Model Comparison

GLM-5 vs Qwen3 235B A22B

Comparing GLM-5 and Qwen3 235B A22B across benchmarks, pricing, and capabilities.

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Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

GLM-5 and Qwen3 235B A22B don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Qwen3 235B A22B costs less

For input processing, GLM-5 ($1.00/1M tokens) is 10.0x more expensive than Qwen3 235B A22B ($0.10/1M tokens).

For output processing, GLM-5 ($3.20/1M tokens) is 32.0x more expensive than Qwen3 235B A22B ($0.10/1M tokens).

In conclusion, GLM-5 is more expensive than Qwen3 235B A22B.*

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

Lowest available price from all providers
Wed Apr 15 2026 • llm-stats.com
Zhipu AI
GLM-5
Input tokens$1.00
Output tokens$3.20
Best providerUnknown Organization
Alibaba Cloud / Qwen Team
Qwen3 235B A22B
Input tokens$0.10
Output tokens$0.10
Best providerFireworks
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

509.0B diff

GLM-5 has 509.0B more parameters than Qwen3 235B A22B, making it 216.6% larger.

Zhipu AI
GLM-5
744.0Bparameters
Alibaba Cloud / Qwen Team
Qwen3 235B A22B
235.0Bparameters
744.0B
GLM-5
235.0B
Qwen3 235B A22B

Context Window

Maximum input and output token capacity

GLM-5 accepts 200,000 input tokens compared to Qwen3 235B A22B's 128,000 tokens. Both models can generate responses up to 128,000 tokens.

Zhipu AI
GLM-5
Input200,000 tokens
Output128,000 tokens
Alibaba Cloud / Qwen Team
Qwen3 235B A22B
Input128,000 tokens
Output128,000 tokens
Wed Apr 15 2026 • llm-stats.com

License

Usage and distribution terms

GLM-5 is licensed under MIT, while Qwen3 235B A22B uses Apache 2.0.

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

GLM-5

MIT

Open weights

Qwen3 235B A22B

Apache 2.0

Open weights

Release Timeline

When each model was launched

GLM-5 was released on 2026-02-11, while Qwen3 235B A22B was released on 2025-04-29.

GLM-5 is 10 months newer than Qwen3 235B A22B.

GLM-5

Feb 11, 2026

2 months ago

9mo newer
Qwen3 235B A22B

Apr 29, 2025

11 months 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-5 is available from ZAI. Qwen3 235B A22B is available from Fireworks, DeepInfra, Novita, Together.

GLM-5

z logo
Unknown Organization
Input Price:Input: $1.00/1MOutput Price:Output: $3.20/1M

Qwen3 235B A22B

fireworks logo
Fireworks
Input Price:Input: $0.10/1MOutput Price:Output: $0.10/1M
deepinfra logo
Deepinfra
Input Price:Input: $0.20/1MOutput Price:Output: $0.60/1M
novita logo
Novita
Input Price:Input: $0.20/1MOutput Price:Output: $0.80/1M
together logo
Together
Input Price:Input: $0.20/1MOutput Price:Output: $0.60/1M
* Prices shown are per million tokens

Outputs Comparison

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Key Takeaways

Zhipu AI
Larger context window (200,000 tokens)
Alibaba Cloud / Qwen Team

Qwen3 235B A22B

View details

Alibaba Cloud / Qwen Team

Less expensive input tokens
Less expensive output tokens

Detailed Comparison

AI Model Comparison Table
Feature
Zhipu AI
GLM-5
Alibaba Cloud / Qwen Team
Qwen3 235B A22B

FAQ

Common questions about GLM-5 vs Qwen3 235B A22B

GLM-5 (Zhipu AI) and Qwen3 235B A22B (Alibaba Cloud / Qwen Team) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.
GLM-5 scores t2-bench: 89.7%, SWE-Bench Verified: 77.8%, BrowseComp: 75.9%, MCP Atlas: 67.8%, Terminal-Bench 2.0: 56.2%. Qwen3 235B A22B scores Arena Hard: 95.6%, GSM8k: 94.4%, BBH: 88.9%, MMLU: 87.8%, MMLU-Redux: 87.4%.
Qwen3 235B A22B is 10.0x cheaper for input tokens. GLM-5 costs $1.00/M input and $3.20/M output via z. Qwen3 235B A22B costs $0.10/M input and $0.10/M output via fireworks.
GLM-5 supports 200K tokens and Qwen3 235B A22B supports 128K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include context window (200K vs 128K), input pricing ($1.00 vs $0.10/M), licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.
GLM-5 is developed by Zhipu AI and Qwen3 235B A22B is developed by Alibaba Cloud / Qwen Team.