head-to-head

DeepSeek: DeepSeek V4 Flash Vision Exp vs OpenAI: GPT-5.6 Terra Pro (batch)

Side-by-side comparison of specs, pricing, benchmark scores, and task rankings. Updated 2026-10-06.

DeepSeek: DeepSeek V4 Flash Vision Exp OpenAI: GPT-5.6 Terra Pro (batch)
Vendordeepseekopenai
Quality Score100100
Benchmark Score57.7-
Input Price$0.22/M$1.00/M
Output Price$0.65/M$6.00/M
Context Window1,048,5761,050,000
Max Output262,144128,000
Tool Calling✓✓
Structured Output✓✓
Reasoning Mode✓✓
Vision✓✓
Audio--
Benchmark Scores
ai_index57.5-

The verdict

For a sample job of 1 million input tokens and 250,000 output tokens, DeepSeek V4 Flash Vision Exp costs $0.38 and GPT-5.6 Terra Pro (batch) costs $2.50, so DeepSeek V4 Flash Vision Exp is about 6.6 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.

Across the 20 tasks where they differ, DeepSeek V4 Flash Vision Exp scores higher on 20 (SQL Generation, Code Review, Code Completion and others).

DeepSeek V4 Flash Vision Exp was released in August 2026 and GPT-5.6 Terra Pro (batch) in July 2026.

Pick DeepSeek V4 Flash Vision Exp if you need lower cost or 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?

TaskDeepSeek: DeepSeek V4 Flash Vision ExpOpenAI: GPT-5.6 Terra Pro (batch)
SQL Generation 140 133
Code Review 142 132
Code Completion 133 118
Code Refactoring 145 136
Bug Fixing 146 136
Unit Test Generation 130 124
Code Documentation 137 130
Regex Writing 125 118
CI/CD Pipelines 126 120
Frontend Component Design 128 122
Data Analysis 132 124
CSV / Spreadsheet Cleanup 136 133
ETL Scripting 136 128
JSON Extraction 131 122
Bulk Data Labeling 129 119
OCR / Document Parsing 133 131
Table Extraction from PDFs 133 131
Long-Document Summarization 147 137
Short-Form Summarization 126 114
Blog Post Writing 128 121

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

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