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Model comparison

K-Exaone vs Phi-4

Data verified

Head-to-head evidence from 12 shared benchmark results across 5 categories. Overall scores shown here use BenchLM's provisional ranking lane.

LG AI Research
53/100
Margin
27.0pts
← winning
Microsoft
26/100
0 category wins0 category wins

Evidence parity. K-Exaone and Phi-4 share 12 comparable benchmark results. 0 of 8 categories are comparable. 0 results are unique to K-Exaone; 0 to Phi-4.

Updated July 14, 2026
Shared results
12
K-Exaone only
0
Phi-4 only
0
Comparable categories
0 / 8

Benchmark data for K-Exaone and Phi-4 is coming soon on BenchLM.

Confidence note. This is a partial-evidence comparison with 12 shared benchmark results across 5 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.

K-Exaone has the larger context window at 256K, compared with 16K for Phi-4.

Category breakdown

Exact category averages are shown below. Not measured means BenchLM does not have enough sourced public coverage for that model and category.

Operational comparison

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

MetricK-ExaonePhi-4Comparison
Input / output priceUSD per 1M tokensK-ExaoneNot availablePhi-4$0 input / $0 outputA complete price comparison is not available.
Generation speedtokens per secondK-ExaoneNot availablePhi-435 tok/sA complete speed comparison is not available.
First-answer latencyseconds to first tokenK-ExaoneNot availablePhi-42.02 sA complete latency comparison is not available.
Context windowmaximum listed tokensK-Exaone256KPhi-416KK-Exaone lists the larger context window.

Benchmark Deep Dive

Agentic
BenchmarkK-ExaonePhi-4Result
Tau2-TelecomSource 74.3%0%K-Exaone leads
Coding
BenchmarkK-ExaonePhi-4Result
Terminal-Bench HardSource 22.7%3.8%K-Exaone leads
AA-SciCodeSource 35.6%26.0%K-Exaone leads
Reasoning
BenchmarkK-ExaonePhi-4Result
AA-LCRSource 55.7%0.0%K-Exaone leads
CritPtSource 1.1%0.0%K-Exaone leads
Knowledge
BenchmarkK-ExaonePhi-4Result
Artificial Analysis Intelligence IndexSource 24.7%4.9%K-Exaone leads
AA-GPQA DiamondSource 78.3%57.5%K-Exaone leads
AA-HLESource 13.1%4.1%K-Exaone leads
AA-Omniscience IndexSource -57.9%-56.7%Phi-4 leads
AA-Omniscience AccuracySource 16.5%13.2%K-Exaone leads
AA-Omniscience Hallucination RateSource 89.1%80.5%Phi-4 leads
Inst. Following
BenchmarkK-ExaonePhi-4Result
AA-IFBenchSource 64.7%23.5%K-Exaone leads
Frequently Asked Questions (3)

Can I compare K-Exaone and Phi-4 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 K-Exaone and Phi-4 today?

Phi-4: $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 14, 2026

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