head-to-head

OpenAI: GPT-6.1 Sol vs DeepSeek: DeepSeek V4.1 Flash (batch)

Side-by-side comparison of specs, pricing, benchmark scores, and task rankings. Updated 2026-09-30.

OpenAI: GPT-6.1 Sol DeepSeek: DeepSeek V4.1 Flash (batch)
Vendoropenaideepseek
Quality Score100100
Benchmark Score89.266.3
Input Price$2.00/M$0.11/M
Output Price$10.00/M$0.34/M
Context Window1,050,0001,048,576
Max Output128,000131,072
Tool Calling✓✓
Structured Output✓✓
Reasoning Mode✓✓
Vision✓✓
Audio--
Benchmark Scores
ai_index85.565.1

The verdict

For a sample job of 1 million input tokens and 250,000 output tokens, DeepSeek V4.1 Flash (batch) costs $0.20 and GPT-6.1 Sol costs $4.50, so DeepSeek V4.1 Flash (batch) is about 23.0 times cheaper for the same work.

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

On our blended benchmark score GPT-6.1 Sol leads 89.2 to 66.3.

Across the 20 tasks where they differ, GPT-6.1 Sol scores higher on 13 (SQL Generation, Code Review, Code Refactoring and others), DeepSeek V4.1 Flash (batch) on 7 (Code Completion, Code Documentation, Regex Writing and others).

Pick GPT-6.1 Sol if you need benchmark performance; pick DeepSeek V4.1 Flash (batch) 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?

TaskOpenAI: GPT-6.1 SolDeepSeek: DeepSeek V4.1 Flash (batch)
SQL Generation 143 141
Code Review 148 144
Code Completion 119 133
Code Refactoring 149 146
Bug Fixing 152 148
Unit Test Generation 134 131
Code Documentation 137 137
Regex Writing 126 126
CI/CD Pipelines 130 127
Frontend Component Design 132 129
Data Analysis 136 133
CSV / Spreadsheet Cleanup 136 136
ETL Scripting 140 137
JSON Extraction 121 131
Bulk Data Labeling 118 129
OCR / Document Parsing 135 134
Table Extraction from PDFs 135 134
Long-Document Summarization 150 148
Short-Form Summarization 117 127
Blog Post Writing 131 129

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

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