Model comparison
Claude Opus 4.5 vs MAI-Thinking-1
Head-to-head evidence from 8 shared benchmark results across 5 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Claude Opus 4.5 #34 (Supported); MAI-Thinking-1 unranked (Not scored). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Claude Opus 4.5 and MAI-Thinking-1 share 8 comparable benchmark results. 5 of 8 categories are comparable. 51 results are unique to Claude Opus 4.5; 5 to MAI-Thinking-1.
Updated July 23, 2026- Shared results
- 8
- Claude Opus 4.5 only
- 51
- MAI-Thinking-1 only
- 5
- Comparable categories
- 5 / 8
Treat this as a split decision. Claude Opus 4.5 makes more sense if agentic is the priority or you would rather avoid the extra latency and token burn of a reasoning model; MAI-Thinking-1 is the better fit if mathematics is the priority or you need the larger 256K context window.
Confidence note. This is a partial-evidence comparison with 8 shared benchmark results across 5 evidence categories; 5 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 4.5 and MAI-Thinking-1 finish on the same BenchAlign overall score, so this is less about a single winner and more about where the edge shows up. The BenchAlign headline says tie; the benchmark table is where the real choice happens.
MAI-Thinking-1 is the reasoning model in the pair, while Claude Opus 4.5 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. MAI-Thinking-1 gives you the larger context window at 256K, compared with 200K 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 | Claude Opus 4.5 | Δ | MAI-Thinking-1 |
|---|---|---|---|
| Math | Claude Opus 4.557.5 | Margin→ 32.2 | MAI-Thinking-189.7 |
| Agentic | Claude Opus 4.562.6 | Margin← 16.6 | MAI-Thinking-146.0 |
| Inst. Following | Claude Opus 4.569.5 | Margin→ 15.5 | MAI-Thinking-185.0 |
| Knowledge | Claude Opus 4.558.1 | Margin→ 14.4 | MAI-Thinking-172.5 |
| Coding | Claude Opus 4.571.7 | Margin← 6.2 | MAI-Thinking-165.5 |
| Reasoning | Claude Opus 4.564.4 | MarginNo overlap | MAI-Thinking-1Not measured |
| Multilingual | Claude Opus 4.585.7 | MarginNo overlap | MAI-Thinking-1Not measured |
| Multimodal | Claude Opus 4.569.9 | MarginNo overlap | MAI-Thinking-1Not measured |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
IFBench
Inst. FollowingA 58%B 85%Winner: MAI-Thinking-1Δ 27IFBench: Claude Opus 4.5 scored 58%; MAI-Thinking-1 scored 85%. MAI-Thinking-1 wins this benchmark. - Source ↗
Terminal-Bench 2.0
AgenticA 59.3%B 46%Winner: Claude Opus 4.5Δ 13.3Terminal-Bench 2.0: Claude Opus 4.5 scored 59.3%; MAI-Thinking-1 scored 46%. Claude Opus 4.5 wins this benchmark. - Source ↗
SWE-bench Verified
CodingA 80.9%B 73.5%Winner: Claude Opus 4.5Δ 7.4SWE-bench Verified: Claude Opus 4.5 scored 80.9%; MAI-Thinking-1 scored 73.5%. Claude Opus 4.5 wins this benchmark. - Source ↗
MMLU-Pro
KnowledgeA 89.5%B 85%Winner: Claude Opus 4.5Δ 4.5MMLU-Pro: Claude Opus 4.5 scored 89.5%; MAI-Thinking-1 scored 85%. Claude Opus 4.5 wins this benchmark. - Source ↗
SWE-bench Pro
CodingA 57.1%B 52.8%Winner: Claude Opus 4.5Δ 4.3SWE-bench Pro: Claude Opus 4.5 scored 57.1%; MAI-Thinking-1 scored 52.8%. Claude Opus 4.5 wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Claude Opus 4.5 | MAI-Thinking-1 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Claude Opus 4.5$5 input / $25 output | MAI-Thinking-1Not available | A complete price comparison is not available. |
| Generation speedtokens per second | Claude Opus 4.546 tok/s | MAI-Thinking-1Not available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Claude Opus 4.51.01 s | MAI-Thinking-1Not available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Claude Opus 4.5200K | MAI-Thinking-1256K | MAI-Thinking-1 lists the larger context window. |
