Model comparison
o3 vs o3-pro
Head-to-head evidence from 2 shared benchmark results across 1 category. Overall scores shown here use the public BenchAlign v5 ranking lane.
Sibling matchup inside the o3 family.
Public leaderboard positions: o3 #131 (Supported); o3-pro #127 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. o3 and o3-pro share 2 comparable benchmark results. 0 of 8 categories are comparable. 14 results are unique to o3; 0 to o3-pro.
Updated July 22, 2026- Shared results
- 2
- o3 only
- 14
- o3-pro only
- 0
- Comparable categories
- 0 / 8
Benchmark data for o3 and o3-pro is coming soon on BenchLM.
Confidence note. This is a partial-evidence comparison with 2 shared benchmark results across 1 evidence category; 0 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
BenchLM has partial data for these models, but not enough overlapping benchmark coverage to produce a fair score-level comparison yet.
o3-pro is priced at $20.00 input / $80.00 output per 1M tokens, versus $2.00 input / $8.00 output per 1M tokens for o3.
Operator verdict
What I would choose
Use o3 unless an internal evaluation proves that o3-pro's extra inference time improves the tasks you sell. The listed token prices are ten times higher for o3-pro, while this page has only 2 shared sourced results and no scoreable category aggregate.
Operator receipt. I checked the listed API prices and measured runtime rows on July 15, 2026. o3 is $2 input / $8 output and 118 tok/s; o3-pro is $20 input / $80 output and 27 tok/s.
Honest limit. Two shared rows cannot establish a general quality winner. The equal-looking catalog score is not evidence of equal capability, and the public data here cannot justify the o3-pro premium by itself.
Reviewed by Glevd on July 15, 2026.
Category breakdown
Exact category averages are shown below. Not measured means BenchLM does not have enough sourced public coverage for that model and category.
| Category | o3 | Δ | o3-pro |
|---|---|---|---|
| Math | o314.5 | MarginNo overlap | o3-proNot measured |
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | o3 | o3-pro | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | o3$2 input / $8 output | o3-pro$20 input / $80 output | o3 has the lower combined listed price. |
| Generation speedtokens per second | o3118 tok/s | o3-pro27 tok/s | o3 has the higher measured throughput. |
| First-answer latencyseconds to first token | o35.38 s | o3-pro84.93 s | o3 reaches the first token sooner. |
| Context windowmaximum listed tokens | o3200K | o3-pro200K | Listed context windows are equal. |
Benchmark Deep Dive
Agentic1 benchmarks
| Benchmark | o3 | o3-pro | Result |
|---|---|---|---|
| τ²-bench resultsSource | 80.7% | — | Not comparable |
Coding1 benchmarks
| Benchmark | o3 | o3-pro | Result |
|---|---|---|---|
| AA-SciCodeSource | 41.0% | — | Not comparable |
Reasoning2 benchmarks
Knowledge6 benchmarks
| Benchmark | o3 | o3-pro | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 30.4% | 32.5% | o3-pro leads |
| AA-GPQA DiamondSource | 82.7% | 84.5% | o3-pro leads |
| AA-HLESource | 20.0% | — | Not comparable |
| AA-Omniscience IndexSource | -15.3% | — | Not comparable |
| AA-Omniscience AccuracySource | 38.4% | — | Not comparable |
| AA-Omniscience Hallucination RateSource | 87.1% | — | Not comparable |
Math3 benchmarks
Multimodal2 benchmarks
Inst. Following1 benchmarks
| Benchmark | o3 | o3-pro | Result |
|---|---|---|---|
| AA-IFBenchSource | 71.4% | — | Not comparable |
Frequently Asked Questions (3)
Can I compare o3 and o3-pro on BenchLM yet?
Not fully yet. BenchLM is tracking both models, but the sourced benchmark breakdown for this comparison is still coming soon.
Why does this comparison show “coming soon”?
BenchLM only shows category winners and benchmark-level calls when we have sourced results that can be compared fairly. For these models, the public benchmark coverage is not complete enough yet.
What data is available for o3 and o3-pro today?
o3: $2.00 input / $8.00 output per 1M tokens o3-pro: $20.00 input / $80.00 output per 1M tokens Both model pages still include creator, context window, reasoning mode, and other metadata while benchmark coverage fills in.
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