Model comparison
Claude Opus 4.6 vs o1-pro
Head-to-head evidence from 2 shared benchmark results across 1 category. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Claude Opus 4.6 #19 (Supported); o1-pro #148 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Claude Opus 4.6 and o1-pro share 2 comparable benchmark results. 1 of 8 categories are comparable. 44 results are unique to Claude Opus 4.6; 0 to o1-pro.
Updated July 24, 2026- Shared results
- 2
- Claude Opus 4.6 only
- 44
- o1-pro only
- 0
- Comparable categories
- 1 / 8
Pick Claude Opus 4.6 if you want the stronger benchmark profile. o1-pro only becomes the better choice if knowledge is the priority or you want the stronger reasoning-first profile.
Confidence note. This is a partial-evidence comparison with 2 shared benchmark results across 1 evidence category; 1 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
Claude Opus 4.6 is clearly ahead on the BenchAlign aggregate, 67.84 to 45.03. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
o1-pro is also the more expensive model on tokens at $150.00 input / $600.00 output per 1M tokens, versus $5.00 input / $25.00 output per 1M tokens for Claude Opus 4.6. That is roughly 24.0x on output cost alone. o1-pro is the reasoning model in the pair, while Claude Opus 4.6 is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use. Claude Opus 4.6 gives you the larger context window at 1M, compared with 200K for o1-pro.
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 | Claude Opus 4.6 | Δ | o1-pro |
|---|---|---|---|
| Knowledge | Claude Opus 4.669.1 | Margin→ 9.9 | o1-pro79.0 |
| Agentic | Claude Opus 4.673.0 | MarginNo overlap | o1-proNot measured |
| Coding | Claude Opus 4.668.1 | MarginNo overlap | o1-proNot measured |
| Math | Claude Opus 4.636.3 | MarginNo overlap | o1-proNot measured |
| Multimodal | Claude Opus 4.677.3 | MarginNo overlap | o1-proNot measured |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
GPQA
KnowledgeA 91.3%B 79%Winner: Claude Opus 4.6Δ 12.3GPQA: Claude Opus 4.6 scored 91.3%; o1-pro scored 79%. Claude Opus 4.6 wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Claude Opus 4.6 | o1-pro | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Claude Opus 4.6$5 input / $25 output | o1-pro$150 input / $600 output | Claude Opus 4.6 has the lower combined listed price. |
| Generation speedtokens per second | Claude Opus 4.640 tok/s | o1-proNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Claude Opus 4.61.78 s | o1-proNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Claude Opus 4.61M | o1-pro200K | Claude Opus 4.6 lists the larger context window. |
Benchmark Deep Dive
Agentic10 benchmarks
| Benchmark | Claude Opus 4.6 | o1-pro | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 65.4% | — | Not comparable |
| BrowseCompSource | 83.7% | — | Not comparable |
| OSWorld-VerifiedSource | 72.7% | — | Not comparable |
| τ²-bench resultsSource | 84.8% | — | Not comparable |
| Claw-EvalSource | 70.4% | — | Not comparable |
| DeepSearchQASource | 73.7% | — | Not comparable |
| CyberGymSource | 66.6% | — | Not comparable |
| Gert LabsSource | 61.85% | — | Not comparable |
| ResearchClawBenchSource | 19.9% | — | Not comparable |
| JobBenchSource | 36.7% | — | Not comparable |
Coding9 benchmarks
| Benchmark | Claude Opus 4.6 | o1-pro | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | 80.8% | — | Not comparable |
| SWE-bench Verified*Source | 75.6% | — | Not comparable |
| LiveCodeBench ProSource | 70.7% | — | Not comparable |
| SWE-bench ProSource | 53.4% | — | Not comparable |
| SWE-RebenchSource | 65.3% | — | Not comparable |
| React Native EvalsSource | 84.1% | — | Not comparable |
| Vibe Code BenchSource | 57.57% | — | Not comparable |
| AA-SciCodeSource | 45.7% | — | Not comparable |
| FrontierCode 1.1 MainSource | 26.9% | — | Not comparable |
Reasoning2 benchmarks
Knowledgeo1-pro wins15 benchmarks
| Benchmark | Claude Opus 4.6 | o1-pro | Result |
|---|---|---|---|
| GPQASource | 91.3% | 79% | Claude Opus 4.6 leads |
| GPQA-DSource | 89.2% | — | Not comparable |
| SuperGPQASource | 95% | — | Not comparable |
| MMLU-ProSource | 82% | — | Not comparable |
| MMLU-Pro (Arcee)Source | 89.1% | — | Not comparable |
| HLESource | 53% | — | Not comparable |
| HLE w/o toolsSource | 40% | — | Not comparable |
| HealthBench HardSource | 14.8% | — | Not comparable |
| MedXpertQA (Text)Source | 52.1% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 37.8% | 18.9% | Claude Opus 4.6 leads |
| AA-GPQA DiamondSource | 84.0% | — | Not comparable |
| AA-HLESource | 18.6% | — | Not comparable |
| AA-Omniscience IndexSource | 3.5% | — | Not comparable |
| AA-Omniscience AccuracySource | 45.2% | — | Not comparable |
| AA-Omniscience Hallucination RateSource | 76.0% | — | Not comparable |
Math3 benchmarks
Multimodal6 benchmarks
Inst. Following1 benchmarks
| Benchmark | Claude Opus 4.6 | o1-pro | Result |
|---|---|---|---|
| AA-IFBenchSource | 44.6% | — | Not comparable |
Frequently Asked Questions (2)
Which is better, Claude Opus 4.6 or o1-pro?
Claude Opus 4.6 is ahead on BenchLM's BenchAlign leaderboard, 67.84 to 45.03. The biggest single separator in this matchup is GPQA, where the scores are 91.3% and 79%.
Which is better for knowledge tasks, Claude Opus 4.6 or o1-pro?
o1-pro has the edge for knowledge tasks in this comparison, averaging 79 versus 69.1. Inside this category, Artificial Analysis Intelligence Index is the benchmark that creates the most daylight between them.