Model Comparison

GLM-4.6 vs Kimi K2 Instruct

GLM-4.6 significantly outperforms across most benchmarks. Kimi K2 Instruct is 1.8x cheaper per token.

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Performance Benchmarks

Comparative analysis across standard metrics

5 benchmarks

GLM-4.6 outperforms in 5 benchmarks (AIME 2025, GPQA, Humanity's Last Exam, LiveCodeBench v6, Terminal-Bench), while Kimi K2 Instruct 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

Kimi K2 Instruct costs less

For input processing, GLM-4.6 ($0.55/1M tokens) is 1.1x more expensive than Kimi K2 Instruct ($0.50/1M tokens).

For output processing, GLM-4.6 ($2.00/1M tokens) is 4.0x more expensive than Kimi K2 Instruct ($0.50/1M tokens).

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

* 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 Instruct
Input tokens$0.50
Output tokens$0.50
Best providerFireworks
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

643.0B diff

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

Context Window

Maximum input and output token capacity

Kimi K2 Instruct accepts 200,000 input tokens compared to GLM-4.6's 131,072 tokens. Kimi K2 Instruct can generate longer responses up to 200,000 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 Instruct
Input200,000 tokens
Output200,000 tokens
Wed Apr 15 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

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

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 Instruct

MIT

Open weights

Release Timeline

When each model was launched

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

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

GLM-4.6

Sep 30, 2025

6 months ago

2mo newer
Kimi K2 Instruct

Jul 11, 2025

9 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 Instruct is available from Fireworks, 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 Instruct

fireworks logo
Fireworks
Input Price:Input: $0.50/1MOutput Price:Output: $0.50/1M
novita logo
Novita
Input Price:Input: $0.57/1MOutput Price:Output: $2.30/1M
* Prices shown are per million tokens

Outputs Comparison

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Key Takeaways

Zhipu AI
Supports multimodal inputs
Higher AIME 2025 score (93.9% vs 49.5%)
Higher GPQA score (81.0% vs 75.1%)
Higher Humanity's Last Exam score (17.2% vs 4.7%)
Higher LiveCodeBench v6 score (82.8% vs 53.7%)
Higher Terminal-Bench score (40.5% vs 30.0%)
Moonshot AI
Larger context window (200,000 tokens)
Less expensive input tokens
Less expensive output tokens

Detailed Comparison

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

FAQ

Common questions about GLM-4.6 vs Kimi K2 Instruct

GLM-4.6 significantly outperforms across most benchmarks. GLM-4.6 is made by Zhipu AI and Kimi K2 Instruct 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 Instruct scores MATH-500: 97.4%, GSM8k: 97.3%, CBNSL: 95.6%, HumanEval: 93.3%, MMLU-Redux: 92.7%.
Kimi K2 Instruct is 1.1x cheaper for input tokens. GLM-4.6 costs $0.55/M input and $2.00/M output via fireworks. Kimi K2 Instruct costs $0.50/M input and $0.50/M output via fireworks.
GLM-4.6 supports 131K tokens and Kimi K2 Instruct supports 200K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include context window (131K vs 200K), input pricing ($0.55 vs $0.50/M), multimodal support (yes vs no). See the full comparison above for benchmark-by-benchmark results.
GLM-4.6 is developed by Zhipu AI and Kimi K2 Instruct is developed by Moonshot AI.