head-to-head

DeepSeek: DeepSeek V4.1 Flash vs OpenAI: GPT-5.6 Luna (batch)

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

DeepSeek: DeepSeek V4.1 Flash OpenAI: GPT-5.6 Luna (batch)
Vendordeepseekopenai
Quality Score100100
Benchmark Score-89.4
Input Price$0.05/M$0.10/M
Output Price$0.57/M$0.60/M
Context Window1,048,5761,050,000
Max Output943,718128,000
Tool Calling✓✓
Structured Output✓✓
Reasoning Mode✓✓
Vision✓✓
Audio--
Benchmark Scores
ai_index-84.5
ai_index_agentic-75.2
ai_index_coding-100.0

The verdict

For a sample job of 1 million input tokens and 250,000 output tokens, DeepSeek V4.1 Flash costs $0.19 and GPT-5.6 Luna (batch) costs $0.25, so DeepSeek V4.1 Flash is about 1.3 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, GPT-5.6 Luna (batch) on 20 (SQL Generation, Code Review, Code Completion and others).

DeepSeek V4.1 Flash was released in September 2026 and GPT-5.6 Luna (batch) in July 2026.

Pick DeepSeek V4.1 Flash if you need lower cost; pick GPT-5.6 Luna (batch) 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?

TaskDeepSeek: DeepSeek V4.1 FlashOpenAI: GPT-5.6 Luna (batch)
SQL Generation 133 171
Code Review 132 166
Code Completion 131 133
Code Refactoring 136 163
Bug Fixing 136 179
Unit Test Generation 124 154
Code Documentation 131 143
Regex Writing 119 136
CI/CD Pipelines 120 144
Frontend Component Design 122 146
Data Analysis 124 170
CSV / Spreadsheet Cleanup 133 154
ETL Scripting 128 154
JSON Extraction 131 149
Bulk Data Labeling 129 135
OCR / Document Parsing 131 146
Table Extraction from PDFs 131 146
Long-Document Summarization 137 160
Short-Form Summarization 123 132
Blog Post Writing 121 140

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

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