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GLM-5.3 (max) Model Benchmarked by Artificial Analysis
Key points
- GLM-5.3 (max) scored 60 on Artificial Analysis Intelligence Index.
- It has a 1M token context window and supports text input/output.
- Pricing is $1.40/1M input tokens and $4.40/1M output tokens.
- The model operates at 74 tokens per second, slower than average.
Model Overview and Performance
Artificial Analysis conducted benchmarks on the GLM-5.3 (max) model, which was released on August 18, 2026, by Z AI. The model achieved a score of 60 on the Artificial Analysis Intelligence Index, surpassing the median score of 35 for comparable models. During evaluation, it generated 170 million tokens, which is higher than the median of 72 million tokens.
Pricing and Cost Efficiency
The pricing for GLM-5.3 (max) is set at $1.40 per 1 million input tokens and $4.40 per 1 million output tokens. These rates are considered moderately priced compared to the median rates of $1.75 for input and $10.00 for output tokens. The total cost to evaluate GLM-5.3 (max) on the Intelligence Index was $1238.50.
Speed and Context Window
GLM-5.3 (max) processes at a speed of 74 tokens per second, which is slower than the average speed for models in its class. The model supports text input and output and features a 1 million token context window.
Benchmarking Methodology
Models are compared based on their class, including non-reasoning, reasoning, open-weights (categorized by parameter size: Tiny, Small, Medium, Large), and proprietary models (categorized by price range). Proprietary models are compared across proprietary and open-weights models within the same price range, using a blended 3:1 input/output price ratio.
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Primary sources
GitHub meta-llama/llama-models GitHub deepseek-ai/DeepSeek-V2 GitHub QwenLM/Qwen GitHub deepseek-ai/deepseek-LLM GitHub deepseek-ai/DeepSeek-Coder-V2 GitHub MiniMax-AI/MiniMax-M2Reporting from
Artificial Analysis has benchmarked the GLM-5.3 (max) model, finding it scores 60 on their Intelligence Index, placing it above the median for comparable models. The model is noted for its 1M token context window, moderate pricing, and slower-than-average speed.