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Model comparison

Ling 2.6 Flash vs o3-mini

Data verified

Head-to-head evidence from 6 shared benchmark results across 3 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

InclusionAI
43.87/100
Margin
3.5pts
winning →
OpenAI
47.41/100
0 category wins3 category wins

Public leaderboard positions: Ling 2.6 Flash #154 (Estimated); o3-mini #136 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. Ling 2.6 Flash and o3-mini share 6 comparable benchmark results. 3 of 8 categories are comparable. 12 results are unique to Ling 2.6 Flash; 4 to o3-mini.

Updated July 21, 2026
Shared results
6
Ling 2.6 Flash only
12
o3-mini only
4
Comparable categories
3 / 8

Pick o3-mini if you want the stronger benchmark profile. Ling 2.6 Flash only becomes the better choice if you need the larger 262K context window or you would rather avoid the extra latency and token burn of a reasoning model.

Confidence note. This is a partial-evidence comparison with 6 shared benchmark results across 3 evidence categories; 3 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.

Why this result

o3-mini is clearly ahead on the BenchAlign aggregate, 47.41 to 43.87. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.

o3-mini's sharpest advantage is in instruction following, where it averages 93.9 against 57. The single biggest benchmark swing on the page is GPQA, 59% to 77.2%.

o3-mini is the reasoning model in the pair, while Ling 2.6 Flash is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use. Ling 2.6 Flash gives you the larger context window at 262K, compared with 200K for o3-mini.

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 scores and score margins for Ling 2.6 Flash and o3-mini
CategoryLing 2.6 FlashΔo3-mini
Inst. FollowingLing 2.6 Flash57.0Margin 36.9o3-mini93.9
CodingLing 2.6 Flash27.0Margin 22.3o3-mini49.3
KnowledgeLing 2.6 Flash59.0Margin 18.2o3-mini77.2

Decisive benchmark drivers

The largest measured benchmark gaps in this matchup, with exact reported values.

More
A · Ling 2.6 FlashB · o3-mini
  1. GPQA

    Knowledge
    Source ↗
    A 59%B 77.2%
    Winner: o3-miniΔ 18.2
    GPQA: Ling 2.6 Flash scored 59%; o3-mini scored 77.2%. o3-mini wins this benchmark.

Operational comparison

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

MetricLing 2.6 Flasho3-miniComparison
Input / output priceUSD per 1M tokensLing 2.6 FlashNot availableo3-mini$1.1 input / $4.4 outputA complete price comparison is not available.
Generation speedtokens per secondLing 2.6 Flash209.5 tok/so3-mini160 tok/sLing 2.6 Flash has the higher measured throughput.
First-answer latencyseconds to first tokenLing 2.6 Flash1.07 so3-mini7.12 sLing 2.6 Flash reaches the first token sooner.
Context windowmaximum listed tokensLing 2.6 Flash262Ko3-mini200KLing 2.6 Flash lists the larger context window.

Benchmark Deep Dive

Agentic
BenchmarkLing 2.6 Flasho3-miniResult
τ²-bench resultsSource 86%28.7%Ling 2.6 Flash leads
GDPval-AASource 2.2%Not comparable
GDPval-AASource 545Not comparable
AA Agentic IndexSource 2.3%Not comparable
Codingo3-mini wins
BenchmarkLing 2.6 Flasho3-miniResult
SciCodeSource 27%Not comparable
AA Coding IndexSource 25.3%Not comparable
AA-SciCodeSource 27.1%39.9%o3-mini leads
SWE-bench VerifiedSource 49.3%Not comparable
Reasoning
BenchmarkLing 2.6 Flasho3-miniResult
AA-LCRSource 25.0%Not comparable
CritPtSource 0.0%Not comparable
Knowledgeo3-mini wins
BenchmarkLing 2.6 Flasho3-miniResult
Artificial Analysis Intelligence IndexSource 14.1%19.0%o3-mini leads
GPQASource 59%77.2%o3-mini leads
AA-GPQA DiamondSource 59.3%74.8%o3-mini leads
AA-HLESource 6.2%8.7%o3-mini leads
AA-Omniscience IndexSource -65.7%Not comparable
AA-Omniscience AccuracySource 15.4%Not comparable
AA-Omniscience Hallucination RateSource 95.8%Not comparable
MMLUSource 86.9%Not comparable
Math
BenchmarkLing 2.6 Flasho3-miniResult
AIME 2024Source 87.3%Not comparable
Inst. Followingo3-mini wins
BenchmarkLing 2.6 Flasho3-miniResult
IFBenchSource 57%Not comparable
AA-IFBenchSource 57.4%Not comparable
IFEvalSource 93.9%Not comparable
Frequently Asked Questions (4)

Which is better, Ling 2.6 Flash or o3-mini?

o3-mini is ahead on BenchLM's BenchAlign leaderboard, 47.41 to 43.87. The biggest single separator in this matchup is GPQA, where the scores are 59% and 77.2%.

Which is better for knowledge tasks, Ling 2.6 Flash or o3-mini?

o3-mini has the edge for knowledge tasks in this comparison, averaging 77.2 versus 59. Inside this category, GPQA is the benchmark that creates the most daylight between them.

Which is better for coding, Ling 2.6 Flash or o3-mini?

o3-mini has the edge for coding in this comparison, averaging 49.3 versus 27. Inside this category, AA-SciCode is the benchmark that creates the most daylight between them.

Which is better for instruction following, Ling 2.6 Flash or o3-mini?

o3-mini has the edge for instruction following in this comparison, averaging 93.9 versus 57. Ling 2.6 Flash stays close enough that the answer can still flip depending on your workload.

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Last updated: July 21, 2026

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