Model Comparison

GLM-4.5 vs Qwen2 7B Instruct

GLM-4.5 significantly outperforms across most benchmarks.

Performance Benchmarks

Comparative analysis across standard metrics

3 benchmarks

GLM-4.5 outperforms in 3 benchmarks (GPQA, LiveCodeBench, MMLU-Pro), while Qwen2 7B Instruct is better at 0 benchmarks.

GLM-4.5 significantly outperforms across most benchmarks.

Wed Apr 15 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Cost data unavailable.

Lowest available price from all providers
Wed Apr 15 2026 • llm-stats.com
Zhipu AI
GLM-4.5
Input tokens$0.40
Output tokens$1.60
Best providerDeepinfra
Alibaba Cloud / Qwen Team
Qwen2 7B Instruct
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
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Model Size

Parameter count comparison

347.4B diff

GLM-4.5 has 347.4B more parameters than Qwen2 7B Instruct, making it 4558.8% larger.

Zhipu AI
GLM-4.5
355.0Bparameters
Alibaba Cloud / Qwen Team
Qwen2 7B Instruct
7.6Bparameters
355.0B
GLM-4.5
7.6B
Qwen2 7B Instruct

Context Window

Maximum input and output token capacity

Only GLM-4.5 specifies input context (131,072 tokens). Only GLM-4.5 specifies output context (131,072 tokens).

Zhipu AI
GLM-4.5
Input131,072 tokens
Output131,072 tokens
Alibaba Cloud / Qwen Team
Qwen2 7B Instruct
Input- tokens
Output- tokens
Wed Apr 15 2026 • llm-stats.com

License

Usage and distribution terms

GLM-4.5 is licensed under MIT, while Qwen2 7B Instruct uses Apache 2.0.

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

GLM-4.5

MIT

Open weights

Qwen2 7B Instruct

Apache 2.0

Open weights

Release Timeline

When each model was launched

GLM-4.5 was released on 2025-07-28, while Qwen2 7B Instruct was released on 2024-07-23.

GLM-4.5 is 12 months newer than Qwen2 7B Instruct.

GLM-4.5

Jul 28, 2025

8 months ago

1.0yr newer
Qwen2 7B Instruct

Jul 23, 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

Outputs Comparison

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Key Takeaways

Larger context window (131,072 tokens)
Higher GPQA score (79.1% vs 25.3%)
Higher LiveCodeBench score (72.9% vs 26.6%)
Higher MMLU-Pro score (84.6% vs 44.1%)
Alibaba Cloud / Qwen Team

Qwen2 7B Instruct

View details

Alibaba Cloud / Qwen Team

Detailed Comparison

AI Model Comparison Table
Feature
Zhipu AI
GLM-4.5
Alibaba Cloud / Qwen Team
Qwen2 7B Instruct

FAQ

Common questions about GLM-4.5 vs Qwen2 7B Instruct

GLM-4.5 significantly outperforms across most benchmarks. GLM-4.5 is made by Zhipu AI and Qwen2 7B Instruct is made by Alibaba Cloud / Qwen Team. 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%. Qwen2 7B Instruct scores MT-Bench: 84.1%, GSM8k: 82.3%, HumanEval: 79.9%, C-Eval: 77.2%, AlignBench: 72.1%.
GLM-4.5 supports 131K tokens and Qwen2 7B Instruct supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.
GLM-4.5 is developed by Zhipu AI and Qwen2 7B Instruct is developed by Alibaba Cloud / Qwen Team.