head-to-head

Meta: Muse Spark 1.2 Contributor vs OpenAI: GPT-5.6 Luna

Side-by-side comparison of specs, pricing, benchmark scores, and task rankings. Updated 2026-10-06.

Meta: Muse Spark 1.2 Contributor OpenAI: GPT-5.6 Luna
Vendormetaopenai
Quality Score100100
Benchmark Score-62.3
Input Price$0.10/M$0.20/M
Output Price$0.20/M$1.20/M
Context Window1,048,5761,050,000
Max Output943,718128,000
Tool Calling✓✓
Structured Output✓✓
Reasoning Mode✓✓
Vision✓✓
Audio--
Benchmark Scores
ai_index-61.6

The verdict

For a sample job of 1 million input tokens and 250,000 output tokens, Muse Spark 1.2 Contributor costs $0.15 and GPT-5.6 Luna costs $0.50, so Muse Spark 1.2 Contributor is about 3.3 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.

Only Muse Spark 1.2 Contributor offers video input.

Across the 20 tasks where they differ, Muse Spark 1.2 Contributor scores higher on 2 (JSON Extraction, Bulk Data Labeling), GPT-5.6 Luna on 18 (SQL Generation, Code Review, Code Completion and others).

Muse Spark 1.2 Contributor was released in August 2026 and GPT-5.6 Luna in July 2026.

Pick Muse Spark 1.2 Contributor if you need lower cost or video input; pick GPT-5.6 Luna 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?

TaskMeta: Muse Spark 1.2 ContributorOpenAI: GPT-5.6 Luna
SQL Generation 134 141
Code Review 132 143
Code Completion 131 133
Code Refactoring 136 145
Bug Fixing 136 147
Unit Test Generation 124 131
Code Documentation 131 137
Regex Writing 119 125
CI/CD Pipelines 120 127
Frontend Component Design 122 129
Data Analysis 124 133
CSV / Spreadsheet Cleanup 134 136
ETL Scripting 128 136
JSON Extraction 131 131
Bulk Data Labeling 129 129
OCR / Document Parsing 131 134
Table Extraction from PDFs 131 134
Long-Document Summarization 138 147
Short-Form Summarization 123 126
Blog Post Writing 122 129

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

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