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Model profile

Ling 2.6 Flash

InclusionAICurrentReleased Apr 21, 2026
Data verified
Overall Score
43.87Public #154 of 200
Arena Elo
Not listed
Eligible category ranks
3of 8
Price (1M tokens)
Not listedAPI pricing
Speed
209.5tok/s
Context
262K

Evidence coverage

18 of 323 tracked benchmarks are published. 0 are verified and 18 provisional. 5 of 8 categories are measured.

Updated July 21, 2026Methodology
Published / tracked
18 / 323
Verified
0
Provisional
18
Categories with evidence
5 / 8

Evidence by category

  • Agentic4 benchmarks
    Reported
  • Coding3 benchmarks
    Reported
  • Reasoning2 benchmarks
    Reported
  • Knowledge7 benchmarks
    Reported
  • Math0 benchmarks
    Not measured
  • Multilingual0 benchmarks
    Not measured
  • Multimodal0 benchmarks
    Not measured
  • Inst. Following2 benchmarks
    Reported
Open WeightSelf-hostNon-Reasoning
Confidence:
Low
flash

Ling 2.6 Flash ranks #154 out of 200 models on the public leaderboard with an overall score of 43.87/100. It does not yet have enough sourced coverage for BenchLM's verified leaderboard. While not a frontier model, it offers specific advantages depending on the use case.

Ling 2.6 Flash is a open weight model with a 262K token context window. It processes queries without explicit chain-of-thought reasoning, offering faster response times and lower token usage.

This profile currently has 18 of 323 tracked benchmarks. BenchLM only exposes non-generated benchmark rows publicly, so missing categories stay blank until a sourced evaluation is available.

Its strongest category is Instruction Following (#25), while its weakest is Coding (#93). This performance profile makes it a well-rounded choice across a range of tasks.

Peer position

Exact provisional scores and ranks for the closest listed peers. A score can appear before a model clears the evidence threshold for a rank, so equal scores can have different rank states.

Range 43.244.4

  1. Nemotron Ultra 253B
    NVIDIA
    #15044.4
    Nemotron Ultra 253B is #150 with a score of 44.4.
    Compare
  2. Nemotron 3 Nano Omni 30B A3B
    NVIDIA
    #15144.24
    Nemotron 3 Nano Omni 30B A3B is #151 with a score of 44.24.
    Compare
  3. GPT-4.1 mini
    OpenAI
    #15244.19
    GPT-4.1 mini is #152 with a score of 44.19.
    Compare
  4. GPT-5 mini
    OpenAI
    #15343.93
    GPT-5 mini is #153 with a score of 43.93.
    Compare
  5. Ling 2.6 FlashCurrent model
    InclusionAI
    #15443.87
    Ling 2.6 Flash is #154 with a score of 43.87.
  6. Gemma 4 E4B
    Google
    #15543.2
    Gemma 4 E4B is #155 with a score of 43.2.
    Compare
  7. Mistral Medium 3
    Mistral
    #15643.2
    Mistral Medium 3 is #156 with a score of 43.2.
    Compare

Category percentile

More

Relative position among models eligible for each sourced category. A higher percentile means a stronger position within that category's ranked cohort; 100 is highest.

  1. Inst. Following20%
    Eligible cohort rank #25 of 31Category score 48.2
  2. Agentic24%
    Eligible cohort rank #91 of 119Category score 41.0
  3. Coding24%
    Eligible cohort rank #93 of 122Category score 45.4

Category evidence

Scores and ranks appear only where this model has published benchmark evidence. Categories without displayable source records remain not measured.

Category scores, ranks, weighting, benchmark coverage, and evidence status
CategoryScore
AgenticRank #91 of 119Percentile 24thWeight 22%4 benchmarksReported41.0
CodingRank #93 of 122Percentile 24thWeight 20%3 benchmarksReported45.4
ReasoningWeight 17%2 benchmarksReportedScore pending
KnowledgeRank Not rankedWeight 12%7 benchmarksReported47.8
MathWeight 5%0 benchmarksNot measuredNot measured
MultilingualWeight 7%0 benchmarksNot measuredNot measured
MultimodalWeight 12%0 benchmarksNot measuredNot measured
Inst. FollowingRank #25 of 31Percentile 20thWeight 5%2 benchmarksReported48.2

Benchmark Details

Rows below have a displayable published verification record. Each source link and provenance note remains in the page HTML while its category is closed. Source-unverified manual rows and generated rows stay hidden.

Agentic4 benchmarks
τ²-bench resultsSecondary exact

τ²-Bench Tool-Agent-User Evaluation

86%Display only
Source: Artificial Analysis Ling 2.6 Flash summary screenshotProvenance: User-supplied screenshot of the Artificial Analysis Ling 2.6 Flash summary reports tau2-Bench at 86.
GDPval-AAReported

GDPval-AA normalized

2.2%Display only
Source: Artificial Analysis model benchmarksProvenance: Display-only row synced from the current Artificial Analysis model payload. It is excluded from BenchLM weighted scoring.
GDPval-AASecondary exact
545Display only
Source: Artificial Analysis Ling 2.6 Flash summary screenshotProvenance: User-supplied screenshot of the Artificial Analysis Ling 2.6 Flash summary reports GDPval-AA Elo at 783.
AA Agentic IndexReported

Artificial Analysis Agentic Index

2.3%Display only
Source: Artificial Analysis model benchmarksProvenance: Display-only row synced from the current Artificial Analysis model payload. It is excluded from BenchLM weighted scoring.
Coding3 benchmarks
SciCodeSecondary exact

