| Signal | GPT-5.2-Codex | Delta | o3 |
|---|---|---|---|
Capabilities | 86 | -- | |
Context window size | 89 | +5 | |
Output Capacity | 85 | +2 | |
Pricing Tier | 14 | +6 | |
Recency | 100 | +26 | |
Versatility | 50 | -17 | |
| Overall Result | 4 wins | of 6 | 1 wins |
24
days ranked higher
4
days
2
days ranked higher
OpenAI
OpenAI
o3 saves you $275.00/month
That's $3300.00/year compared to GPT-5.2-Codex at your current usage level of 100K calls/month.
| Metric | GPT-5.2-Codex | o3 | Winner |
|---|---|---|---|
| Overall Score | 67 | 62 | GPT-5.2-Codex |
| Rank | #20 | #44 | GPT-5.2-Codex |
| Quality Rank | #20 | #44 | GPT-5.2-Codex |
| Adoption Rank | #20 | #44 | GPT-5.2-Codex |
| Parameters | -- | -- | -- |
| Context Window | 400K | 200K | GPT-5.2-Codex |
| Pricing | $1.75/$14.00/M | $2.00/$8.00/M | -- |
| Signal Scores | |||
| Capabilities | 86 | 86 | GPT-5.2-Codex |
| Context window size | 89 | 84 | GPT-5.2-Codex |
| Output Capacity | 85 | 83 | GPT-5.2-Codex |
| Pricing Tier | 14 | 8 | GPT-5.2-Codex |
| Recency | 100 | 74 | GPT-5.2-Codex |
| Versatility | 50 | 67 | o3 |
GPT-5.2-Codex has a moderate advantage with a 4.599999999999994-point lead in composite score. It wins on more signal dimensions, but o3 has specific strengths that could make it the better choice for certain workflows.
Best for Quality
GPT-5.2-Codex
Marginally better benchmark scores; both are excellent
Best for Cost
o3
37% lower pricing; better value at scale
Best for Reliability
GPT-5.2-Codex
Higher uptime and faster response speeds
Best for Prototyping
GPT-5.2-Codex
Stronger community support and better developer experience
Best for Production
GPT-5.2-Codex
Wider enterprise adoption and proven at scale
by OpenAI
GPT-5.2-Codex currently scores higher (67 vs 62), but the best choice depends on your specific use case, budget, and requirements.
GPT-5.2-Codex is ranked #20 and o3 is ranked #44. Rankings are based on a composite score from multiple signals including benchmarks, community sentiment, and adoption metrics.
Compare the detailed pricing breakdown above to see which model offers better value for your usage pattern.