Model comparison
Claude Opus 4.7 vs MAI-Thinking-1
Head-to-head evidence from 0 shared benchmark results across 0 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Claude Opus 4.7 #12 (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 4.7 and MAI-Thinking-1 share 0 comparable benchmark results. 1 of 8 categories are comparable. 21 results are unique to Claude Opus 4.7; 13 to MAI-Thinking-1.
Updated July 23, 2026- Shared results
- 0
- Claude Opus 4.7 only
- 21
- MAI-Thinking-1 only
- 13
- Comparable categories
- 1 / 8
Treat this as a split decision. Claude Opus 4.7 makes more sense if you need the larger 1M context window 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 want the stronger reasoning-first profile.
Confidence note. This is a partial-evidence comparison with 0 shared benchmark results across 0 evidence categories; 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 4.7 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 4.7 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 4.7 gives you the larger context window at 1M, compared with 256K for MAI-Thinking-1.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Claude Opus 4.7 | MAI-Thinking-1 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Claude Opus 4.7$5 input / $25 output | MAI-Thinking-1Not available | A complete price comparison is not available. |
| Generation speedtokens per second | Claude Opus 4.7Not available | MAI-Thinking-1Not available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Claude Opus 4.7Not available | MAI-Thinking-1Not available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Claude Opus 4.71M | MAI-Thinking-1256K | Claude Opus 4.7 lists the larger context window. |
Benchmark Deep Dive
Agentic5 benchmarks
Coding7 benchmarks
| Benchmark | Claude Opus 4.7 | MAI-Thinking-1 | Result |
|---|---|---|---|
| Vibe Code BenchSource | 71.00% | — | Not comparable |
| React Native EvalsSource | 82.8% | — | Not comparable |
| AA-SciCodeSource | 50.1% | — | Not comparable |
| FrontierCode 1.1 MainSource | 38.5% | — | Not comparable |
| SWE-bench VerifiedSource | — | 73.5% | Not comparable |
| SWE-bench ProSource | — | 52.8% | Not comparable |
| Terminal-Bench 2.0Source | — | 46.0% | Not comparable |
Reasoning3 benchmarks
Knowledge10 benchmarks
| Benchmark | Claude Opus 4.7 | MAI-Thinking-1 | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 42.7% | — | Not comparable |
| AA-GPQA DiamondSource | 88.5% | — | Not comparable |
| AA-HLESource | 31.2% | — | Not comparable |
| AA-Omniscience IndexSource | 14.2% | — | Not comparable |
| AA-Omniscience AccuracySource | 43.5% | — | Not comparable |
| AA-Omniscience Hallucination RateSource | 51.9% | — | Not comparable |
| GPQASource | — | 84.2% | Not comparable |
| GPQA-DSource | — | 84.2% | Not comparable |
| MMLU-ProSource | — | 85% | Not comparable |
| SimpleQASource | — | 31% | Not comparable |
MathMAI-Thinking-1 wins5 benchmarks
Multimodal2 benchmarks
Frequently Asked Questions (2)
Which is better, Claude Opus 4.7 or MAI-Thinking-1?
Claude Opus 4.7 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 math, Claude Opus 4.7 or MAI-Thinking-1?
MAI-Thinking-1 has the edge for math in this comparison, averaging 89.7 versus 38.6. Claude Opus 4.7 stays close enough that the answer can still flip depending on your workload.
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