Model comparison
Exaone 4.0 32B vs MAI-Thinking-1
Head-to-head evidence from 2 shared benchmark results across 2 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Exaone 4.0 32B #170 (Estimated); MAI-Thinking-1 unranked (Not scored). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Exaone 4.0 32B and MAI-Thinking-1 share 2 comparable benchmark results. 1 of 8 categories are comparable. 11 results are unique to Exaone 4.0 32B; 11 to MAI-Thinking-1.
Updated July 23, 2026- Shared results
- 2
- Exaone 4.0 32B only
- 11
- MAI-Thinking-1 only
- 11
- Comparable categories
- 1 / 8
Treat this as a split decision. Exaone 4.0 32B makes more sense if knowledge is the priority; MAI-Thinking-1 is the better fit if you need the larger 256K context window.
Confidence note. This is a partial-evidence comparison with 2 shared benchmark results across 2 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
Exaone 4.0 32B 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 gives you the larger context window at 256K, compared with 128K for Exaone 4.0 32B.
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 | Exaone 4.0 32B | Δ | MAI-Thinking-1 |
|---|---|---|---|
| Knowledge | Exaone 4.0 32B81.8 | Margin← 9.3 | MAI-Thinking-172.5 |
| Agentic | Exaone 4.0 32BNot measured | MarginNo overlap | MAI-Thinking-146.0 |
| Coding | Exaone 4.0 32BNot measured | MarginNo overlap | MAI-Thinking-165.5 |
| Math | Exaone 4.0 32BNot measured | MarginNo overlap | MAI-Thinking-189.7 |
| Inst. Following | Exaone 4.0 32BNot measured | MarginNo overlap | MAI-Thinking-185.0 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
MMLU-Pro
KnowledgeA 81.8%B 85%Winner: MAI-Thinking-1Δ 3.2MMLU-Pro: Exaone 4.0 32B scored 81.8%; MAI-Thinking-1 scored 85%. MAI-Thinking-1 wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Exaone 4.0 32B | MAI-Thinking-1 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Exaone 4.0 32BNot available | MAI-Thinking-1Not available | A complete price comparison is not available. |
| Generation speedtokens per second | Exaone 4.0 32BNot available | MAI-Thinking-1Not available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Exaone 4.0 32BNot available | MAI-Thinking-1Not available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Exaone 4.0 32B128K | MAI-Thinking-1256K | MAI-Thinking-1 lists the larger context window. |
Benchmark Deep Dive
Agentic2 benchmarks
Coding4 benchmarks
Reasoning3 benchmarks
KnowledgeExaone 4.0 32B wins10 benchmarks
| Benchmark | Exaone 4.0 32B | MAI-Thinking-1 | Result |
|---|---|---|---|
| MMLU-ProSource | 81.8% | 85% | MAI-Thinking-1 leads |
| Artificial Analysis Intelligence IndexSource | 6.0% | — | Not comparable |
| AA-GPQA DiamondSource | 62.8% | — | Not comparable |
| AA-HLESource | 4.9% | — | Not comparable |
| AA-Omniscience IndexSource | -62.3% | — | Not comparable |
| AA-Omniscience AccuracySource | 10.4% | — | Not comparable |
| AA-Omniscience Hallucination RateSource | 81.0% | — | Not comparable |
| GPQASource | — | 84.2% | Not comparable |
| GPQA-DSource | — | 84.2% | Not comparable |
| SimpleQASource | — | 31% | Not comparable |
Math3 benchmarks
Frequently Asked Questions (2)
Which is better, Exaone 4.0 32B or MAI-Thinking-1?
Exaone 4.0 32B 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, Exaone 4.0 32B or MAI-Thinking-1?
Exaone 4.0 32B has the edge for knowledge tasks in this comparison, averaging 81.8 versus 72.5. Inside this category, MMLU-Pro is the benchmark that creates the most daylight between them.
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