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Model comparison

Ling 2.6 Flash vs Qwen3.6 Plus

Data verified

Head-to-head evidence from 17 shared benchmark results across 5 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

InclusionAI
43.87/100
Margin
21.3pts
winning →
65.2/100
1 category wins2 category wins

Public leaderboard positions: Ling 2.6 Flash #154 (Estimated); Qwen3.6 Plus #30 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. Ling 2.6 Flash and Qwen3.6 Plus share 17 comparable benchmark results. 3 of 8 categories are comparable. 1 result is unique to Ling 2.6 Flash; 43 to Qwen3.6 Plus.

Updated July 21, 2026
Shared results
17
Ling 2.6 Flash only
1
Qwen3.6 Plus only
43
Comparable categories
3 / 8

Pick Qwen3.6 Plus if you want the stronger benchmark profile. Ling 2.6 Flash only becomes the better choice if knowledge is the priority or you would rather avoid the extra latency and token burn of a reasoning model.

Confidence note. This is a partial-evidence comparison with 17 shared benchmark results across 5 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

Qwen3.6 Plus is clearly ahead on the BenchAlign aggregate, 65.2 to 43.87. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.

Qwen3.6 Plus's sharpest advantage is in coding, where it averages 70.3 against 27. The single biggest benchmark swing on the page is GPQA, 59% to 90.4%. Ling 2.6 Flash does hit back in knowledge, so the answer changes if that is the part of the workload you care about most.

Qwen3.6 Plus 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. Qwen3.6 Plus gives you the larger context window at 1M, compared with 262K for Ling 2.6 Flash.

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 Qwen3.6 Plus
CategoryLing 2.6 FlashΔQwen3.6 Plus
CodingLing 2.6 Flash27.0Margin 43.3Qwen3.6 Plus70.3
Inst. FollowingLing 2.6 Flash57.0Margin 25.3Qwen3.6 Plus82.3
KnowledgeLing 2.6 Flash59.0Margin 1.9Qwen3.6 Plus57.1
AgenticLing 2.6 FlashNot measuredMarginNo overlapQwen3.6 Plus61.6
ReasoningLing 2.6 FlashNot measuredMarginNo overlapQwen3.6 Plus62.0
MathLing 2.6 FlashNot measuredMarginNo overlapQwen3.6 Plus60.5
MultilingualLing 2.6 FlashNot measuredMarginNo overlapQwen3.6 Plus84.7
MultimodalLing 2.6 FlashNot measuredMarginNo overlapQwen3.6 Plus79.8

Decisive benchmark drivers

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

More
A · Ling 2.6 FlashB · Qwen3.6 Plus
  1. GPQA

    Knowledge
    Source ↗
    A 59%B 90.4%
    Winner: Qwen3.6 PlusΔ 31.4
    GPQA: Ling 2.6 Flash scored 59%; Qwen3.6 Plus scored 90.4%. Qwen3.6 Plus wins this benchmark.
  2. IFBench

    Inst. Following
    Source ↗
    A 57%B 75.8%
    Winner: Qwen3.6 PlusΔ 18.8
    IFBench: Ling 2.6 Flash scored 57%; Qwen3.6 Plus scored 75.8%. Qwen3.6 Plus wins this benchmark.

Operational comparison

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

MetricLing 2.6 FlashQwen3.6 PlusComparison
Input / output priceUSD per 1M tokensLing 2.6 FlashNot availableQwen3.6 PlusNot availableA complete price comparison is not available.
Generation speedtokens per secondLing 2.6 Flash209.5 tok/sQwen3.6 PlusNot availableA complete speed comparison is not available.
First-answer latencyseconds to first tokenLing 2.6 Flash1.07 sQwen3.6 PlusNot availableA complete latency comparison is not available.
Context windowmaximum listed tokensLing 2.6 Flash262KQwen3.6 Plus1MQwen3.6 Plus lists the larger context window.

