Model comparison
Claude Opus 4.6 (Adaptive) vs GPT-5.4
Head-to-head evidence from 15 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Claude Opus 4.6 (Adaptive) #35 (Estimated); GPT-5.4 #8 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Claude Opus 4.6 (Adaptive) and GPT-5.4 share 15 comparable benchmark results. 0 of 8 categories are comparable. 1 result is unique to Claude Opus 4.6 (Adaptive); 37 to GPT-5.4.
Updated July 23, 2026- Shared results
- 15
- Claude Opus 4.6 (Adaptive) only
- 1
- GPT-5.4 only
- 37
- Comparable categories
- 0 / 8
Benchmark data for Claude Opus 4.6 (Adaptive) and GPT-5.4 is coming soon on BenchLM.
Confidence note. This is a partial-evidence comparison with 15 shared benchmark results across 6 evidence categories; 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.
GPT-5.4 has the larger context window at 1.05M, compared with 1M for Claude Opus 4.6 (Adaptive).
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 (Adaptive) | Δ | GPT-5.4 |
|---|---|---|---|
| Agentic | Claude Opus 4.6 (Adaptive)Not measured | MarginNo overlap | GPT-5.477.2 |
| Coding | Claude Opus 4.6 (Adaptive)Not measured | MarginNo overlap | GPT-5.457.7 |
| Knowledge | Claude Opus 4.6 (Adaptive)Not measured | MarginNo overlap | GPT-5.457.6 |
| Math | Claude Opus 4.6 (Adaptive)Not measured | MarginNo overlap | GPT-5.442.5 |
| Multimodal | Claude Opus 4.6 (Adaptive)Not measured | MarginNo overlap | GPT-5.473.2 |
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Claude Opus 4.6 (Adaptive) | GPT-5.4 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Claude Opus 4.6 (Adaptive)Not available | GPT-5.4$2.5 input / $15 output | A complete price comparison is not available. |
| Generation speedtokens per second | Claude Opus 4.6 (Adaptive)Not available | GPT-5.474 tok/s | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Claude Opus 4.6 (Adaptive)Not available | GPT-5.4151.79 s | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Claude Opus 4.6 (Adaptive)1M | GPT-5.41.05M | GPT-5.4 lists the larger context window. |
Benchmark Deep Dive
Agentic17 benchmarks
| Benchmark | Claude Opus 4.6 (Adaptive) | GPT-5.4 | Result |
|---|---|---|---|
| APEX-Agents-AASource | 33.0% | 33.3% | GPT-5.4 leads |
| τ²-bench resultsSource | 92.1% | 87.1% | Claude Opus 4.6 (Adaptive) leads |
| Terminal-Bench 2.0Source | — | 75.1% | Not comparable |
| CyberGymSource | — | 79.0% | Not comparable |
| BrowseCompSource | — | 82.7% | Not comparable |
| OSWorld-VerifiedSource | — | 75% | Not comparable |
| MCP AtlasSource | — | 70.6% | Not comparable |
| ToolathlonSource | — | 54.6% | Not comparable |
| Claw-EvalSource | — | 60.3% | Not comparable |
| DeepSearchQASource | — | 73.6% | Not comparable |
| AA Agentic IndexSource | — | 41.1% | Not comparable |
| GDPval-AASource | — | 44.7% | Not comparable |
| GDPval-AASource | — | 1395 | Not comparable |
| Gert LabsSource | — | 64.89% | Not comparable |
| ResearchClawBenchSource | — | 15.3% | Not comparable |
| JobBenchSource | — | 38.9% | Not comparable |
| ExploitGymSource | — | 6.0% | Not comparable |
Coding6 benchmarks
| Benchmark | Claude Opus 4.6 (Adaptive) | GPT-5.4 | Result |
|---|---|---|---|
| Vibe Code BenchSource | 53.50% | 67.42% | GPT-5.4 leads |
| AA-SciCodeSource | 51.9% | 56.6% | GPT-5.4 leads |
| LiveCodeBench ProSource | — | 87.5% | Not comparable |
| SWE-bench ProSource | — | 57.7% | Not comparable |
| React Native EvalsSource | — | 85.3% | Not comparable |
| AA Coding IndexSource | — | 71.0% | Not comparable |
Reasoning2 benchmarks
Knowledge13 benchmarks
| Benchmark | Claude Opus 4.6 (Adaptive) | GPT-5.4 | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 43.7% | 51.4% | GPT-5.4 leads |
| AA-GPQA DiamondSource | 89.6% | 92.0% | GPT-5.4 leads |
| AA-HLESource | 36.7% | 41.6% | GPT-5.4 leads |
| AA-Omniscience IndexSource | 13.5% | 5.7% | Claude Opus 4.6 (Adaptive) leads |
| AA-Omniscience AccuracySource | 46.4% | 50.0% | GPT-5.4 leads |
| AA-Omniscience Hallucination RateSource | 61.3% | 88.6% | Claude Opus 4.6 (Adaptive) leads |
| GPQASource | — | 92.8% | Not comparable |
| HLESource | — | 52.1% | Not comparable |
| HLE w/o toolsSource | — | 39.8% | Not comparable |
| GPQA-DSource | — | 92.8% | Not comparable |
| HealthBench HardSource | — | 40.1% | Not comparable |
| MedXpertQA (Text)Source | — | 59.6% | Not comparable |
| HealthBench ProfessionalSource | — | 48.1% | Not comparable |
Math2 benchmarks
Multilingual1 benchmarks
| Benchmark | Claude Opus 4.6 (Adaptive) | GPT-5.4 | Result |
|---|---|---|---|
| AA Global-MMLU-LiteSource | 92.2% | — | Not comparable |
Multimodal11 benchmarks
| Benchmark | Claude Opus 4.6 (Adaptive) | GPT-5.4 | Result |
|---|---|---|---|
| AA-MMMU-ProSource | 75.4% | 78.4% | GPT-5.4 leads |
| Design Arena WebsiteSource | 1325 | 1250 | Claude Opus 4.6 (Adaptive) leads |
| MMMU-ProSource | — | 81.2% | Not comparable |
| OfficeQA ProSource | — | 53.2% | Not comparable |
| MMMU-Pro w/ PythonSource | — | 82.1% | Not comparable |
| CharXivSource | — | 82.8% | Not comparable |
| ERQASource | — | 65.4% | Not comparable |
| SimpleVQASource | — | 61.1% | Not comparable |
| ScreenSpot ProSource | — | 85.4% | Not comparable |
| ZeroBenchSource | — | 41.0% | Not comparable |
| MedXpertQA (MM)Source | — | 77.1% | Not comparable |
Inst. Following1 benchmarks
| Benchmark | Claude Opus 4.6 (Adaptive) | GPT-5.4 | Result |
|---|---|---|---|
| AA-IFBenchSource | 53.1% | 73.9% | GPT-5.4 leads |
Frequently Asked Questions (3)
Can I compare Claude Opus 4.6 (Adaptive) and GPT-5.4 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 4.6 (Adaptive) and GPT-5.4 today?
GPT-5.4: $2.50 input / $15.00 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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