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Model comparison

Exaone 4.0 1.2B vs MAI-Thinking-1

Data verified

Head-to-head evidence from 0 shared benchmark results across 0 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

No sourced benchmark result is currently shared by both models. This page therefore compares only the available metadata, pricing, and runtime rows; it does not name a quality winner.
LG AI Research
39.06/100
No comparison
N/A
0 category wins0 category wins

Public leaderboard positions: Exaone 4.0 1.2B #179 (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 1.2B and MAI-Thinking-1 share 0 comparable benchmark results. 0 of 8 categories are comparable. 11 results are unique to Exaone 4.0 1.2B; 13 to MAI-Thinking-1.

Updated July 23, 2026
Shared results
0
Exaone 4.0 1.2B only
11
MAI-Thinking-1 only
13
Comparable categories
0 / 8

Benchmark data for Exaone 4.0 1.2B and MAI-Thinking-1 is coming soon on BenchLM.

Confidence note. This is a partial-evidence comparison with 0 shared benchmark results across 0 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.

MAI-Thinking-1 has the larger context window at 256K, compared with 128K for Exaone 4.0 1.2B.

Operational comparison

Runtime and commercial metrics are compared only when both models have a complete sourced value.

MetricExaone 4.0 1.2BMAI-Thinking-1Comparison
Input / output priceUSD per 1M tokensExaone 4.0 1.2BNot availableMAI-Thinking-1Not availableA complete price comparison is not available.
Generation speedtokens per secondExaone 4.0 1.2BNot availableMAI-Thinking-1Not availableA complete speed comparison is not available.
First-answer latencyseconds to first tokenExaone 4.0 1.2BNot availableMAI-Thinking-1Not availableA complete latency comparison is not available.
Context windowmaximum listed tokensExaone 4.0 1.2B128KMAI-Thinking-1256KMAI-Thinking-1 lists the larger context window.

Benchmark Deep Dive

Agentic
BenchmarkExaone 4.0 1.2BMAI-Thinking-1Result
τ²-bench resultsSource 20.5%Not comparable
Terminal-Bench 2.0Source 46%Not comparable
Coding
BenchmarkExaone 4.0 1.2BMAI-Thinking-1Result
AA-SciCodeSource 7.4%Not comparable
SWE-bench VerifiedSource 73.5%Not comparable
SWE-bench ProSource 52.8%Not comparable
Terminal-Bench 2.0Source 46.0%Not comparable
Reasoning
BenchmarkExaone 4.0 1.2BMAI-Thinking-1Result
AA-LCRSource 0.0%Not comparable
CritPtSource 0.0%Not comparable
Graphwalks BFS 128KSource 90%Not comparable
Knowledge
BenchmarkExaone 4.0 1.2BMAI-Thinking-1Result
Artificial Analysis Intelligence IndexSource 2.8%Not comparable
AA-GPQA DiamondSource 42.4%Not comparable
AA-HLESource 5.8%Not comparable
AA-Omniscience IndexSource -82.6%Not comparable
AA-Omniscience AccuracySource 4.7%Not comparable
AA-Omniscience Hallucination RateSource 91.5%Not comparable
GPQASource 84.2%Not comparable
GPQA-DSource 84.2%Not comparable
MMLU-ProSource 85%Not comparable
SimpleQASource 31%Not comparable
Math
BenchmarkExaone 4.0 1.2BMAI-Thinking-1Result
AIME 2025Source 97%Not comparable
AIME26Source 94.5%Not comparable
HMMT Feb 2026Source 84.9%Not comparable
Inst. Following
BenchmarkExaone 4.0 1.2BMAI-Thinking-1Result
AA-IFBenchSource 25.3%Not comparable
IFBenchSource 85%Not comparable
Frequently Asked Questions (2)

Can I compare Exaone 4.0 1.2B and MAI-Thinking-1 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.

Related Comparisons

Last updated: July 23, 2026

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