head-to-head

Z.ai: GLM 5.3 FlashX vs inclusionAI: Ling 3.0 Flash

Side-by-side comparison of specs, pricing, benchmark scores, and task rankings. Updated 2026-11-07.

Z.ai: GLM 5.3 FlashX inclusionAI: Ling 3.0 Flash
Vendorz-aiinclusionai
Quality Score100100
Input Price$0.37/M$0.02/M
Output Price$1.25/M$0.06/M
Context Window1,048,576262,144
Max Output131,07232,768
Tool Calling✓✓
Structured Output✓✓
Reasoning Mode✓✓
Vision✓-
Audio--

The verdict

For a sample job of 1 million input tokens and 250,000 output tokens, Ling 3.0 Flash costs $0.037 and GLM 5.3 FlashX costs $0.68, so Ling 3.0 Flash is about 18.6 times cheaper for the same work.

GLM 5.3 FlashX reads up to 1,048,576 tokens at once, roughly 1,573 pages of text, against about 393 pages for Ling 3.0 Flash.

Only GLM 5.3 FlashX offers image input and video input.

Across the 19 tasks where they differ, GLM 5.3 FlashX scores higher on 15 (SQL Generation, Code Review, Code Completion and others), Ling 3.0 Flash on 4 (Regex Writing, JSON Extraction, Bulk Data Labeling and others).

GLM 5.3 FlashX was released in September 2026 and Ling 3.0 Flash in July 2026.

Pick GLM 5.3 FlashX if you need long documents, image input, video input or the stronger all-round task scores; pick Ling 3.0 Flash if you need lower cost.

Costs use current list prices per million tokens; page counts assume about 0.75 words per token and 500 words per page.

Who wins by task?

TaskZ.ai: GLM 5.3 FlashXinclusionAI: Ling 3.0 Flash
SQL Generation 133 131
Code Review 132 126
Code Completion 131 129
Code Refactoring 136 127
Bug Fixing 136 130
Unit Test Generation 124 121
Code Documentation 131 126
Regex Writing 119 120
CI/CD Pipelines 120 117
Frontend Component Design 122 92
CSV / Spreadsheet Cleanup 133 128
ETL Scripting 128 122
JSON Extraction 131 132
Bulk Data Labeling 129 130
OCR / Document Parsing 131 83
Table Extraction from PDFs 131 83
Long-Document Summarization 137 129
Short-Form Summarization 123 124
Blog Post Writing 121 119

Scores reflect capability match + benchmark data + pricing for each task. Methodology →

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