Model Comparison

GLM-4.6 vs Kimi K2 0905

GLM-4.6 significantly outperforms across most benchmarks. GLM-4.6 is 1.2x cheaper per token.

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Performance Benchmarks

Comparative analysis across standard metrics

1 benchmarks

GLM-4.6 outperforms in 1 benchmarks (GPQA), while Kimi K2 0905 is better at 0 benchmarks.

GLM-4.6 significantly outperforms across most benchmarks.

Wed Apr 15 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

GLM-4.6 costs less

For input processing, GLM-4.6 ($0.55/1M tokens) is 1.1x cheaper than Kimi K2 0905 ($0.60/1M tokens).

For output processing, GLM-4.6 ($2.00/1M tokens) is 1.3x cheaper than Kimi K2 0905 ($2.50/1M tokens).

In conclusion, Kimi K2 0905 is more expensive than GLM-4.6.*

* Using a 3:1 ratio of input to output tokens

Lowest available price from all providers
Wed Apr 15 2026 • llm-stats.com
Zhipu AI
GLM-4.6
Input tokens$0.55
Output tokens$2.00
Best providerFireworks
Moonshot AI
Kimi K2 0905
Input tokens$0.60
Output tokens$2.50
Best providerNovita
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

643.0B diff

Kimi K2 0905 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 0905
1000.0Bparameters
357.0B
GLM-4.6
1000.0B
Kimi K2 0905

Context Window

Maximum input and output token capacity

Kimi K2 0905 accepts 262,144 input tokens compared to GLM-4.6's 131,072 tokens. Kimi K2 0905 can generate longer responses up to 262,144 tokens, while GLM-4.6 is limited to 131,072 tokens.

Zhipu AI
GLM-4.6
Input131,072 tokens
Output131,072 tokens
Moonshot AI
Kimi K2 0905
Input262,144 tokens
Output262,144 tokens
Wed Apr 15 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

GLM-4.6 supports multimodal inputs, whereas Kimi K2 0905 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 0905

Text
Images
Audio
Video

License

Usage and distribution terms

GLM-4.6 is licensed under MIT, while Kimi K2 0905 uses a proprietary license.

License differences may affect how you can use these models in commercial or open-source projects.

GLM-4.6

MIT

Open weights

Kimi K2 0905

Proprietary

Closed source

Release Timeline

When each model was launched

GLM-4.6 was released on 2025-09-30, while Kimi K2 0905 was released on 2025-09-05.

GLM-4.6 is 1 month newer than Kimi K2 0905.

GLM-4.6

Sep 30, 2025

6 months ago

3w newer
Kimi K2 0905

Sep 5, 2025

7 months 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

Provider Availability

GLM-4.6 is available from Fireworks, DeepInfra. Kimi K2 0905 is available from Novita.

GLM-4.6

fireworks logo
Fireworks
Input Price:Input: $0.55/1MOutput Price:Output: $2.19/1M
deepinfra logo
Deepinfra
Input Price:Input: $0.60/1MOutput Price:Output: $2.00/1M

Kimi K2 0905

novita logo
Novita
Input Price:Input: $0.60/1MOutput Price:Output: $2.50/1M
* Prices shown are per million tokens

Outputs Comparison

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Key Takeaways

Zhipu AI
Supports multimodal inputs
Less expensive input tokens
Less expensive output tokens
Has open weights
Higher GPQA score (81.0% vs 75.8%)
Moonshot AI
Larger context window (262,144 tokens)

Detailed Comparison

AI Model Comparison Table
Feature
Zhipu AI
GLM-4.6
Moonshot AI
Kimi K2 0905

FAQ

Common questions about GLM-4.6 vs Kimi K2 0905

GLM-4.6 significantly outperforms across most benchmarks. GLM-4.6 is made by Zhipu AI and Kimi K2 0905 is made by Moonshot AI. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.
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 0905 scores HumanEval: 94.5%, MMLU: 90.2%, MATH: 89.1%, MMLU-Pro: 82.5%, GPQA: 75.8%.
GLM-4.6 is 1.1x cheaper for input tokens. GLM-4.6 costs $0.55/M input and $2.00/M output via fireworks. Kimi K2 0905 costs $0.60/M input and $2.50/M output via novita.
GLM-4.6 supports 131K tokens and Kimi K2 0905 supports 262K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include context window (131K vs 262K), input pricing ($0.55 vs $0.60/M), multimodal support (yes vs no), licensing (MIT vs Proprietary). See the full comparison above for benchmark-by-benchmark results.
GLM-4.6 is developed by Zhipu AI and Kimi K2 0905 is developed by Moonshot AI.