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Model comparison

Exaone 4.0 32B vs Ornith-1.0-397B

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
40.26/100
Margin
31.7pts
winning →
DeepReinforce AI
72/100
0 category wins0 category wins

Public leaderboard positions: Exaone 4.0 32B #168 (Estimated); Ornith-1.0-397B unranked (Not scored). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. Exaone 4.0 32B and Ornith-1.0-397B share 0 comparable benchmark results. 0 of 8 categories are comparable. 14 results are unique to Exaone 4.0 32B; 7 to Ornith-1.0-397B.

Updated July 17, 2026
Shared results
0
Exaone 4.0 32B only
14
Ornith-1.0-397B only
7
Comparable categories
0 / 8

Benchmark data for Exaone 4.0 32B and Ornith-1.0-397B 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.

Ornith-1.0-397B has the larger context window at 256K, compared with 128K for Exaone 4.0 32B.

Operational comparison

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

MetricExaone 4.0 32BOrnith-1.0-397BComparison
Input / output priceUSD per 1M tokensExaone 4.0 32BNot availableOrnith-1.0-397B$0 input / $0 outputA complete price comparison is not available.
Generation speedtokens per secondExaone 4.0 32BNot availableOrnith-1.0-397BNot availableA complete speed comparison is not available.
First-answer latencyseconds to first tokenExaone 4.0 32BNot availableOrnith-1.0-397BNot availableA complete latency comparison is not available.
Context windowmaximum listed tokensExaone 4.0 32B128KOrnith-1.0-397B256KOrnith-1.0-397B lists the larger context window.

Benchmark Deep Dive

Agentic
BenchmarkExaone 4.0 32BOrnith-1.0-397BResult
τ²-bench resultsSource 4.1%Not comparable
Terminal-Bench 2.0Source 77.5%Not comparable
Claw-EvalSource 77.1%Not comparable
Coding
BenchmarkExaone 4.0 32BOrnith-1.0-397BResult
Terminal-Bench HardSource 1.5%Not comparable
AA-SciCodeSource 25.2%Not comparable
SWE-bench VerifiedSource 82.4%Not comparable
SWE-bench ProSource 62.2%Not comparable
SWE MultilingualSource 78.9%Not comparable
NL2RepoSource 48.2%Not comparable
Terminal-Bench 2.0Source 77.5%Not comparable
Reasoning
BenchmarkExaone 4.0 32BOrnith-1.0-397BResult
AA-LCRSource 8.0%Not comparable
CritPtSource 0.0%Not comparable
Knowledge
BenchmarkExaone 4.0 32BOrnith-1.0-397BResult
MMLU-ProSource 81.8%Not comparable
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
Math
BenchmarkExaone 4.0 32BOrnith-1.0-397BResult
AIME 2025Source 85.3%Not comparable
Inst. Following
BenchmarkExaone 4.0 32BOrnith-1.0-397BResult
AA-IFBenchSource 33.5%Not comparable
Frequently Asked Questions (3)

Can I compare Exaone 4.0 32B and Ornith-1.0-397B 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.

What data is available for Exaone 4.0 32B and Ornith-1.0-397B today?

Ornith-1.0-397B: $0.00 input / $0.00 output per 1M tokens Both model pages still include creator, context window, reasoning mode, and other metadata while benchmark coverage fills in.

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Last updated: July 17, 2026

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