Model comparison
Claude Opus 4.6 vs GPT-4.1 nano
Head-to-head evidence from 15 shared benchmark results across 7 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Claude Opus 4.6 #19 (Supported); GPT-4.1 nano #170 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Claude Opus 4.6 and GPT-4.1 nano share 15 comparable benchmark results. 2 of 8 categories are comparable. 31 results are unique to Claude Opus 4.6; 6 to GPT-4.1 nano.
Updated July 24, 2026- Shared results
- 15
- Claude Opus 4.6 only
- 31
- GPT-4.1 nano only
- 6
- Comparable categories
- 2 / 8
Pick Claude Opus 4.6 if you want the stronger benchmark profile. GPT-4.1 nano only becomes the better choice if you want the cheaper token bill.
Confidence note. This is a partial-evidence comparison with 15 shared benchmark results across 7 evidence categories; 2 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 41.14. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Claude Opus 4.6's sharpest advantage is in mathematics, where it averages 36.3 against 1. The single biggest benchmark swing on the page is GPQA, 91.3% to 50.3%.
Claude Opus 4.6 is also the more expensive model on tokens at $5.00 input / $25.00 output per 1M tokens, versus $0.10 input / $0.40 output per 1M tokens for GPT-4.1 nano. That is roughly 62.5x on output cost alone.
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 | GPT-4.1 nano |
|---|---|---|---|
| Math | Claude Opus 4.636.3 | Margin← 35.3 | GPT-4.1 nano1.0 |
| Knowledge | Claude Opus 4.669.1 | Margin← 18.8 | GPT-4.1 nano50.3 |
| Agentic | Claude Opus 4.673.0 | MarginNo overlap | GPT-4.1 nanoNot measured |
| Coding | Claude Opus 4.668.1 | MarginNo overlap | GPT-4.1 nanoNot measured |
| Multimodal | Claude Opus 4.677.3 | MarginNo overlap | GPT-4.1 nanoNot measured |
| Inst. Following | Claude Opus 4.6Not measured | MarginNo overlap | GPT-4.1 nano83.2 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
GPQA
KnowledgeA 91.3%B 50.3%Winner: Claude Opus 4.6Δ 41GPQA: Claude Opus 4.6 scored 91.3%; GPT-4.1 nano scored 50.3%. Claude Opus 4.6 wins this benchmark. - Source ↗
FrontierMath v2 (Tiers 1-3)
MathA 40.700%B 1.034%Winner: Claude Opus 4.6Δ 39.7FrontierMath v2 (Tiers 1-3): Claude Opus 4.6 scored 40.700%; GPT-4.1 nano scored 1.034%. 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 | GPT-4.1 nano | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Claude Opus 4.6$5 input / $25 output | GPT-4.1 nano$0.1 input / $0.4 output | GPT-4.1 nano has the lower combined listed price. |
| Generation speedtokens per second | Claude Opus 4.640 tok/s | GPT-4.1 nano181 tok/s | GPT-4.1 nano has the higher measured throughput. |
| First-answer latencyseconds to first token | Claude Opus 4.61.78 s | GPT-4.1 nano0.63 s | GPT-4.1 nano reaches the first token sooner. |
| Context windowmaximum listed tokens | Claude Opus 4.61M | GPT-4.1 nano1M | Listed context windows are equal. |
Benchmark Deep Dive
Agentic13 benchmarks
| Benchmark | Claude Opus 4.6 | GPT-4.1 nano | 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% | 17.3% | Claude Opus 4.6 leads |
| 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 |
| AA Agentic IndexSource | — | 1.2% | Not comparable |
| GDPval-AASource | — | 0.0% | Not comparable |
| GDPval-AASource | — | 63 | Not comparable |
Coding10 benchmarks
| Benchmark | Claude Opus 4.6 | GPT-4.1 nano | 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% | 25.9% | Claude Opus 4.6 leads |
| FrontierCode 1.1 MainSource | 26.9% | — | Not comparable |
| AA Coding IndexSource | — | 11.1% | Not comparable |
Reasoning2 benchmarks
KnowledgeClaude Opus 4.6 wins16 benchmarks
| Benchmark | Claude Opus 4.6 | GPT-4.1 nano | Result |
|---|---|---|---|
| GPQASource | 91.3% | 50.3% | 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% | 9.6% | Claude Opus 4.6 leads |
| AA-GPQA DiamondSource | 84.0% | 51.2% | Claude Opus 4.6 leads |
| AA-HLESource | 18.6% | 3.9% | Claude Opus 4.6 leads |
| AA-Omniscience IndexSource | 3.5% | -56.4% | Claude Opus 4.6 leads |
| AA-Omniscience AccuracySource | 45.2% | 13.3% | Claude Opus 4.6 leads |
| AA-Omniscience Hallucination RateSource | 76.0% | 80.4% | Claude Opus 4.6 leads |
| MMLUSource | — | 80.1% | Not comparable |
MathClaude Opus 4.6 wins3 benchmarks
Multimodal6 benchmarks
Frequently Asked Questions (3)
Which is better, Claude Opus 4.6 or GPT-4.1 nano?
Claude Opus 4.6 is ahead on BenchLM's BenchAlign leaderboard, 67.84 to 41.14. The biggest single separator in this matchup is GPQA, where the scores are 91.3% and 50.3%.
Which is better for knowledge tasks, Claude Opus 4.6 or GPT-4.1 nano?
Claude Opus 4.6 has the edge for knowledge tasks in this comparison, averaging 69.1 versus 50.3. Inside this category, AA-Omniscience Index is the benchmark that creates the most daylight between them.
Which is better for math, Claude Opus 4.6 or GPT-4.1 nano?
Claude Opus 4.6 has the edge for math in this comparison, averaging 36.3 versus 1. Inside this category, FrontierMath v2 (Tiers 1-3) is the benchmark that creates the most daylight between them.