head-to-head

Anthropic: Claude Sonnet 5.5 (batch) vs DeepSeek: DeepSeek Flash Latest

Side-by-side comparison of specs, pricing, benchmark scores, and task rankings. Updated 2026-09-29.

Anthropic: Claude Sonnet 5.5 (batch) DeepSeek: DeepSeek Flash Latest
Vendoranthropic~deepseek
Quality Score100100
Benchmark Score97.0-
Input Price$1.00/M$0.02/M
Output Price$5.00/M$0.60/M
Context Window1,000,0001,048,576
Max Output128,000943,718
Tool Calling✓✓
Structured Output✓✓
Reasoning Mode✓✓
Vision✓✓
Audio--
Benchmark Scores
ai_index92.4-

The verdict

For a sample job of 1 million input tokens and 250,000 output tokens, DeepSeek Flash Latest costs $0.17 and Claude Sonnet 5.5 (batch) costs $2.25, so DeepSeek Flash Latest is about 13.2 times cheaper for the same work.

Both take in a similar amount of text: 1,000,000 and 1,048,576 tokens, about 1,500 and 1,573 pages.

Across the 20 tasks where they differ, Claude Sonnet 5.5 (batch) scores higher on 16 (SQL Generation, Code Review, Code Refactoring and others), DeepSeek Flash Latest on 4 (Code Completion, JSON Extraction, Bulk Data Labeling and others).

Pick Claude Sonnet 5.5 (batch) if you need the stronger all-round task scores; pick DeepSeek Flash Latest 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?

TaskAnthropic: Claude Sonnet 5.5 (batch)DeepSeek: DeepSeek Flash Latest
SQL Generation 144 133
Code Review 149 132
Code Completion 120 131
Code Refactoring 150 136
Bug Fixing 153 136
Unit Test Generation 135 124
Code Documentation 139 131
Regex Writing 128 119
CI/CD Pipelines 131 120
Frontend Component Design 133 122
Data Analysis 137 124
CSV / Spreadsheet Cleanup 137 133
ETL Scripting 140 128
JSON Extraction 122 131
Bulk Data Labeling 120 129
OCR / Document Parsing 135 131
Table Extraction from PDFs 135 131
Long-Document Summarization 152 137
Short-Form Summarization 119 123
Blog Post Writing 132 121

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

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