Model Comparison

GLM-4.6 vs Qwen3-Coder

Comparing GLM-4.6 and Qwen3-Coder across benchmarks, pricing, and capabilities.

Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

GLM-4.6 and Qwen3-Coder 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-Coder costs less

For input processing, GLM-4.6 ($0.55/1M tokens) is 3.1x more expensive than Qwen3-Coder ($0.18/1M tokens).

For output processing, GLM-4.6 ($2.00/1M tokens) is 11.1x more expensive than Qwen3-Coder ($0.18/1M tokens).

In conclusion, GLM-4.6 is more expensive than Qwen3-Coder.*

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

Lowest available price from all providers
Tue Apr 14 2026 • llm-stats.com
Zhipu AI
GLM-4.6
Input tokens$0.55
Output tokens$2.00
Best providerFireworks
Alibaba Cloud / Qwen Team
Qwen3-Coder
Input tokens$0.18
Output tokens$0.18
Best providerDeepinfra
Notice missing or incorrect data?Start an Issue

Model Size

Parameter count comparison

123.0B diff

Qwen3-Coder has 123.0B more parameters than GLM-4.6, making it 34.5% larger.

Zhipu AI
GLM-4.6
357.0Bparameters
Alibaba Cloud / Qwen Team
Qwen3-Coder
480.0Bparameters
357.0B
GLM-4.6
480.0B
Qwen3-Coder

Context Window

Maximum input and output token capacity

Qwen3-Coder accepts 256,000 input tokens compared to GLM-4.6's 131,072 tokens. Qwen3-Coder can generate longer responses up to 256,000 tokens, while GLM-4.6 is limited to 131,072 tokens.

Zhipu AI
GLM-4.6
Input131,072 tokens
Output131,072 tokens
Alibaba Cloud / Qwen Team
Qwen3-Coder
Input256,000 tokens
Output256,000 tokens
Tue Apr 14 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

GLM-4.6 supports multimodal inputs, whereas Qwen3-Coder does not.

GLM-4.6 can handle both text and other forms of data like images, making it suitable for multimodal applications.

GLM-4.6

Text
Images
Audio
Video

Qwen3-Coder

Text
Images
Audio
Video

License

Usage and distribution terms

GLM-4.6 is licensed under MIT, while Qwen3-Coder uses Apache 2.0.

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

GLM-4.6

MIT

Open weights

Qwen3-Coder

Apache 2.0

Open weights

Release Timeline

When each model was launched

GLM-4.6 was released on 2025-09-30, while Qwen3-Coder was released on 2025-01-01.

GLM-4.6 is 9 months newer than Qwen3-Coder.

GLM-4.6

Sep 30, 2025

6 months ago

9mo newer
Qwen3-Coder

Jan 1, 2025

1.3 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-4.6 is available from Fireworks, DeepInfra. Qwen3-Coder is available from DeepInfra, Fireworks.

GLM-4.6

fireworks logo
Fireworks
Input Price:Input: $0.55/1MOutput Price:Output: $2.19/1M
deepinfra logo
Deepinfra
Input Price:Input: $0.60/1MOutput Price:Output: $2.00/1M

Qwen3-Coder

deepinfra logo
Deepinfra
Input Price:Input: $0.18/1MOutput Price:Output: $0.18/1M
fireworks logo
Fireworks
Input Price:Input: $0.25/1MOutput Price:Output: $0.25/1M
* Prices shown are per million tokens

Outputs Comparison

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Key Takeaways

Supports multimodal inputs
Alibaba Cloud / Qwen Team

Qwen3-Coder

View details

Alibaba Cloud / Qwen Team

Larger context window (256,000 tokens)
Less expensive input tokens
Less expensive output tokens

Detailed Comparison

AI Model Comparison Table
Feature
Zhipu AI
GLM-4.6
Alibaba Cloud / Qwen Team
Qwen3-Coder

FAQ

Common questions about GLM-4.6 vs Qwen3-Coder

GLM-4.6 (Zhipu AI) and Qwen3-Coder (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-4.6 scores AIME 2025: 93.9%, LiveCodeBench v6: 82.8%, GPQA: 81.0%, SWE-Bench Verified: 68.0%, BrowseComp: 45.1%.
Qwen3-Coder is 3.1x cheaper for input tokens. GLM-4.6 costs $0.55/M input and $2.00/M output via fireworks. Qwen3-Coder costs $0.18/M input and $0.18/M output via deepinfra.
GLM-4.6 supports 131K tokens and Qwen3-Coder supports 256K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include context window (131K vs 256K), input pricing ($0.55 vs $0.18/M), multimodal support (yes vs no), licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.
GLM-4.6 is developed by Zhipu AI and Qwen3-Coder is developed by Alibaba Cloud / Qwen Team.