Ling-2.6-1T is an inclusionAI instruction model optimized for large-scale agentic and coding workloads with long-context support and structured output capabilities.
Added Apr 23, 2026
Context Window
262.1K
Max Output
32.8K
Input Price (Auto)
$1.00/1M
Output Price (Auto)
$3.00/1M
Capabilities
Performance metrics and benchmarks
Sourced from Artificial Analysis.
Intelligence Index
33.6
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Coding Index
33.0
Agentic Index
48.2
GPQA Diamond
Graduate-level scientific reasoning
75.2%
Better than 69% of models compared
HLE
Humanity's Last Exam
8.2%
Better than 63% of models compared
IFBench
Instruction-following benchmark
56.9%
Better than 74% of models compared
T²-Bench Telecom
Conversational AI agents in dual-control scenarios
89.8%
Better than 86% of models compared
AA-LCR
Long context reasoning evaluation
34.7%
Better than 53% of models compared
GDPval-AA
Economically valuable tasks
27.3%
Better than 71% of models compared
CritPt
Research-level physics reasoning
0.3%
Better than 64% of models compared
SciCode
Python programming for scientific computing
37.0%
Better than 69% of models compared
Terminal-Bench Hard
Agentic coding and terminal use
31.1%
Better than 78% of models compared
AA-Omniscience Accuracy
Proportion of correctly answered questions
21.4%
Better than 63% of models compared
AA-Omniscience Hallucination Rate
Rate of incorrect answers among non-correct responses
92.2%
Better than 15% of models compared
Last updated May 11, 2026
Artificial Analysis
