head-to-head

Z.ai: GLM Flash Latest vs OpenAI: GPT-5.6 Terra

Side-by-side comparison of specs, pricing, benchmark scores, and task rankings. Updated 2026-10-19.

Z.ai: GLM Flash Latest OpenAI: GPT-5.6 Terra
Vendor~z-aiopenai
Quality Score100100
Benchmark Score-70.0
Input Price$0.05/M$2.00/M
Output Price$0.20/M$12.00/M
Context Window1,048,5761,050,000
Max Output943,718128,000
Tool Calling✓✓
Structured Output✓✓
Reasoning Mode✓✓
Vision✓✓
Audio--
Benchmark Scores
ai_index-69.4

The verdict

For a sample job of 1 million input tokens and 250,000 output tokens, GLM Flash Latest costs $0.098 and GPT-5.6 Terra costs $5.00, so GLM Flash Latest is about 51.0 times cheaper for the same work.

Both take in a similar amount of text: 1,048,576 and 1,050,000 tokens, about 1,573 and 1,575 pages.

Only GLM Flash Latest offers video input.

Across the 20 tasks where they differ, GLM Flash Latest scores higher on 4 (Code Completion, JSON Extraction, Bulk Data Labeling and others), GPT-5.6 Terra on 16 (SQL Generation, Code Review, Code Refactoring and others).

GLM Flash Latest was released in August 2026 and GPT-5.6 Terra in July 2026.

Pick GLM Flash Latest if you need lower cost or video input; pick GPT-5.6 Terra if you need the stronger all-round task scores.

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 Flash LatestOpenAI: GPT-5.6 Terra
SQL Generation 134 140
Code Review 132 145
Code Completion 132 118
Code Refactoring 136 147
Bug Fixing 136 149
Unit Test Generation 124 132
Code Documentation 132 135
Regex Writing 120 124
CI/CD Pipelines 120 128
Frontend Component Design 122 130
Data Analysis 124 134
CSV / Spreadsheet Cleanup 134 135
ETL Scripting 128 137
JSON Extraction 132 121
Bulk Data Labeling 129 117
OCR / Document Parsing 131 134
Table Extraction from PDFs 131 134
Long-Document Summarization 138 147
Short-Form Summarization 124 116
Blog Post Writing 122 128

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

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