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GLM-4.6 vs Kimi K2 Base

GLM-4.6 leads the LLM Stats Score 28.7 to 13.2.

Zhipu AI · Moonshot AI · Updated for 2026

Which is better?

GLM-4.6 leads the overall LLM Stats Score 28.7 to 13.2, ranking #154 overall.

In the 2 individual benchmarks reported for both models, GLM-4.6 wins 2; this is a narrower head-to-head signal than the composite indexes.

Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose GLM-4.6

  • overall performance matters — it scores 28.7 and ranks #154 on LLM Stats
  • your work emphasizes reasoning — it leads those capability indexes
  • you value its reported benchmark strengths — it wins 2 of 2 exact shared results
  • you want the most recent training data — it shipped Sep 2025

Choose Kimi K2 Base

  • you are already invested in the Moonshot AI ecosystem

At a glance

The differences that matter most.

Core performance indexes
28.7
#154
13.2
#268
28.7
#147
12.3
#266
14.6
#152
10.6
#184
Cost, coverage & limits
Benchmark wins
2 of 2
0 of 2
Input price
$0.50 / M
— / M
Output price
$2.00 / M
— / M
Context window
202,752
—

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
GLM-4.6
Kimi K2 Base
24.5#125
14.2#230
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

7 reported for GLM-4.6 · 13 for Kimi K2 Base

2 shared

GLM-4.6 outperforms in 2 benchmarks (GPQA, LiveCodeBench v6), while Kimi K2 Base is better at 0 benchmarks.

GLM-4.6 significantly outperforms across most benchmarks.

Tue Oct 20 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

643.0B diff

Kimi K2 Base has 643.0B more parameters than GLM-4.6, making it 180.1% larger.

Zhipu AI
GLM-4.6
357.0Bparameters
Moonshot AI
Kimi K2 Base
1.0Tparameters
357.0B
GLM-4.6
1000.0B
Kimi K2 Base

Context Window

Maximum input and output token capacity

Only GLM-4.6 specifies input context (202,752 tokens). Only GLM-4.6 specifies output context (202,752 tokens).

Zhipu AI
GLM-4.6
Input202,752 tokens
Output202,752 tokens
Moonshot AI
Kimi K2 Base
Input- tokens
Output- tokens
Tue Oct 20 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

GLM-4.6 supports multimodal inputs, whereas Kimi K2 Base does not.

GLM-4.6 can handle both text and other forms of data like images, making it suitable for multimodal applications.

GLM-4.6

Text
Images
Audio
Video

Kimi K2 Base

Text
Images
Audio
Video

License

Usage and distribution terms

Both models are licensed under MIT.

Both models share the same licensing terms, providing consistent usage rights.

GLM-4.6

MIT

Open weights

Kimi K2 Base

MIT

Open weights

Release Timeline

When each model was launched

GLM-4.6 was released on 2025-09-30, while Kimi K2 Base was released on 2025-07-11.

GLM-4.6 is 3 months newer than Kimi K2 Base.

GLM-4.6

Sep 30, 2025

1.1 years ago

2mo newer
Kimi K2 Base

Jul 11, 2025

1.3 years ago

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

Outputs Comparison

Notice missing or incorrect data?

Judge for yourself.

Run your own prompts against GLM-4.6 and Kimi K2 Base side-by-side, then vote on the output you prefer.

GLM-4.6
✓ Preferred
Kimi K2 Base
Open in Playground

FAQ

Common questions about GLM-4.6 vs Kimi K2 Base.

Which is better, GLM-4.6 or Kimi K2 Base?

GLM-4.6 leads the LLM Stats Score 28.7 to 13.2. GLM-4.6 is made by Zhipu AI and Kimi K2 Base is made by Moonshot AI. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does GLM-4.6 compare to Kimi K2 Base in benchmarks?

GLM-4.6 scores AIME 2025: 93.9%, LiveCodeBench v6: 82.8%, GPQA: 81.0%, SWE-Bench Verified: 68.0%, BrowseComp: 45.1%. Kimi K2 Base scores C-Eval: 92.5%, GSM8k: 92.1%, MMLU-redux-2.0: 90.2%, MMLU: 87.8%, TriviaQA: 85.1%.

What are the context window sizes for GLM-4.6 and Kimi K2 Base?

GLM-4.6 supports 203K tokens and Kimi K2 Base supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between GLM-4.6 and Kimi K2 Base?

Key differences include LLM Stats Score (28.7 vs 13.2), multimodal support (yes vs no). See the full comparison above for benchmark-by-benchmark results.

Who makes GLM-4.6 and Kimi K2 Base?

GLM-4.6 is developed by Zhipu AI and Kimi K2 Base is developed by Moonshot AI.