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GLM-5.3-Flash vs Qwen2.5-Coder 7B Instruct

Comparing GLM-5.3-Flash and Qwen2.5-Coder 7B Instruct across benchmarks, pricing, and capabilities.

Zhipu AI · Alibaba Cloud / Qwen Team · Updated for 2026

Which is better?

GLM-5.3-Flash and Qwen2.5-Coder 7B Instruct trade strengths across price, capabilities, and technical limits. The better choice depends on the workload.

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

Choose GLM-5.3-Flash

  • you want the most recent training data — it shipped Aug 2026

Choose Qwen2.5-Coder 7B Instruct

  • you are already invested in the Alibaba Cloud / Qwen Team ecosystem

At a glance

The differences that matter most.

Benchmark wins
Input price
$0.15 / M
— / M
Output price
$0.50 / M
— / M
Context window
1,048,576
Released
Aug 2026
Sep 2024
License
MIT
Apache 2.0

Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

GLM-5.3-Flash and Qwen2.5-Coder 7B Instructdon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Arena Performance

Playground indexes and blind preference scores

Model Size

Parameter count comparison

313.0B diff

GLM-5.3-Flash has 313.0B more parameters than Qwen2.5-Coder 7B Instruct, making it 4471.4% larger.

Zhipu AI
GLM-5.3-Flash
320.0Bparameters
Alibaba Cloud / Qwen Team
Qwen2.5-Coder 7B Instruct
7.0Bparameters
320.0B
GLM-5.3-Flash
7.0B
Qwen2.5-Coder 7B Instruct

Context Window

Maximum input and output token capacity

Only GLM-5.3-Flash specifies input context (1,048,576 tokens). Only GLM-5.3-Flash specifies output context (131,072 tokens).

Zhipu AI
GLM-5.3-Flash
Input1,048,576 tokens
Output131,072 tokens
Alibaba Cloud / Qwen Team
Qwen2.5-Coder 7B Instruct
Input- tokens
Output- tokens
Wed Aug 26 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

GLM-5.3-Flash supports multimodal inputs, whereas Qwen2.5-Coder 7B Instruct does not.

GLM-5.3-Flash can handle both text and other forms of data like images, making it suitable for multimodal applications.

GLM-5.3-Flash

Text
Images
Audio
Video

Qwen2.5-Coder 7B Instruct

Text
Images
Audio
Video

License

Usage and distribution terms

GLM-5.3-Flash is licensed under MIT, while Qwen2.5-Coder 7B Instruct uses Apache 2.0.

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

GLM-5.3-Flash

MIT

Open weights

Qwen2.5-Coder 7B Instruct

Apache 2.0

Open weights

Release Timeline

When each model was launched

GLM-5.3-Flash was released on 2026-08-26, while Qwen2.5-Coder 7B Instruct was released on 2024-09-19.

GLM-5.3-Flash is 24 months newer than Qwen2.5-Coder 7B Instruct.

GLM-5.3-Flash

Aug 26, 2026

0 days ago

1.9yr newer
Qwen2.5-Coder 7B Instruct

Sep 19, 2024

1.9 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 GLM-5.3-Flash and Qwen2.5-Coder 7B Instruct side-by-side, then vote on the output you prefer.

GLM-5.3-Flash
✓ Preferred
Qwen2.5-Coder 7B Instruct
Open in Playground

FAQ

Common questions about GLM-5.3-Flash vs Qwen2.5-Coder 7B Instruct.

Which is better, GLM-5.3-Flash or Qwen2.5-Coder 7B Instruct?

GLM-5.3-Flash (Zhipu AI) and Qwen2.5-Coder 7B Instruct (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.

How does GLM-5.3-Flash compare to Qwen2.5-Coder 7B Instruct in benchmarks?

GLM-5.3-Flash scores CharXiv-R: 89.4%, Terminal-Bench 2.1: 84.3%, MMVU: 80.5%, Toolathlon: 78.4%, Chartography: 78.0%. Qwen2.5-Coder 7B Instruct scores HumanEval: 88.4%, GSM8k: 83.9%, MBPP: 83.5%, HellaSwag: 76.8%, Winogrande: 72.9%.

What are the context window sizes for GLM-5.3-Flash and Qwen2.5-Coder 7B Instruct?

GLM-5.3-Flash supports 1.0M tokens and Qwen2.5-Coder 7B Instruct supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between GLM-5.3-Flash and Qwen2.5-Coder 7B Instruct?

Key differences include multimodal support (yes vs no), licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes GLM-5.3-Flash and Qwen2.5-Coder 7B Instruct?

GLM-5.3-Flash is developed by Zhipu AI and Qwen2.5-Coder 7B Instruct is developed by Alibaba Cloud / Qwen Team.