Model Comparison

DeepSeek-V3 vs GLM-4.5-Air

GLM-4.5-Air significantly outperforms across most benchmarks.

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Performance Benchmarks

Comparative analysis across standard metrics

6 benchmarks

DeepSeek-V3 outperforms in 0 benchmarks, while GLM-4.5-Air is better at 6 benchmarks (AIME 2024, GPQA, LiveCodeBench, MATH-500, MMLU-Pro, SWE-Bench Verified).

GLM-4.5-Air significantly outperforms across most benchmarks.

Fri May 08 2026 • llm-stats.com

Arena Performance

Human preference votes

Model Size

Parameter count comparison

565.0B diff

DeepSeek-V3 has 565.0B more parameters than GLM-4.5-Air, making it 533.0% larger.

DeepSeek
DeepSeek-V3
671.0Bparameters
Zhipu AI
GLM-4.5-Air
106.0Bparameters
671.0B
DeepSeek-V3
106.0B
GLM-4.5-Air

Context Window

Maximum input and output token capacity

Only DeepSeek-V3 specifies input context (131,072 tokens). Only DeepSeek-V3 specifies output context (131,072 tokens).

DeepSeek
DeepSeek-V3
Input131,072 tokens
Output131,072 tokens
Zhipu AI
GLM-4.5-Air
Input- tokens
Output- tokens
Fri May 08 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek-V3 is licensed under MIT + Model License (Commercial use allowed), while GLM-4.5-Air uses MIT.

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

DeepSeek-V3

MIT + Model License (Commercial use allowed)

Open weights

GLM-4.5-Air

MIT

Open weights

Release Timeline

When each model was launched

DeepSeek-V3 was released on 2024-12-25, while GLM-4.5-Air was released on 2025-07-28.

GLM-4.5-Air is 7 months newer than DeepSeek-V3.

DeepSeek-V3

Dec 25, 2024

1.4 years ago

GLM-4.5-Air

Jul 28, 2025

9 months ago

7mo newer

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

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Key Takeaways

DeepSeek
Larger context window (131,072 tokens)
Zhipu AI
Higher AIME 2024 score (89.4% vs 39.2%)
Higher GPQA score (75.0% vs 59.1%)
Higher LiveCodeBench score (70.7% vs 37.6%)
Higher MATH-500 score (98.1% vs 90.2%)
Higher MMLU-Pro score (81.4% vs 75.9%)
Higher SWE-Bench Verified score (57.6% vs 42.0%)

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-V3
Zhipu AI
GLM-4.5-Air

FAQ

Common questions about DeepSeek-V3 vs GLM-4.5-Air.

Which is better, DeepSeek-V3 or GLM-4.5-Air?

GLM-4.5-Air significantly outperforms across most benchmarks. DeepSeek-V3 is made by DeepSeek and GLM-4.5-Air is made by Zhipu AI. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does DeepSeek-V3 compare to GLM-4.5-Air in benchmarks?

DeepSeek-V3 scores DROP: 91.6%, CLUEWSC: 90.9%, MATH-500: 90.2%, MMLU-Redux: 89.1%, MMLU: 88.5%. GLM-4.5-Air scores MATH-500: 98.1%, AIME 2024: 89.4%, MMLU-Pro: 81.4%, TAU-bench Retail: 77.9%, BFCL-v3: 76.4%.

What are the context window sizes for DeepSeek-V3 and GLM-4.5-Air?

DeepSeek-V3 supports 131K tokens and GLM-4.5-Air 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 DeepSeek-V3 and GLM-4.5-Air?

Key differences include licensing (MIT + Model License (Commercial use allowed) vs MIT). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V3 and GLM-4.5-Air?

DeepSeek-V3 is developed by DeepSeek and GLM-4.5-Air is developed by Zhipu AI.