- Peringkat
- #254
- Total token output
- 31,975
- Waktu respons (rata-rata)
- 1.31s
- Total Biaya
- $0.011
Mercury 2.5 Preview (low) vs GPT-4o-mini
Mercury 2.5 Preview (low) unggul dalam skor rata-rata dengan 5.0 vs 5.0. GPT-4o-mini memiliki biaya benchmark lebih rendah di $0.010 vs $0.011. Mercury 2.5 Preview (low) lebih cepat di 1.31s vs 1.92s, dengan tingkat keberhasilan 47.0% vs 22.7%.
- Peringkat
- #257
- Total token output
- 2,913
- Waktu respons (rata-rata)
- 1.92s
- Total Biaya
- $0.010
Model yang direkomendasikan
Mercury 2.5 Preview (low)
It has the strongest score in this comparison (5.0) and the best overall balance of cost and response time across all 2 models.
Perbandingan terperinci
| Metrik | Mercury 2.5 Preview Mercury 2.5 Preview low | GPT-4o-mini GPT-4o-mini none |
|---|---|---|
| Skor | 5.0 | 5.0 |
| Peringkat | #254 | #257 |
| Keandalan | 10.0 | 10.0 |
| Konsistensi | 7.0 | 9.9 |
| Percobaan | 66/66 | 66/66 |
| Tes benar | ||
| Tingkat lulus per percobaan | 47.0% | 22.7% |
| Tes tidak stabil | 8 | 0 |
| Total Run | 66 | 66 |
| Biaya per hasil | 0.169 | 0.195 |
| Total Biaya | $0.011 | $0.010 |
| Harga input | $0.040 / 1M | $0.150 / 1M |
| Harga output | $0.150 / 1M | $0.600 / 1M |
| Total token input | 133,525 | 53,145 |
| Token output | 7,259 | 2,913 |
| Token penalaran | 24,716 | 0 |
| Waktu respons (rata-rata) | 1.31s | 1.92s |
| Waktu respons (maks) | 7.29s | 7.58s |
| Waktu respons (total) | 28.77s | 30.71s |
| Parameter | ~100B | ~8B |
| Ketersediaan | Tertutup | Tertutup |
Showcase generasi model
Hamster playing table tennis
Prompt: Create a detailed SVG illustration of a hamster playing table tennis.
#254 Mercury 2.5 Preview
low- Biaya
- $0.001
- Waktu
- 1.5s
- Token
- 1,169 tok
#257 GPT-4o-mini
none- Biaya
- $0.001
- Waktu
- 6.6s
- Token
- 742 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 |
|---|---|---|---|---|---|---|---|---|---|
| Mercury 2.5 Preview | 5.6 | 3.8 | 66.7% | 3 | 759ms | 786 | 290 | 3,019 | |
| GPT-4o-mini | 4.8 | 10.0 | 25.0% | 0 | 1.34s | 618 | 186 | 0 |
| 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 | 5.5 | 10.0 | 33.3% | 0 | 972ms | 7,794 | 695 | 2,263 | |
| GPT-4o-mini | 3.2 | 9.6 | 0.0% | 0 | 1.63s | 7,314 | 367 | 0 |
| 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 | 3.0 | 10.0 | 0.0% | 0 | 4.77s | 110,517 | 5,013 | 9,661 | |
| GPT-4o-mini | 3.0 | 10.0 | 0.0% | 0 | 6.32s | 29,916 | 1,497 | 0 |
| 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 | 6.3 | 5.8 | 66.7% | 1 | 1.12s | 8,309 | 611 | 1,521 | |
| GPT-4o-mini | 10.0 | 10.0 | 100.0% | 0 | 1.27s | 7,161 | 183 | 0 |
| 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 | 4.1 | 4.4 | 44.5% | 2 | 836ms | 849 | 45 | 2,247 | |
| GPT-4o-mini | 3.0 | 10.0 | 0.0% | 0 | 743ms | 741 | 17 | 0 |
| 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 | 5.0 | 10.0 | 0.0% | 0 | 1.05s | 540 | 105 | 749 | |
| GPT-4o-mini | 4.0 | 10.0 | 0.0% | 0 | 909ms | 480 | 66 | 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 | 6.3 | 10.0 | 50.0% | 0 | 1.60s | 745 | 99 | 1,492 | |
| GPT-4o-mini | 6.3 | 10.0 | 50.0% | 0 | 1.11s | 666 | 69 | 0 |
| 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 | 8.2 | 7.2 | 88.9% | 1 | 710ms | 777 | 312 | 2,271 | |
| GPT-4o-mini | 3.5 | 10.0 | 0.0% | 0 | 1.21s | 651 | 308 | 0 |
| 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 | 2.8 | 1.6 | 33.3% | 1 | 1.57s | 2,983 | 76 | 739 | |
| GPT-4o-mini | 10.0 | 10.0 | 100.0% | 0 | 2.51s | 5,400 | 205 | 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 | 591ms | 225 | 13 | 754 | |
| GPT-4o-mini | 3.0 | 10.0 | 0.0% | 0 | 794ms | 198 | 15 | 0 |
Perbandingan Cepat
Ganti Pasangan Perbandingan
Mercury 2.5 PreviewlowvsMiniMax M2.7mediumDeepSeek V3.2nonevsMercury 2.5 PreviewlowGPT-4o-mininonevsLaguna S 2.1lowTersedia gratisNorth Mini CodenoneTersedia gratisvsMercury 2.5 PreviewlowMercury 2.5 PreviewlowvsQwen3.5-9BnoneMercury 2.5 PreviewlowvsMiMo-V2.5noneMiniMax M2.7mediumvsGPT-4o-mininoneMercury 2.5 PreviewlowvsQwen3 Coder NextnoneMercury 2.5 PreviewlowvsMistral Small 4mediumMercury 2.5 PreviewlowvsMistral Small 4noneMercury 2.5 PreviewlowvsNemotron 3.5 LightningmediumTersedia gratisNemotron 3.5 LightninglowTersedia gratisvsGPT-4o-mininone