head-to-head

DeepSeek: DeepSeek V4.1 Flash 1017 vs Google: Gemini 4 Argon

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

DeepSeek: DeepSeek V4.1 Flash 1017 Google: Gemini 4 Argon
Vendordeepseekgoogle
Quality Score100100
Benchmark Score-90.2
Input Price$0.15/M$2.00/M
Output Price$0.60/M$10.00/M
Context Window1,048,5761,048,576
Max Output393,216943,718
Tool Calling✓✓
Structured Output✓✓
Reasoning Mode✓✓
Vision✓✓
Audio-✓
Benchmark Scores
ai_index-86.7

The verdict

For a sample job of 1 million input tokens and 250,000 output tokens, DeepSeek V4.1 Flash 1017 costs $0.30 and Gemini 4 Argon costs $4.50, so DeepSeek V4.1 Flash 1017 is about 15.0 times cheaper for the same work.

Both read up to 1,048,576 tokens at once, roughly 1,573 pages of text.

Only Gemini 4 Argon offers audio input and video input.

Across the 20 tasks where they differ, DeepSeek V4.1 Flash 1017 scores higher on 4 (Code Completion, JSON Extraction, Bulk Data Labeling and others), Gemini 4 Argon on 16 (SQL Generation, Code Review, Code Refactoring and others).

Pick DeepSeek V4.1 Flash 1017 if you need lower cost; pick Gemini 4 Argon if you need audio input, video input 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 V4.1 Flash 1017Google: Gemini 4 Argon
SQL Generation 133 143
Code Review 132 148
Code Completion 131 119
Code Refactoring 136 149
Bug Fixing 136 152
Unit Test Generation 124 134
Code Documentation 131 137
Regex Writing 119 126
CI/CD Pipelines 120 130
Frontend Component Design 122 132
Data Analysis 124 137
CSV / Spreadsheet Cleanup 133 136
ETL Scripting 128 140
JSON Extraction 131 121
Bulk Data Labeling 129 118
OCR / Document Parsing 131 135
Table Extraction from PDFs 131 135
Long-Document Summarization 137 150
Short-Form Summarization 123 117
Blog Post Writing 121 131

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

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