeek V4 Pro 0423 (high) memiliki biaya benchmark lebih rendah di $0.149 vs $1.007. GLM 5.2 (medium) lebih cepat di 26.88s vs 91.29s, dengan tingkat keberhasilan 65.2% vs 81.2%.
Model yang Dibandingkan
- Peringkat
- #102
- Total token output
- 81,020
- Waktu respons (rata-rata)
- 26.88s
- Total Biaya
- $1.007
Model yang direkomendasikan
DeepSeek V4 Pro 0423 (high)
Its score stays close to the best score here (8.1 vs 8.2), while costing about 6.8x less than GLM 5.2 (medium).
Perbandingan terperinci
| Metrik | DeepSeek V4 Pro 0423 DeepSeek V4 Pro 0423 high | GLM 5.2 GLM 5.2 medium |
|---|---|---|
| Skor | 8.1 | 8.2 |
| Peringkat | #106 | #102 |
| Keandalan | 10.0 | 9.6 |
| Konsistensi | 7.8 | 8.1 |
| Percobaan | 69/69 | 66/69 |
| Tes benar | ||
| Tingkat lulus per percobaan | 65.2% | 81.2% |
| Tes tidak stabil | 6 | 4 |
| Total Run | 69 | 66 |
| Biaya per hasil | 3.717 | 2.890 |
| Total Biaya | $0.149 | $1.007 |
| Harga input | $0.209 / 1M | $0.153 / 1M |
| Harga output | $0.418 / 1M | $12.000 / 1M |
| Harga baca cache | $0.018 / 1M | $0.150 / 1M |
| Harga tulis cache | T/A | T/A |
| Total token input | 287,061 | 227,164 |
| Token output | 32,056 | 20,029 |
| Token penalaran | 196,607 | 60,991 |
| Waktu respons (rata-rata) | 91.29s | 26.88s |
| Waktu respons (maks) | 416.76s | 102.40s |
| Waktu respons (total) | 2099.56s | 591.34s |
| Parameter | 1.6T total (49B aktif) | 744B total (40B aktif) |
| Ketersediaan | Sumber terbuka | Sumber terbuka |
Harga cache berlaku untuk token input. Pembacaan memakai kembali prompt tersimpan; penulisan menyimpannya dan dapat menambah biaya. Token output menggunakan harga output.
Showcase generasi model
Hamster playing table tennis
Prompt: Create a detailed SVG illustration of a hamster playing table tennis.
#106 DeepSeek V4 Pro 0423
high- Biaya
- $0.023
- Waktu
- 257.6s
- Token
- 14,870 tok
#102 GLM 5.2
medium- Biaya
- $0.041
- Waktu
- 195.8s
- Token
- 9,287 tok
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 |
|---|---|---|---|---|---|---|---|---|---|
| DeepSeek V4 Pro 0423 | 10.0 | 10.0 | 100.0% | 0 | 64.54s | 196,304 | 9,128 | 10,091 | |
| GLM 5.2 | 10.0 | 10.0 | 100.0% | 0 | 102.40s | 189,965 | 7,768 | 11,491 |
| 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 0423 | 5.7 | 5.9 | 58.3% | 2 | 25.70s | 536 | 149 | 3,214 | |
| GLM 5.2 | 10.0 | 10.0 | 100.0% | 0 | 5.89s | 639 | 497 | 2,634 |
| 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 0423 | 6.3 | 8.7 | 33.3% | 0 | 243.00s | 5,090 | 383 | 84,580 | |
| GLM 5.2 | 8.2 | 7.2 | 88.9% | 1 | 40.96s | 7,317 | 1,475 | 17,123 |
| 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 0423 | 10.0 | 10.0 | 100.0% | 0 | 78.99s | 66,082 | 4,582 | 25,404 | |
| GLM 5.2 | 5.0 | 5.0 | 50.0% | 0 | 51.96s | 12,696 | 458 | 4,531 |
| 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 0423 | 10.0 | 10.0 | 100.0% | 0 | 25.03s | 7,690 | 274 | 2,166 | |
| GLM 5.2 | 10.0 | 10.0 | 100.0% | 0 | 13.44s | 7,149 | 348 | 2,345 |
| 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 0423 | 3.6 | 7.2 | 22.2% | 1 | 249.47s | 578 | 16,870 | 58,188 | |
| GLM 5.2 | 4.1 | 4.4 | 44.5% | 2 | 45.47s | 551 | 8,188 | 11,606 |
| 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 0423 | 10.0 | 10.0 | 100.0% | 0 | 8.83s | 471 | 115 | 1,013 | |
| GLM 5.2 | 10.0 | 10.0 | 100.0% | 0 | 17.39s | 498 | 54 | 1,842 |
| 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 0423 | 7.8 | 6.6 | 83.3% | 1 | 8.73s | 627 | 66 | 2,726 | |
| GLM 5.2 | 9.9 | 10.0 | 100.0% | 0 | 7.90s | 678 | 94 | 1,518 |
| 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 0423 | 6.9 | 4.9 | 77.8% | 2 | 56.85s | 591 | 178 | 2,563 | |
| GLM 5.2 | 8.2 | 7.2 | 88.9% | 1 | 13.13s | 672 | 536 | 4,822 |
| 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 0423 | 9.8 | 10.0 | 100.0% | 0 | 15.92s | 8,909 | 295 | 701 | |
| GLM 5.2 | 10.0 | 10.0 | 100.0% | 0 | 20.41s | 6,861 | 230 | 550 |
| 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 0423 | 3.0 | 10.0 | 0.0% | 0 | 34.01s | 183 | 16 | 5,961 | |
| GLM 5.2 | 3.0 | 10.0 | 0.0% | 0 | 34.25s | 138 | 381 | 2,529 |
Perbandingan Cepat
Ganti Pasangan Perbandingan
Grok 4.5highvsGLM 5.2mediumDeepSeek V4.1 Flash 1017maxvsGLM 5.2mediumGemini 4 ArgonlowvsGLM 5.2mediumClaude Opus 4.7mediumvsDeepSeek V4 Pro 0423highSeed-2.0-CodelowvsDeepSeek V4 Pro 0423highKimi K3maxvsGLM 5.2mediumGemini 3.5 FlashhighvsGLM 5.2mediumSeed-2.0-LitemediumvsDeepSeek V4 Pro 0423highClaude Haiku 5.5highvsGLM 5.2mediumDeepSeek V4 Pro 0423highvsNemotron 3 UltramediumTersedia gratisGPT-5.6 TerrahighvsGLM 5.2mediumSeed-2.0-CodelowvsGLM 5.2medium