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DeepSeek-V4-Pro-0813 vs GLM-4.5-Air

DeepSeek-V4-Pro-0813 significantly outperforms across most benchmarks.

DeepSeek · Zhipu AI · Updated for 2026

Which is better?

DeepSeek-V4-Pro-0813 outperforms in 1 benchmarks (Humanity's Last Exam), while GLM-4.5-Air is better at 0 benchmarks. DeepSeek-V4-Pro-0813 significantly outperforms across most benchmarks.

Based on current benchmark, pricing, and model metadata for 2026.

Choose DeepSeek-V4-Pro-0813

  • you want the strongest raw capability — it leads on 1 of 1 shared benchmarks
  • you want the most recent training data — it shipped Aug 2026

Choose GLM-4.5-Air

  • you are already invested in the Zhipu AI ecosystem

At a glance

The differences that matter most.

DeepSeek-V4-Pro-0813
DeepSeek
GLM-4.5-Air
Zhipu AI
Benchmark wins
1 of 1
0 of 1
Input price
$0.43 / M
— / M
Output price
$0.87 / M
— / M
Context window
1,048,576
—
Released
Aug 2026
Jul 2025
License
MIT
MIT

Performance Benchmarks

Comparative analysis across standard metrics

1 benchmarks

DeepSeek-V4-Pro-0813 outperforms in 1 benchmarks (Humanity's Last Exam), while GLM-4.5-Air is better at 0 benchmarks.

DeepSeek-V4-Pro-0813 significantly outperforms across most benchmarks.

Tue Aug 25 2026 • llm-stats.com

Arena Performance

Playground indexes and blind preference scores

Model Size

Parameter count comparison

1494.0B diff

DeepSeek-V4-Pro-0813 has 1494.0B more parameters than GLM-4.5-Air, making it 1409.4% larger.

DeepSeek
DeepSeek-V4-Pro-0813
1.6Tparameters
Zhipu AI
GLM-4.5-Air
106.0Bparameters
1600.0B
DeepSeek-V4-Pro-0813
106.0B
GLM-4.5-Air

Context Window

Maximum input and output token capacity

Only DeepSeek-V4-Pro-0813 specifies input context (1,048,576 tokens). Only DeepSeek-V4-Pro-0813 specifies output context (393,216 tokens).

DeepSeek
DeepSeek-V4-Pro-0813
Input1,048,576 tokens
Output393,216 tokens
Zhipu AI
GLM-4.5-Air
Input- tokens
Output- tokens
Tue Aug 25 2026 • llm-stats.com

License

Usage and distribution terms

Both models are licensed under MIT.

Both models share the same licensing terms, providing consistent usage rights.

DeepSeek-V4-Pro-0813

MIT

Open weights

GLM-4.5-Air

MIT

Open weights

Release Timeline

When each model was launched

DeepSeek-V4-Pro-0813 was released on 2026-08-13, while GLM-4.5-Air was released on 2025-07-28.

DeepSeek-V4-Pro-0813 is 13 months newer than GLM-4.5-Air.

DeepSeek-V4-Pro-0813

Aug 13, 2026

1 weeks ago

1.0yr newer
GLM-4.5-Air

Jul 28, 2025

1.1 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

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Judge for yourself.

Run your own prompts against DeepSeek-V4-Pro-0813 and GLM-4.5-Air side-by-side, then vote on the output you prefer.

DeepSeek-V4-Pro-0813
✓ Preferred
GLM-4.5-Air
Open in Playground

FAQ

Common questions about DeepSeek-V4-Pro-0813 vs GLM-4.5-Air.

Which is better, DeepSeek-V4-Pro-0813 or GLM-4.5-Air?

DeepSeek-V4-Pro-0813 significantly outperforms across most benchmarks. DeepSeek-V4-Pro-0813 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-V4-Pro-0813 compare to GLM-4.5-Air in benchmarks?

DeepSeek-V4-Pro-0813 scores Terminal-Bench 2.1: 87.9%, CyberGym: 83.3%, Toolathlon: 74.1%, DSBench-FullStack: 71.1%, DSBench-Hard: 67.2%. 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-V4-Pro-0813 and GLM-4.5-Air?

DeepSeek-V4-Pro-0813 supports 1.0M 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.

Who makes DeepSeek-V4-Pro-0813 and GLM-4.5-Air?

DeepSeek-V4-Pro-0813 is developed by DeepSeek and GLM-4.5-Air is developed by Zhipu AI.

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