head-to-head

OpenAI: GPT-6.1 Sol (batch) vs Anthropic: Claude Opus 5.5 (batch)

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

OpenAI: GPT-6.1 Sol (batch) Anthropic: Claude Opus 5.5 (batch)
Vendoropenaianthropic
Quality Score100100
Benchmark Score89.2100.0
Input Price$1.00/M$2.00/M
Output Price$5.00/M$10.00/M
Context Window1,050,0001,000,000
Max Output128,000128,000
Tool Calling✓✓
Structured Output✓✓
Reasoning Mode✓✓
Vision✓✓
Audio--
Benchmark Scores
ai_index85.595.1

The verdict

For a sample job of 1 million input tokens and 250,000 output tokens, GPT-6.1 Sol (batch) costs $2.25 and Claude Opus 5.5 (batch) costs $4.50, so GPT-6.1 Sol (batch) is about 2.0 times cheaper for the same work.

Both take in a similar amount of text: 1,050,000 and 1,000,000 tokens, about 1,575 and 1,500 pages.

On our blended benchmark score Claude Opus 5.5 (batch) leads 100.0 to 89.2.

Across the 20 tasks where they differ, GPT-6.1 Sol (batch) scores higher on 7 (Code Completion, Code Documentation, Regex Writing and others), Claude Opus 5.5 (batch) on 13 (SQL Generation, Code Review, Code Refactoring and others).

Pick GPT-6.1 Sol (batch) if you need lower cost; pick Claude Opus 5.5 (batch) if you need benchmark performance.

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 Sol (batch)Anthropic: Claude Opus 5.5 (batch)
SQL Generation 143 144
Code Review 148 150
Code Completion 120 119
Code Refactoring 149 151
Bug Fixing 152 154
Unit Test Generation 134 135
Code Documentation 138 138
Regex Writing 127 127
CI/CD Pipelines 130 131
Frontend Component Design 132 133
Data Analysis 136 138
CSV / Spreadsheet Cleanup 136 136
ETL Scripting 140 141
JSON Extraction 122 121
Bulk Data Labeling 120 118
OCR / Document Parsing 135 135
Table Extraction from PDFs 135 135
Long-Document Summarization 151 152
Short-Form Summarization 119 118
Blog Post Writing 131 132

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

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