Benchmark Deep Dive

Agentic
BenchmarkLing 2.6 FlashQwen3.6 PlusResult
τ²-bench resultsSource 86%97.7%Qwen3.6 Plus leads
GDPval-AASource 2.2%31.8%Qwen3.6 Plus leads
GDPval-AASource 5451135Qwen3.6 Plus leads
AA Agentic IndexSource 2.3%27.6%Qwen3.6 Plus leads
Terminal-Bench 2.0Source 61.6%Not comparable
Claw-EvalSource 58.8%Not comparable
QwenClawBenchSource 57.2%Not comparable
τ³-bench resultsSource 70.7%Not comparable
VITA-BenchSource 44.3%Not comparable
DeepPlanningSource 41.5%Not comparable
ToolathlonSource 39.8%Not comparable
MCP AtlasSource 48.2%Not comparable
MCP-TasksSource 74.1%Not comparable
WideResearchSource 74.3%Not comparable
Gert LabsSource 50.60%Not comparable
ResearchClawBenchSource 18.0%Not comparable
CodingQwen3.6 Plus wins
BenchmarkLing 2.6 FlashQwen3.6 PlusResult
SciCodeSource 27%Not comparable
AA Coding IndexSource 25.3%54.5%Qwen3.6 Plus leads
AA-SciCodeSource 27.1%40.7%Qwen3.6 Plus leads
SWE-bench VerifiedSource 78.8%Not comparable
SWE-bench ProSource 56.6%Not comparable
SWE MultilingualSource 73.8%Not comparable
LiveCodeBench v6Source 87.1%Not comparable
Vibe Code BenchSource 25.56%Not comparable
Reasoning
BenchmarkLing 2.6 FlashQwen3.6 PlusResult
AA-LCRSource 25.0%69.7%Qwen3.6 Plus leads
CritPtSource 0.0%2.9%Qwen3.6 Plus leads
AI-NeedleSource 68.3%Not comparable
LongBench v2Source 62%Not comparable
KnowledgeLing 2.6 Flash wins
BenchmarkLing 2.6 FlashQwen3.6 PlusResult
Artificial Analysis Intelligence IndexSource 14.1%39.6%Qwen3.6 Plus leads
GPQASource 59%90.4%Qwen3.6 Plus leads
AA-GPQA DiamondSource 59.3%88.2%Qwen3.6 Plus leads
AA-HLESource 6.2%25.7%Qwen3.6 Plus leads
AA-Omniscience IndexSource -65.7%2.7%Qwen3.6 Plus leads
AA-Omniscience AccuracySource 15.4%26.2%Qwen3.6 Plus leads
AA-Omniscience Hallucination RateSource 95.8%32.0%Qwen3.6 Plus leads
SuperGPQASource 71.6%Not comparable
MMLU-ProSource 88.5%Not comparable
MMLU-ReduxSource 94.5%Not comparable
C-EvalSource 93.3%Not comparable
HLESource 28.8%Not comparable
Math
BenchmarkLing 2.6 FlashQwen3.6 PlusResult
AIME26Source 95.3%Not comparable
HMMT Feb 2025Source 96.7%Not comparable
HMMT Nov 2025Source 94.6%Not comparable
HMMT Feb 2026Source 87.8%Not comparable
MMAnswerBenchSource 83.8%Not comparable
FrontierMath v2 (Tiers 1-3)Source 26.207%Not comparable
FrontierMath v2 (Tier 4)Source 8.333%Not comparable
Multilingual
BenchmarkLing 2.6 FlashQwen3.6 PlusResult
MMLU-ProXSource 84.7%Not comparable
NOVA-63Source 57.9%Not comparable
Multimodal
BenchmarkLing 2.6 FlashQwen3.6 PlusResult
MMMUSource 86.0%Not comparable
MMMU-ProSource 78.8%Not comparable
MathVisionSource 88.0%Not comparable
VideoMMMUSource 84.0%Not comparable
ScreenSpot ProSource 68.2%Not comparable
CharXivSource 81.5%Not comparable
V*Source 96.9%Not comparable
AA-MMMU-ProSource 78.0%Not comparable
Design Arena WebsiteSource 1249Not comparable
Inst. FollowingQwen3.6 Plus wins
BenchmarkLing 2.6 FlashQwen3.6 PlusResult
IFBenchSource 57%75.8%Qwen3.6 Plus leads
AA-IFBenchSource 57.4%75.2%Qwen3.6 Plus leads
IFEvalSource 94.3%Not comparable
Frequently Asked Questions (4)

Which is better, Ling 2.6 Flash or Qwen3.6 Plus?

Qwen3.6 Plus is ahead on BenchLM's BenchAlign leaderboard, 65.2 to 43.87. The biggest single separator in this matchup is GPQA, where the scores are 59% and 90.4%.

Which is better for knowledge tasks, Ling 2.6 Flash or Qwen3.6 Plus?

Ling 2.6 Flash has the edge for knowledge tasks in this comparison, averaging 59 versus 57.1. Inside this category, AA-Omniscience Index is the benchmark that creates the most daylight between them.

Which is better for coding, Ling 2.6 Flash or Qwen3.6 Plus?

Qwen3.6 Plus has the edge for coding in this comparison, averaging 70.3 versus 27. Inside this category, AA Coding Index is the benchmark that creates the most daylight between them.

Which is better for instruction following, Ling 2.6 Flash or Qwen3.6 Plus?

Qwen3.6 Plus has the edge for instruction following in this comparison, averaging 82.3 versus 57. Inside this category, IFBench is the benchmark that creates the most daylight between them.

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Last updated: July 21, 2026

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