Model comparison
Claude Sonnet 4.6 vs MAI-Thinking-1
Head-to-head evidence from 4 shared benchmark results across 3 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Claude Sonnet 4.6 #32 (Supported); MAI-Thinking-1 unranked (Not scored). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Claude Sonnet 4.6 and MAI-Thinking-1 share 4 comparable benchmark results. 4 of 8 categories are comparable. 29 results are unique to Claude Sonnet 4.6; 9 to MAI-Thinking-1.
Updated July 23, 2026- Shared results
- 4
- Claude Sonnet 4.6 only
- 29
- MAI-Thinking-1 only
- 9
- Comparable categories
- 4 / 8
Treat this as a split decision. Claude Sonnet 4.6 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 4 shared benchmark results across 3 evidence categories; 4 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
Claude Sonnet 4.6 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 Sonnet 4.6 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 Sonnet 4.6.
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 Sonnet 4.6 | Δ | MAI-Thinking-1 |
|---|---|---|---|
| Math | Claude Sonnet 4.626.4 | Margin→ 63.3 | MAI-Thinking-189.7 |
| Agentic | Claude Sonnet 4.665.2 | Margin← 19.2 | MAI-Thinking-146.0 |
| Knowledge | Claude Sonnet 4.666.0 | Margin→ 6.5 | MAI-Thinking-172.5 |
| Coding | Claude Sonnet 4.669.1 | Margin← 3.6 | MAI-Thinking-165.5 |
| Multimodal | Claude Sonnet 4.677.4 | MarginNo overlap | MAI-Thinking-1Not measured |
| Inst. Following | Claude Sonnet 4.6Not measured | MarginNo overlap | MAI-Thinking-185.0 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
Terminal-Bench 2.0
AgenticA 59.1%B 46%Winner: Claude Sonnet 4.6Δ 13.1Terminal-Bench 2.0: Claude Sonnet 4.6 scored 59.1%; MAI-Thinking-1 scored 46%. Claude Sonnet 4.6 wins this benchmark. - Source ↗
SWE-bench Verified
CodingA 79.6%B 73.5%Winner: Claude Sonnet 4.6Δ 6.1SWE-bench Verified: Claude Sonnet 4.6 scored 79.6%; MAI-Thinking-1 scored 73.5%. Claude Sonnet 4.6 wins this benchmark. - Source ↗
MMLU-Pro
KnowledgeA 79.2%B 85%Winner: MAI-Thinking-1Δ 5.8MMLU-Pro: Claude Sonnet 4.6 scored 79.2%; MAI-Thinking-1 scored 85%. MAI-Thinking-1 wins this benchmark. - Source ↗
GPQA
KnowledgeA 89.9%B 84.2%Winner: Claude Sonnet 4.6Δ 5.7GPQA: Claude Sonnet 4.6 scored 89.9%; MAI-Thinking-1 scored 84.2%. Claude Sonnet 4.6 wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Claude Sonnet 4.6 | MAI-Thinking-1 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Claude Sonnet 4.6$3 input / $15 output | MAI-Thinking-1Not available | A complete price comparison is not available. |
| Generation speedtokens per second | Claude Sonnet 4.644 tok/s | MAI-Thinking-1Not available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Claude Sonnet 4.61.48 s | MAI-Thinking-1Not available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Claude Sonnet 4.6200K | MAI-Thinking-1256K | MAI-Thinking-1 lists the larger context window. |
Benchmark Deep Dive
AgenticClaude Sonnet 4.6 wins8 benchmarks
| Benchmark | Claude Sonnet 4.6 | MAI-Thinking-1 | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 59.1% | 46% | Claude Sonnet 4.6 leads |
| OSWorld-VerifiedSource | 72.1% | — | Not comparable |
| Claw-EvalSource | 67.8% | — | Not comparable |
| CyberGymSource | 65.2% | — | Not comparable |
| τ²-bench resultsSource | 79.5% | — | Not comparable |
| Gert LabsSource | 62.92% | — | Not comparable |
| OSWorld 2.0Source | 8.3% | — | Not comparable |
| JobBenchSource | 36.9% | — | Not comparable |
CodingClaude Sonnet 4.6 wins9 benchmarks
| Benchmark | Claude Sonnet 4.6 | MAI-Thinking-1 | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | 79.6% | 73.5% | Claude Sonnet 4.6 leads |
| SWE-RebenchSource | 60.7% | — | Not comparable |
| React Native EvalsSource | 80.6% | — | Not comparable |
| Vibe Code BenchSource | 51.48% | — | Not comparable |
| cursorBench31Source | 48.8% | — | Not comparable |
| AA-SciCodeSource | 46.9% | — | Not comparable |
| FrontierCode 1.1 MainSource | 24.3% | — | Not comparable |
| SWE-bench ProSource | — | 52.8% | Not comparable |
| Terminal-Bench 2.0Source | — | 46.0% | Not comparable |
Reasoning3 benchmarks
KnowledgeMAI-Thinking-1 wins12 benchmarks
| Benchmark | Claude Sonnet 4.6 | MAI-Thinking-1 | Result |
|---|---|---|---|
| GPQASource | 89.9% | 84.2% | Claude Sonnet 4.6 leads |
| SuperGPQASource | 95% | — | Not comparable |
| MMLU-ProSource | 79.2% | 85% | MAI-Thinking-1 leads |
| HLESource | 49% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 35.9% | — | Not comparable |
| AA-GPQA DiamondSource | 79.9% | — | Not comparable |
| AA-HLESource | 13.2% | — | Not comparable |
| AA-Omniscience IndexSource | -2.9% | — | Not comparable |
| AA-Omniscience AccuracySource | 38.0% | — | Not comparable |
| AA-Omniscience Hallucination RateSource | 65.9% | — | Not comparable |
| GPQA-DSource | — | 84.2% | Not comparable |
| SimpleQASource | — | 31% | Not comparable |
MathMAI-Thinking-1 wins5 benchmarks
Multimodal3 benchmarks
Frequently Asked Questions (5)
Which is better, Claude Sonnet 4.6 or MAI-Thinking-1?
Claude Sonnet 4.6 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 Sonnet 4.6 or MAI-Thinking-1?
MAI-Thinking-1 has the edge for knowledge tasks in this comparison, averaging 72.5 versus 66. Inside this category, MMLU-Pro is the benchmark that creates the most daylight between them.
Which is better for coding, Claude Sonnet 4.6 or MAI-Thinking-1?
Claude Sonnet 4.6 has the edge for coding in this comparison, averaging 69.1 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 Sonnet 4.6 or MAI-Thinking-1?
MAI-Thinking-1 has the edge for math in this comparison, averaging 89.7 versus 26.4. Claude Sonnet 4.6 stays close enough that the answer can still flip depending on your workload.
Which is better for agentic tasks, Claude Sonnet 4.6 or MAI-Thinking-1?
Claude Sonnet 4.6 has the edge for agentic tasks in this comparison, averaging 65.2 versus 46. Inside this category, Terminal-Bench 2.0 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.