Benchmark Deep Dive
AgenticClaude Opus 4.5 wins16 benchmarks
| Benchmark | Claude Opus 4.5 | MAI-Thinking-1 | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 59.3% | 46% | Claude Opus 4.5 leads |
| 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 |
CodingClaude Opus 4.5 wins7 benchmarks
| Benchmark | Claude Opus 4.5 | MAI-Thinking-1 | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | 80.9% | 73.5% | Claude Opus 4.5 leads |
| LiveCodeBench v6Source | 84.8% | — | Not comparable |
| SWE-bench ProSource | 57.1% | 52.8% | Claude Opus 4.5 leads |
| SWE MultilingualSource | 77.5% | — | Not comparable |
| NL2RepoSource | 43.2% | — | Not comparable |
| AA-SciCodeSource | 47.0% | — | Not comparable |
| Terminal-Bench 2.0Source | — | 46.0% | Not comparable |
Reasoning5 benchmarks
KnowledgeMAI-Thinking-1 wins15 benchmarks
| Benchmark | Claude Opus 4.5 | MAI-Thinking-1 | Result |
|---|---|---|---|
| GPQASource | 87% | 84.2% | Claude Opus 4.5 leads |
| SuperGPQASource | 70.6% | — | Not comparable |
| MMLU-ProSource | 89.5% | 85% | Claude Opus 4.5 leads |
| MMLU-ReduxSource | 96.6% | — | Not comparable |
| C-EvalSource | 92.2% | — | Not comparable |
| HLESource | 30.8% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 34.7% | — | Not comparable |
| AA-GPQA DiamondSource | 81.0% | — | Not comparable |
| 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 |
| GPQA-DSource | — | 84.2% | Not comparable |
| SimpleQASource | — | 31% | Not comparable |
MathMAI-Thinking-1 wins8 benchmarks
| Benchmark | Claude Opus 4.5 | MAI-Thinking-1 | Result |
|---|---|---|---|
| AIME26Source | 95.1% | 94.5% | Claude Opus 4.5 leads |
| HMMT Feb 2025Source | 92.9% | — | Not comparable |
| HMMT Nov 2025Source | 93.3% | — | Not comparable |
| HMMT Feb 2026Source | 85.3% | 84.9% | Claude Opus 4.5 leads |
| MMAnswerBenchSource | 84.0% | — | Not comparable |
| FrontierMath v2 (Tiers 1-3)Source | 20.690% | — | Not comparable |
| FrontierMath v2 (Tier 4)Source | 4.167% | — | Not comparable |
| AIME 2025Source | — | 97% | Not comparable |
Multilingual2 benchmarks
Multimodal8 benchmarks
| Benchmark | Claude Opus 4.5 | MAI-Thinking-1 | Result |
|---|---|---|---|
| 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 |
Frequently Asked Questions (6)
Which is better, Claude Opus 4.5 or MAI-Thinking-1?
Claude Opus 4.5 and MAI-Thinking-1 are tied on the BenchAlign overall score, so the right pick depends on which category matters most for your use case.
Which is better for knowledge tasks, Claude Opus 4.5 or MAI-Thinking-1?
MAI-Thinking-1 has the edge for knowledge tasks in this comparison, averaging 72.5 versus 58.1. Inside this category, MMLU-Pro is the benchmark that creates the most daylight between them.
Which is better for coding, Claude Opus 4.5 or MAI-Thinking-1?
Claude Opus 4.5 has the edge for coding in this comparison, averaging 71.7 versus 65.5. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
Which is better for math, Claude Opus 4.5 or MAI-Thinking-1?
MAI-Thinking-1 has the edge for math in this comparison, averaging 89.7 versus 57.5. Inside this category, AIME26 is the benchmark that creates the most daylight between them.
Which is better for agentic tasks, Claude Opus 4.5 or MAI-Thinking-1?
Claude Opus 4.5 has the edge for agentic tasks in this comparison, averaging 62.6 versus 46. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
Which is better for instruction following, Claude Opus 4.5 or MAI-Thinking-1?
MAI-Thinking-1 has the edge for instruction following in this comparison, averaging 85 versus 69.5. Inside this category, IFBench is the benchmark that creates the most daylight between them.
Related Comparisons
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.