Kimi K2 0711
Kimi K2 0711 version. Kimi-k2 is a Mixture-of-Experts (MoE) foundation model with exceptional coding and agent capabilities, featuring 1 trillion total parameters and 32 billion activated parameters. In benchmark evaluations covering general knowledge reasoning, programming, mathematics, and agent-related tasks, the K2 model outperforms other leading open-source models. Quantized at FP8.
- Tool Calling
- Structured Output
Pricing
Auto routing · per 1M tokens- Input
- $0.40
- Output
- $1.80
Specifications
- Context window
- 128K
- Max output
- 8.2K
- Parameters
- 1T / 32B
- Total / active
Benchmarks
Benchmarks
Sourced from Artificial Analysis.
Intelligence Index
12.7
Agentic work
T²-Bench Telecom (legacy)
Legacy fallback · Conversational AI agents in dual-control scenarios
61.1%
Better than 57% of models compared
Document reasoning
AA-LCR v1.1
Long context reasoning with updated grading
53.0%
Better than 46% of models compared
Reasoning
HLE
Humanity's Last Exam
7.4%
Better than 43% of models compared
IFBench
Instruction-following benchmark
41.5%
Better than 42% of models compared
Coding
Terminal-Bench Hard (legacy)
Legacy fallback · Agentic coding and terminal use
15.9%
Better than 53% of models compared
LiveCodeBench
Contamination-free coding benchmark
55.6%
Better than 62% of models compared
Math
AIME 2025
American Invitational Mathematics Examination 2025
57.0%
Better than 54% of models compared
AIME
American Invitational Mathematics Examination
69.3%
Better than 79% of models compared
Math-500
Diverse mathematical problem solving benchmark
97.1%
Better than 87% of models compared
Knowledge
MMLU-Pro
Professional and academic subject knowledge
82.4%
Better than 80% of models compared
Legacy benchmarks
GPQA Diamond (legacy)
Graduate-level scientific reasoning
76.6%
Better than 60% of models compared
AA-LCR (unversioned / legacy)
Long context reasoning evaluation
53.0%
Better than 46% of models compared
Last updated Oct 3, 2026
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