Objective comparison based on public benchmarks updated weekly: Intelligence Index, Chatbot Arena ELO, pricing and speed.
Overall winner (2026)
DeepSeek V4 Pro
4 of 6 criteria won
ELO Arena
1446
Intelligence Index
25.9
Coding Index
33.3
2 criteria won
View full profile →DeepSeek
ELO Arena
1458
Intelligence Index
53.2
Coding Index
70.0
4 criteria won
View full profile →| Critério | Gemini 2.5 Pro | DeepSeek V4 Pro |
|---|---|---|
| Chatbot Arena ELO | 1446 | 1458 ✓ |
| Intelligence Index (AA) | 25.9 | 53.2 ✓ |
| Coding Index (AA) | 33.3 | 70.0 ✓ |
| Input price ($/1M tok) | $1.25 ✓ | $1.32 |
| Output price ($/1M tok) | $10.00 | $3.96 ✓ |
| Context window | 1.0M tokens | 1.0M tokens |
| Speed (tokens/s) | 128 tok/s ✓ | 54 tok/s |
✓ = winner in this criterion • Source: Artificial Analysis, LMArena, official APIs • Updated weekly
Choosing between Gemini 2.5 Pro and DeepSeek V4 Pro depends on your use case, budget and technical requirements. Below, a practical guide based on benchmark data and each model's specifications.
Google · Multimodal
DeepSeek · Text · Open Source
DeepSeek V4 Pro wins in 4 of 6 criteria analyzed. Check the full table to choose based on your use case.
Data is aggregated from Artificial Analysis (Intelligence Index, Coding Index) and Chatbot Arena/LMArena (ELO). Pricing and specs come from official APIs. Updated weekly.
The Intelligence Index is an aggregate score from Artificial Analysis that combines multiple academic benchmarks (MMLU, GPQA, LiveBench, etc.) into a single rating. The higher the score, the more capable the model is at reasoning tasks.
Yes. Gemini 2.5 Pro costs $1.25/1M input tokens, while DeepSeek V4 Pro costs $1.32/1M tokens — 6% more expensive. For high-volume projects, Gemini 2.5 Pro represents significant savings. Total cost also depends on output pricing and your application's usage pattern.
Gemini 2.5 Pro and DeepSeek V4 Pro have the same context window: 1.0M tokens. For this criterion, the choice should be based on other factors like pricing and quality for your specific use case.