Model Comparison

GLM-4.5 vs Grok-2

GLM-4.5 significantly outperforms across most benchmarks. GLM-4.5 is 5.7x cheaper per token.

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Performance Benchmarks

Comparative analysis across standard metrics

2 benchmarks

GLM-4.5 outperforms in 2 benchmarks (GPQA, MMLU-Pro), while Grok-2 is better at 0 benchmarks.

GLM-4.5 significantly outperforms across most benchmarks.

Fri May 01 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

GLM-4.5 costs less

For input processing, GLM-4.5 ($0.40/1M tokens) is 5.0x cheaper than Grok-2 ($2.00/1M tokens).

For output processing, GLM-4.5 ($1.60/1M tokens) is 6.3x cheaper than Grok-2 ($10.00/1M tokens).

In conclusion, Grok-2 is more expensive than GLM-4.5.*

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

Lowest available price from all providers
Fri May 01 2026 • llm-stats.com
Zhipu AI
GLM-4.5
Input tokens$0.40
Output tokens$1.60
Best providerDeepinfra
xAI
Grok-2
Input tokens$2.00
Output tokens$10.00
Best providerxAI
Notice missing or incorrect data?Start an Issue→

Context Window

Maximum input and output token capacity

GLM-4.5 accepts 131,072 input tokens compared to Grok-2's 128,000 tokens. GLM-4.5 can generate longer responses up to 131,072 tokens, while Grok-2 is limited to 8,000 tokens.

Zhipu AI
GLM-4.5
Input131,072 tokens
Output131,072 tokens
xAI
Grok-2
Input128,000 tokens
Output8,000 tokens
Fri May 01 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Grok-2 supports multimodal inputs, whereas GLM-4.5 does not.

Grok-2 can handle both text and other forms of data like images, making it suitable for multimodal applications.

GLM-4.5

Text
Images
Audio
Video

Grok-2

Text
Images
Audio
Video

License

Usage and distribution terms

GLM-4.5 is licensed under MIT, while Grok-2 uses a proprietary license.

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

GLM-4.5

MIT

Open weights

Grok-2

Proprietary

Closed source

Release Timeline

When each model was launched

GLM-4.5 was released on 2025-07-28, while Grok-2 was released on 2024-08-13.

GLM-4.5 is 12 months newer than Grok-2.

GLM-4.5

Jul 28, 2025

9 months ago

11mo newer
Grok-2

Aug 13, 2024

1.7 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

Provider Availability

GLM-4.5 is available from DeepInfra, Fireworks, Novita. Grok-2 is available from xAI.

GLM-4.5

deepinfra logo
Deepinfra
Input Price:Input: $0.40/1MOutput Price:Output: $1.60/1M
fireworks logo
Fireworks
Input Price:Input: $0.55/1MOutput Price:Output: $2.19/1M
novita logo
Novita
Input Price:Input: $0.60/1MOutput Price:Output: $2.20/1M

Grok-2

xai logo
xAI
Input Price:Input: $2.00/1MOutput Price:Output: $10.00/1M
* Prices shown are per million tokens

Outputs Comparison

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Key Takeaways

Zhipu AI
Larger context window (131,072 tokens)
Less expensive input tokens
Less expensive output tokens
Has open weights
Higher GPQA score (79.1% vs 56.0%)
Higher MMLU-Pro score (84.6% vs 75.5%)
xAI
Supports multimodal inputs

Detailed Comparison

AI Model Comparison Table
Feature
Zhipu AI
GLM-4.5
xAI
Grok-2

FAQ

Common questions about GLM-4.5 vs Grok-2

GLM-4.5 significantly outperforms across most benchmarks. GLM-4.5 is made by Zhipu AI and Grok-2 is made by xAI. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.
GLM-4.5 scores MATH-500: 98.2%, AIME 2024: 91.0%, MMLU-Pro: 84.6%, TAU-bench Retail: 79.7%, GPQA: 79.1%. Grok-2 scores DocVQA: 93.6%, HumanEval: 88.4%, MMLU: 87.5%, MATH: 76.1%, MMLU-Pro: 75.5%.
GLM-4.5 is 5.0x cheaper for input tokens. GLM-4.5 costs $0.40/M input and $1.60/M output via deepinfra. Grok-2 costs $2.00/M input and $10.00/M output via xai.
GLM-4.5 supports 131K tokens and Grok-2 supports 128K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include context window (131K vs 128K), input pricing ($0.40 vs $2.00/M), multimodal support (no vs yes), licensing (MIT vs Proprietary). See the full comparison above for benchmark-by-benchmark results.
GLM-4.5 is developed by Zhipu AI and Grok-2 is developed by xAI.