Objective comparison based on public benchmarks updated weekly: Intelligence Index, GPQA Diamond, Chatbot Arena ELO, pricing and speed.
Overall winner (2026)
o3
5 of 7 criteria won
| Critério | o3 | R1 |
|---|---|---|
| Chatbot Arena ELO | — | — |
| Intelligence Index (AA) | 38.4 ✓ | 18.8 |
| Coding Index (AA) | 38.4 ✓ | 15.9 |
| GPQA Diamond | 83.0% ✓ | 70.8% |
| Input price ($/1M tok) | $2.00 | $0.70 ✓ |
| Output price ($/1M tok) | $8.00 | $2.50 ✓ |
| Context window | 200K tokens ✓ | 164K tokens |
| Speed (tokens/s) | 124 tok/s ✓ | — |
✓ = winner in this criterion • Source: Artificial Analysis, LMArena, official APIs • Updated weekly
Choosing between o3 and R1 depends on your use case, budget and technical requirements. Below, a practical guide based on benchmark data and each model's specifications.
OpenAI · Multimodal
DeepSeek · Text · Open Source
o3 wins in 5 of 7 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.
No. R1 is cheaper: $0.7/1M input tokens vs $2/1M tokens for o3 — a 186% difference. For high-volume projects, R1 can reduce costs substantially.
o3 has the larger context window: 200K tokens vs 164K tokens. For long document analysis, extensive transcripts or full codebases, the larger context window is a decisive criterion.