Skip to main content

Model comparison

Granite-4.0-350M vs K-Exaone

Data verified

Head-to-head evidence from 11 shared benchmark results across 5 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

38.32/100
Margin
10.1pts
winning →
LG AI Research
48.45/100
0 category wins0 category wins

Public leaderboard positions: Granite-4.0-350M #181 (Estimated); K-Exaone #126 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. Granite-4.0-350M and K-Exaone share 11 comparable benchmark results. 0 of 8 categories are comparable. 0 results are unique to Granite-4.0-350M; 0 to K-Exaone.

Updated July 18, 2026
Shared results
11
Granite-4.0-350M only
0
K-Exaone only
0
Comparable categories
0 / 8

Benchmark data for Granite-4.0-350M and K-Exaone is coming soon on BenchLM.

Confidence note. This is a partial-evidence comparison with 11 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 32K for Granite-4.0-350M.

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.

MetricGranite-4.0-350MK-ExaoneComparison
Input / output priceUSD per 1M tokensGranite-4.0-350M$0 input / $0 outputK-ExaoneNot availableA complete price comparison is not available.
Generation speedtokens per secondGranite-4.0-350MNot availableK-ExaoneNot availableA complete speed comparison is not available.
First-answer latencyseconds to first tokenGranite-4.0-350MNot availableK-ExaoneNot availableA complete latency comparison is not available.
Context windowmaximum listed tokensGranite-4.0-350M32KK-Exaone256KK-Exaone lists the larger context window.

Benchmark Deep Dive

Agentic
BenchmarkGranite-4.0-350MK-ExaoneResult
τ²-bench resultsSource 13.2%74.3%K-Exaone leads
Coding
BenchmarkGranite-4.0-350MK-ExaoneResult
AA-SciCodeSource 0.9%35.6%K-Exaone leads
Reasoning
BenchmarkGranite-4.0-350MK-ExaoneResult
AA-LCRSource 0.0%55.7%K-Exaone leads
CritPtSource 0.0%1.1%K-Exaone leads
Knowledge
BenchmarkGranite-4.0-350MK-ExaoneResult
Artificial Analysis Intelligence IndexSource 1.0%24.7%K-Exaone leads
AA-GPQA DiamondSource 26.1%78.3%K-Exaone leads
AA-HLESource 5.7%13.1%K-Exaone leads
AA-Omniscience IndexSource -72.1%-57.9%K-Exaone leads
AA-Omniscience AccuracySource 3.2%16.5%K-Exaone leads
AA-Omniscience Hallucination RateSource 77.8%89.1%Granite-4.0-350M leads
Inst. Following
BenchmarkGranite-4.0-350MK-ExaoneResult
AA-IFBenchSource 15.9%64.7%K-Exaone leads
Frequently Asked Questions (3)

Can I compare Granite-4.0-350M and K-Exaone 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 Granite-4.0-350M and K-Exaone today?

Granite-4.0-350M: $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.

Related Comparisons

Last updated: July 18, 2026

The AI models change fast. We track them for you.

A weekly brief for engineers and researchers covering new models, ranking shifts, and pricing changes.

Free. No spam. Unsubscribe anytime.