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Moonshot | Kimi K2 0905

Kimi K2 0905 is the September update of [Kimi K2 0711](moonshotai/kimi-k2). It is a large-scale Mixture-of-Experts (MoE) language model developed by Moonshot AI, featuring 1 trillion total parameters with 32 billion active per forward pass. It supports long-context inference up to 256k tokens, extended from the previous 128k. This update improves agentic coding with higher accuracy and better generalization across scaffolds, and enhances frontend coding with more aesthetic and functional outputs for web, 3D, and related tasks. Kimi K2 is optimized for agentic capabilities, including advanced tool use, reasoning, and code synthesis. It excels across coding (LiveCodeBench, SWE-bench), reasoning (ZebraLogic, GPQA), and tool-use (Tau2, AceBench) benchmarks. The model is trained with a novel stack incorporating the MuonClip optimizer for stable large-scale MoE training.

Compare

Poor

33.0
Most Recent Test

Not recommended for Great Commission use cases.

Strengths

  • Excellent at 3.4. The Resurrection

Weaknesses

  • Limited task completion capability
  • Weak doctrinal alignment
  • Struggles with 1.1. Missiological Research
  • Struggles with 1.2. Evangelistic Material
  • Struggles with 1.7. Difficult Passages
Overall Score
33.0
Tier 1 (Task) 70%
33.8
Tier 2 (Doctrine) 20%
15.0
Tier 3 (Worldview) 10%
63.3
Performance Profile
Visual representation of performance across all evaluated categories
Model Information
Description

Kimi K2 0905 is the September update of [Kimi K2 0711](moonshotai/kimi-k2). It is a large-scale Mixture-of-Experts (MoE) language model developed by Moonshot AI, featuring 1 trillion total parameters with 32 billion active per forward pass. It supports long-context inference up to 256k tokens, extended from the previous 128k. This update improves agentic coding with higher accuracy and better generalization across scaffolds, and enhances frontend coding with more aesthetic and functional outputs for web, 3D, and related tasks. Kimi K2 is optimized for agentic capabilities, including advanced tool use, reasoning, and code synthesis. It excels across coding (LiveCodeBench, SWE-bench), reasoning (ZebraLogic, GPQA), and tool-use (Tau2, AceBench) benchmarks. The model is trained with a novel stack incorporating the MuonClip optimizer for stable large-scale MoE training.

Provider

Moonshot

Model ID

moonshotai/kimi-k2-0905

Tests Run

1

Insights & Analysis

Categories

Category Heatmap
Performance breakdown by category - darker green indicates stronger alignment
30
1.1
30
1.2
43
1.3
40
1.4
40
1.5
47
1.6
7
1.7
20
2.1
40
2.2
0
2.3
10
2.4
20
2.5
0
2.6
75
3.1
75
3.2
50
3.3
100
3.4
50
3.5
50
3.6
Low
High
Category Breakdown (Bar Chart)
Performance across different categories
1.x = Task Capability2.x = Gospel Core3.x = Worldview Confession

Recent Tests

Recent Test Runs
DateScoreVersionTier 1 (Task)Tier 2 (Gospel)Tier 3 (Worldview)Trust Tier
10/10/202633.01.0.033.815.063.3automated