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Ling 2.6 Flash

inclusionai/ling-2.6-flash
BackTry Model
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Ling 2.6 Flash

inclusionai/ling-2.6-flash
BackTry Model

Ling-2.6-flash is an instant (instruct) model from inclusionAI with 104B total parameters and 7.4B active parameters, designed for real-world agents that require fast responses, strong execution, and high token efficiency. It delivers performance comparable to state-of-the-art models at a similar scale while significantly reducing token usage across coding, document processing, and lightweight agent workflows.

Added Apr 21, 2026

Context Window

262.1K

Max Output

32.8K

Input Price (Auto)

$0.10/1M

Output Price (Auto)

$0.30/1M

Cache Read (Auto)

$0.020/1M

Capabilities

Benchmarks

Performance metrics and benchmarks

Sourced from Artificial Analysis.

Intelligence Index

14.2

Better than 42% of models compared

Coding Index

25.3

Better than 34% of models compared

Agentic Index

2.3

Better than 18% of models compared

Reasoning

GPQA Diamond

Graduate-level scientific reasoning

59.3%

Better than 36% of models compared

HLE

Humanity's Last Exam

6.3%

Better than 43% of models compared

IFBench

Instruction-following benchmark

57.4%

Better than 69% of models compared

T²-Bench Telecom

Conversational AI agents in dual-control scenarios

86.0%

Better than 78% of models compared

AA-LCR

Long context reasoning evaluation

28.0%

Better than 35% of models compared

GDPval-AA

Economically valuable tasks

2.2%

CritPt

Research-level physics reasoning

0.0%

Coding

SciCode

Python programming for scientific computing

27.1%

Better than 33% of models compared

Terminal-Bench Hard

Agentic coding and terminal use

21.2%

Better than 61% of models compared

Knowledge

AA-Omniscience Accuracy

Proportion of correctly answered questions

15.5%

AA-Omniscience Hallucination Rate

Rate of incorrect answers among non-correct responses

96.7%

Last updated Aug 16, 2026

Artificial Analysis

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