Skip to main content
BenchLM
Advertise

Model comparison

Claude Opus 4.5 vs o3-pro

Data verified

Head-to-head evidence from 2 shared benchmark results across 1 category. Overall scores shown here use the public BenchAlign v5 ranking lane.

64.22/100
Margin
15.9pts
← winning
o3-pro
OpenAI
48.33/100
0 category wins0 category wins

Public leaderboard positions: Claude Opus 4.5 #34 (Supported); o3-pro #127 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. Claude Opus 4.5 and o3-pro share 2 comparable benchmark results. 0 of 8 categories are comparable. 57 results are unique to Claude Opus 4.5; 0 to o3-pro.

Updated July 22, 2026
Shared results
2
Claude Opus 4.5 only
57
o3-pro only
0
Comparable categories
0 / 8

Benchmark data for Claude Opus 4.5 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 $5.00 input / $25.00 output per 1M tokens for Claude Opus 4.5.

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 scores and score margins for Claude Opus 4.5 and o3-pro
CategoryClaude Opus 4.5Δo3-pro
AgenticClaude Opus 4.562.6MarginNo overlapo3-proNot measured
CodingClaude Opus 4.571.7MarginNo overlapo3-proNot measured
ReasoningClaude Opus 4.564.4MarginNo overlapo3-proNot measured
KnowledgeClaude Opus 4.558.1MarginNo overlapo3-proNot measured
MathClaude Opus 4.557.5MarginNo overlapo3-proNot measured
MultilingualClaude Opus 4.585.7MarginNo overlapo3-proNot measured
MultimodalClaude Opus 4.569.9MarginNo overlapo3-proNot measured
Inst. FollowingClaude Opus 4.569.5MarginNo overlapo3-proNot measured

Operational comparison

Runtime and commercial metrics are compared only when both models have a complete sourced value.

MetricClaude Opus 4.5o3-proComparison
Input / output priceUSD per 1M tokensClaude Opus 4.5$5 input / $25 outputo3-pro$20 input / $80 outputClaude Opus 4.5 has the lower combined listed price.
Generation speedtokens per secondClaude Opus 4.546 tok/so3-pro27 tok/sClaude Opus 4.5 has the higher measured throughput.
First-answer latencyseconds to first tokenClaude Opus 4.51.01 so3-pro84.93 sClaude Opus 4.5 reaches the first token sooner.
Context windowmaximum listed tokensClaude Opus 4.5200Ko3-pro200KListed context windows are equal.

Benchmark Deep Dive

Agentic
BenchmarkClaude Opus 4.5o3-proResult
Terminal-Bench 2.0Source 59.3%—Not comparable
OSWorld-VerifiedSource 66.3%—Not comparable
OSWorldSource 66.3%—Not comparable
Claw-EvalSource 59.6%—Not comparable
QwenClawBenchSource 52.3%—Not comparable
τ³-bench resultsSource 70.2%—Not comparable
VITA-BenchSource 23.3%—Not comparable
DeepPlanningSource 26.4%—Not comparable
ToolathlonSource 43.5%—Not comparable
MCP AtlasSource 42.3%—Not comparable
MCP-TasksSource 71.8%—Not comparable
WideResearchSource 76.4%—Not comparable
CyberGymSource 50.6%—Not comparable
τ²-bench resultsSource 86.3%—Not comparable
Gert LabsSource 64.23%—Not comparable
JobBenchSource 32.3%—Not comparable
Coding
BenchmarkClaude Opus 4.5o3-proResult
SWE-bench VerifiedSource 80.9%—Not comparable
LiveCodeBench v6Source 84.8%—Not comparable
SWE-bench ProSource 57.1%—Not comparable
SWE MultilingualSource 77.5%—Not comparable
NL2RepoSource 43.2%—Not comparable
AA-SciCodeSource 47.0%—Not comparable
Reasoning
BenchmarkClaude Opus 4.5o3-proResult
LongBench v2Source 64.4%—Not comparable
AI-NeedleSource 74%—Not comparable
AA-LCRSource 65.3%—Not comparable
CritPtSource 0.3%—Not comparable
Knowledge
BenchmarkClaude Opus 4.5o3-proResult
GPQASource 87%—Not comparable
SuperGPQASource 70.6%—Not comparable
MMLU-ProSource 89.5%—Not comparable
MMLU-ReduxSource 96.6%—Not comparable
C-EvalSource 92.2%—Not comparable
HLESource 30.8%—Not comparable
Artificial Analysis Intelligence IndexSource 34.7%32.5%Claude Opus 4.5 leads
AA-GPQA DiamondSource 81.0%84.5%o3-pro leads
AA-HLESource 12.9%—Not comparable
AA-Omniscience IndexSource -3.9%—Not comparable
AA-Omniscience AccuracySource 40.7%—Not comparable
AA-Omniscience Hallucination RateSource 75.4%—Not comparable
AA MMLU-ProSource 88.9%—Not comparable
Math
BenchmarkClaude Opus 4.5o3-proResult
AIME26Source 95.1%—Not comparable
HMMT Feb 2025Source 92.9%—Not comparable
HMMT Nov 2025Source 93.3%—Not comparable
HMMT Feb 2026Source 85.3%—Not comparable
MMAnswerBenchSource 84.0%—Not comparable
FrontierMath v2 (Tiers 1-3)Source 20.690%—Not comparable
FrontierMath v2 (Tier 4)Source 4.167%—Not comparable
Multilingual
BenchmarkClaude Opus 4.5o3-proResult
MMLU-ProXSource 85.7%—Not comparable
NOVA-63Source 56.7%—Not comparable
Multimodal
BenchmarkClaude Opus 4.5o3-proResult
MMMU-ProSource 70.6%—Not comparable
MathVisionSource 74.3%—Not comparable
CharXivSource 68.5%—Not comparable
VideoMMMUSource 84.4%—Not comparable
ScreenSpot ProSource 45.7%—Not comparable
V*Source 67.0%—Not comparable
AA-MMMU-ProSource 71.2%—Not comparable
Design Arena WebsiteSource 1277—Not comparable
Inst. Following
BenchmarkClaude Opus 4.5o3-proResult
IFEvalSource 90.9%—Not comparable
IFBenchSource 58%—Not comparable
AA-IFBenchSource 43.0%—Not comparable
Frequently Asked Questions (3)

Can I compare Claude Opus 4.5 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 Claude Opus 4.5 and o3-pro today?

Claude Opus 4.5: $5.00 input / $25.00 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.

Related Comparisons

Explore More

Anthropic Compare Pricing Methodology Find Your Best LLM Overall Rankings
Last updated: July 22, 2026

Choose a model with this week’s evidence

Join 2,000+ readers for ranking moves, pricing changes, and the claims that still need proof.

One email each week. Unsubscribe anytime.