Scientific Code Benchmark

27%Weighted 16%
Source: Artificial Analysis Ling 2.6 Flash summary screenshotProvenance: User-supplied screenshot of the Artificial Analysis Ling 2.6 Flash summary reports SciCode at 27.
AA Coding IndexReported

Artificial Analysis Coding Index

25.3%Display only
Source: Artificial Analysis model benchmarksProvenance: Display-only row synced from the current Artificial Analysis model payload. It is excluded from BenchLM weighted scoring.
AA-SciCodeReported

Artificial Analysis SciCode

27.1%Display only
Source: Artificial Analysis model benchmarksProvenance: Display-only row synced from the current Artificial Analysis model payload. It is excluded from BenchLM weighted scoring.
Reasoning2 benchmarks
AA-LCRReported

Artificial Analysis Long Context Reasoning

25.0%Display only
Source: Artificial Analysis model benchmarksProvenance: Display-only row synced from the current Artificial Analysis model payload. It is excluded from BenchLM weighted scoring.
CritPtReported

Critical Physics Tasks

0.0%Display only
Source: Artificial Analysis model benchmarksProvenance: Display-only row synced from the current Artificial Analysis model payload. It is excluded from BenchLM weighted scoring.
Knowledge7 benchmarks
GPQASecondary exact

Graduate-Level Google-Proof Q&A

59%Weighted 7%
Source: Artificial Analysis Ling 2.6 Flash summary screenshotProvenance: User-supplied screenshot of the Artificial Analysis Ling 2.6 Flash summary reports GPQA Diamond at 59. BenchLM maps that onto the site GPQA row for comparability.
Artificial Analysis Intelligence IndexSecondary exact
14.1%Display only
Source: Artificial Analysis: Ling 2.6 FlashProvenance: Artificial Analysis reports Ling 2.6 Flash at 26 on the Intelligence Index. BenchLM stores that display metric directly.
AA-GPQA DiamondReported

Artificial Analysis GPQA Diamond

59.3%Display only
Source: Artificial Analysis model benchmarksProvenance: Display-only row synced from the current Artificial Analysis model payload. It is excluded from BenchLM weighted scoring.
AA-HLEReported

Artificial Analysis Humanity's Last Exam

6.2%Display only
Source: Artificial Analysis model benchmarksProvenance: Display-only row synced from the current Artificial Analysis model payload. It is excluded from BenchLM weighted scoring.
AA-Omniscience IndexReported

Artificial Analysis Omniscience Index

-65.7%Display only
Source: Artificial Analysis model benchmarksProvenance: Display-only row synced from the current Artificial Analysis model payload. It is excluded from BenchLM weighted scoring.
AA-Omniscience AccuracyReported

Artificial Analysis Omniscience Accuracy

15.4%Display only
Source: Artificial Analysis model benchmarksProvenance: Display-only row synced from the current Artificial Analysis model payload. It is excluded from BenchLM weighted scoring.
AA-Omniscience Hallucination RateReported

Artificial Analysis Omniscience Hallucination Rate

95.8%Display only
Source: Artificial Analysis model benchmarksProvenance: Display-only row synced from the current Artificial Analysis model payload. It is excluded from BenchLM weighted scoring.
Inst. Following2 benchmarks
IFBenchSecondary exact

Instruction Following Benchmark

57%Weighted 65%
Source: Artificial Analysis Ling 2.6 Flash summary screenshotProvenance: User-supplied screenshot of the Artificial Analysis Ling 2.6 Flash summary reports IFBench at 57.
AA-IFBenchReported

Artificial Analysis IFBench

57.4%Display only
Source: Artificial Analysis model benchmarksProvenance: Display-only row synced from the current Artificial Analysis model payload. It is excluded from BenchLM weighted scoring.

Frequently Asked Questions

How does Ling 2.6 Flash perform overall in AI benchmarks?

Ling 2.6 Flash has 18 published benchmark scores on BenchLM, but it does not yet have enough non-generated coverage to receive a global overall rank.

Is Ling 2.6 Flash good for knowledge and understanding?

Ling 2.6 Flash has visible benchmark coverage in knowledge and understanding, but BenchLM does not currently assign it a global category rank there.

Is Ling 2.6 Flash good for coding and programming?

Ling 2.6 Flash ranks #93 out of 122 models in coding and programming benchmarks with an average score of 45.4. There are stronger options in this category.

Is Ling 2.6 Flash good for reasoning and logic?

Ling 2.6 Flash has visible benchmark coverage in reasoning and logic, but BenchLM does not currently assign it a global category rank there.

Is Ling 2.6 Flash good for agentic tool use and computer tasks?

Ling 2.6 Flash ranks #91 out of 119 models in agentic tool use and computer tasks benchmarks with an average score of 41. There are stronger options in this category.

Is Ling 2.6 Flash good for instruction following?

Ling 2.6 Flash ranks #25 out of 31 models in instruction following benchmarks with an average score of 48.2. There are stronger options in this category.

Is Ling 2.6 Flash open source?

Yes, Ling 2.6 Flash is an open weight model created by InclusionAI, meaning it can be downloaded and run locally or fine-tuned for specific use cases.

Does Ling 2.6 Flash have full benchmark coverage on BenchLM?

Not yet. Ling 2.6 Flash currently has 18 published benchmark scores out of the 323 benchmarks BenchLM tracks. BenchLM only exposes non-generated public benchmark rows, so missing categories stay blank until a sourced evaluation is available.

What is the context window size of Ling 2.6 Flash?

Ling 2.6 Flash has a published context window of 262K, which determines how much text it can process in a single interaction.

Last updated: July 21, 2026 · Runtime metrics stay blank until BenchLM has a sourced snapshot.

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