Model Comparison

GLM-4.5 vs Qwen3 30B A3B

GLM-4.5 significantly outperforms across most benchmarks. Qwen3 30B A3B is 4.7x cheaper per token.

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Performance Benchmarks

Comparative analysis across standard metrics

3 benchmarks

GLM-4.5 outperforms in 3 benchmarks (AIME 2024, GPQA, LiveCodeBench), while Qwen3 30B A3B is better at 0 benchmarks.

GLM-4.5 significantly outperforms across most benchmarks.

Thu Apr 30 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Qwen3 30B A3B costs less

For input processing, GLM-4.5 ($0.40/1M tokens) is 4.0x more expensive than Qwen3 30B A3B ($0.10/1M tokens).

For output processing, GLM-4.5 ($1.60/1M tokens) is 5.3x more expensive than Qwen3 30B A3B ($0.30/1M tokens).

In conclusion, GLM-4.5 is more expensive than Qwen3 30B A3B.*

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

Lowest available price from all providers

Thu Apr 30 2026 • llm-stats.com

GLM-4.5

Input tokens$0.40

Output tokens$1.60

Best providerDeepinfra

Qwen3 30B A3B

Input tokens$0.10

Output tokens$0.30

Best providerDeepinfra

Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

324.5B diff

GLM-4.5 has 324.5B more parameters than Qwen3 30B A3B, making it 1063.9% larger.

GLM-4.5

355.0Bparameters

Qwen3 30B A3B

30.5Bparameters

355.0B

GLM-4.5

30.5B

Qwen3 30B A3B

Context Window

Maximum input and output token capacity

GLM-4.5 accepts 131,072 input tokens compared to Qwen3 30B A3B's 128,000 tokens. GLM-4.5 can generate longer responses up to 131,072 tokens, while Qwen3 30B A3B is limited to 128,000 tokens.

GLM-4.5

Input131,072 tokens

Output131,072 tokens

Qwen3 30B A3B

Input128,000 tokens

Output128,000 tokens

Thu Apr 30 2026 • llm-stats.com

License

Usage and distribution terms

GLM-4.5 is licensed under MIT, while Qwen3 30B A3B 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

Qwen3 30B A3B

Apache 2.0

Open weights

Release Timeline

When each model was launched

GLM-4.5 was released on 2025-07-28, while Qwen3 30B A3B was released on 2025-04-29.

GLM-4.5 is 3 months newer than Qwen3 30B A3B.

GLM-4.5

Jul 28, 2025

9 months ago

3mo newer

Qwen3 30B A3B

Apr 29, 2025

1.0 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. Qwen3 30B A3B is available from DeepInfra, Novita, Fireworks.

GLM-4.5

Deepinfra

Input Price:Input: $0.40/1MOutput Price:Output: $1.60/1M

Fireworks

Input Price:Input: $0.55/1MOutput Price:Output: $2.19/1M

Novita

Input Price:Input: $0.60/1MOutput Price:Output: $2.20/1M

Qwen3 30B A3B

Deepinfra

Input Price:Input: $0.10/1MOutput Price:Output: $0.30/1M

Novita

Input Price:Input: $0.10/1MOutput Price:Output: $0.44/1M

Fireworks

Input Price:Input: $0.89/1MOutput Price:Output: $0.89/1M

* Prices shown are per million tokens

Outputs Comparison

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Key Takeaways

GLM-4.5

View details

Zhipu AI

Larger context window (131,072 tokens)

Higher AIME 2024 score (91.0% vs 80.4%)

Higher GPQA score (79.1% vs 65.8%)

Higher LiveCodeBench score (72.9% vs 62.6%)

Qwen3 30B A3B

View details

Alibaba Cloud / Qwen Team

Less expensive input tokens

Less expensive output tokens

Detailed Comparison

AI Model Comparison Table
Feature	GLM-4.5	Qwen3 30B A3B

FAQ

Common questions about GLM-4.5 vs Qwen3 30B A3B

GLM-4.5 significantly outperforms across most benchmarks. GLM-4.5 is made by Zhipu AI and Qwen3 30B A3B 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%. Qwen3 30B A3B scores Arena Hard: 91.0%, AIME 2024: 80.4%, LiveBench: 74.3%, Multi-IF: 72.2%, AIME 2025: 70.9%.

Qwen3 30B A3B is 4.0x cheaper for input tokens. GLM-4.5 costs $0.40/M input and $1.60/M output via deepinfra. Qwen3 30B A3B costs $0.10/M input and $0.30/M output via deepinfra.

GLM-4.5 supports 131K tokens and Qwen3 30B A3B 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 $0.10/M), 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 Qwen3 30B A3B is developed by Alibaba Cloud / Qwen Team.

GLM-4.5 vs Qwen3 30B A3B

Performance Benchmarks

Arena Performance

Pricing Analysis

Model Size

Context Window

License

Release Timeline

Knowledge Cutoff

Provider Availability

GLM-4.5

Qwen3 30B A3B

Outputs Comparison

Key Takeaways

GLM-4.5

Qwen3 30B A3B

Detailed Comparison

FAQ

Which is better, GLM-4.5 or Qwen3 30B A3B?

How does GLM-4.5 compare to Qwen3 30B A3B in benchmarks?

Is GLM-4.5 cheaper than Qwen3 30B A3B?

What are the context window sizes for GLM-4.5 and Qwen3 30B A3B?

What are the main differences between GLM-4.5 and Qwen3 30B A3B?

Who makes GLM-4.5 and Qwen3 30B A3B?