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Model comparison

LFM2.5-230M vs Ling 2.6 Flash

Data verified

Head-to-head evidence from 2 shared benchmark results across 2 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

LiquidAI
N/A
No comparison
InclusionAI
43.87/100
0 category wins2 category wins

Public leaderboard positions: LFM2.5-230M unranked (Not scored); Ling 2.6 Flash #154 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. LFM2.5-230M and Ling 2.6 Flash share 2 comparable benchmark results. 2 of 8 categories are comparable. 4 results are unique to LFM2.5-230M; 16 to Ling 2.6 Flash.

Updated July 23, 2026
Shared results
2
LFM2.5-230M only
4
Ling 2.6 Flash only
16
Comparable categories
2 / 8

Treat this as a split decision. LFM2.5-230M makes more sense if its workflow fits your team better; Ling 2.6 Flash is the better fit if knowledge is the priority or you need the larger 262K context window.

Confidence note. This is a partial-evidence comparison with 2 shared benchmark results across 2 evidence categories; 2 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.

Why this result

LFM2.5-230M and Ling 2.6 Flash finish on the same BenchAlign overall score, so this is less about a single winner and more about where the edge shows up. The BenchAlign headline says tie; the benchmark table is where the real choice happens.

Ling 2.6 Flash gives you the larger context window at 262K, compared with 32K for LFM2.5-230M.

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 LFM2.5-230M and Ling 2.6 Flash
CategoryLFM2.5-230MΔLing 2.6 Flash
KnowledgeLFM2.5-230M21.2Margin 37.8Ling 2.6 Flash59.0
Inst. FollowingLFM2.5-230M50.1Margin 6.9Ling 2.6 Flash57.0
CodingLFM2.5-230MNot measuredMarginNo overlapLing 2.6 Flash27.0

Decisive benchmark drivers

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

More
A · LFM2.5-230MB · Ling 2.6 Flash
  1. GPQA

    Knowledge
    Source ↗
    A 25.4%B 59%
    Winner: Ling 2.6 FlashΔ 33.6
    GPQA: LFM2.5-230M scored 25.4%; Ling 2.6 Flash scored 59%. Ling 2.6 Flash wins this benchmark.
  2. IFBench

    Inst. Following
    Source ↗
    A 38.4%B 57%
    Winner: Ling 2.6 FlashΔ 18.6
    IFBench: LFM2.5-230M scored 38.4%; Ling 2.6 Flash scored 57%. Ling 2.6 Flash wins this benchmark.

Operational comparison

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

MetricLFM2.5-230MLing 2.6 FlashComparison
Input / output priceUSD per 1M tokensLFM2.5-230M$0 input / $0 outputLing 2.6 FlashNot availableA complete price comparison is not available.
Generation speedtokens per secondLFM2.5-230MNot availableLing 2.6 Flash209.5 tok/sA complete speed comparison is not available.
First-answer latencyseconds to first tokenLFM2.5-230MNot availableLing 2.6 Flash1.07 sA complete latency comparison is not available.
Context windowmaximum listed tokensLFM2.5-230M32KLing 2.6 Flash262KLing 2.6 Flash lists the larger context window.

Benchmark Deep Dive

Agentic
BenchmarkLFM2.5-230MLing 2.6 FlashResult
BFCL v4Source 21.0%Not comparable
τ²-bench resultsSource 86%Not comparable
GDPval-AASource 2.2%Not comparable
GDPval-AASource 545Not comparable
AA Agentic IndexSource 2.3%Not comparable
Coding
BenchmarkLFM2.5-230MLing 2.6 FlashResult
SciCodeSource 27%Not comparable
AA Coding IndexSource 25.3%Not comparable
AA-SciCodeSource 27.1%Not comparable
Reasoning
BenchmarkLFM2.5-230MLing 2.6 FlashResult
AA-LCRSource 25.0%Not comparable
CritPtSource 0.0%Not comparable
KnowledgeLing 2.6 Flash wins
BenchmarkLFM2.5-230MLing 2.6 FlashResult
GPQASource 25.4%59%Ling 2.6 Flash leads
GPQA-DSource 25.4%Not comparable
MMLU-ProSource 20.3%Not comparable
Artificial Analysis Intelligence IndexSource 14.1%Not comparable
AA-GPQA DiamondSource 59.3%Not comparable
AA-HLESource 6.2%Not comparable
AA-Omniscience IndexSource -65.7%Not comparable
AA-Omniscience AccuracySource 15.4%Not comparable
AA-Omniscience Hallucination RateSource 95.8%Not comparable
Inst. FollowingLing 2.6 Flash wins
BenchmarkLFM2.5-230MLing 2.6 FlashResult
IFEvalSource 71.7%Not comparable
IFBenchSource 38.4%57%Ling 2.6 Flash leads
AA-IFBenchSource 57.4%Not comparable
Frequently Asked Questions (3)

Which is better, LFM2.5-230M or Ling 2.6 Flash?

LFM2.5-230M and Ling 2.6 Flash are tied on the BenchAlign overall score, so the right pick depends on which category matters most for your use case.

Which is better for knowledge tasks, LFM2.5-230M or Ling 2.6 Flash?

Ling 2.6 Flash has the edge for knowledge tasks in this comparison, averaging 59 versus 21.2. Inside this category, GPQA is the benchmark that creates the most daylight between them.

Which is better for instruction following, LFM2.5-230M or Ling 2.6 Flash?

Ling 2.6 Flash has the edge for instruction following in this comparison, averaging 57 versus 50.1. Inside this category, IFBench is the benchmark that creates the most daylight between them.

Related Comparisons

Last updated: July 23, 2026

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