head-to-head

OpenAI: GPT-5.6 Luna vs SpaceXAI: Grok 4.20

Side-by-side comparison of specs, pricing, benchmark scores, and task rankings. Updated 2026-11-07.

OpenAI: GPT-5.6 Luna SpaceXAI: Grok 4.20
Vendoropenaix-ai
Quality Score100100
Benchmark Score89.456.5
Input Price$0.20/M$1.25/M
Output Price$1.20/M$2.50/M
Context Window1,050,0002,000,000
Max Output128,0001,800,000
Tool Calling✓✓
Structured Output✓✓
Reasoning Mode✓✓
Vision✓✓
Audio--
Benchmark Scores
ai_index84.561.0
ai_index_agentic75.2-
ai_index_coding100.0-
eqbench-45.7

The verdict

For a sample job of 1 million input tokens and 250,000 output tokens, GPT-5.6 Luna costs $0.50 and Grok 4.20 costs $1.88, so GPT-5.6 Luna is about 3.8 times cheaper for the same work.

Grok 4.20 reads up to 2,000,000 tokens at once, roughly 3,000 pages of text, against about 1,575 pages for GPT-5.6 Luna.

On our blended benchmark score GPT-5.6 Luna leads 89.4 to 56.5.

Across the 20 tasks where they differ, GPT-5.6 Luna scores higher on 20 (SQL Generation, Code Review, Code Completion and others).

GPT-5.6 Luna was released in July 2026 and Grok 4.20 in March 2026.

Pick GPT-5.6 Luna if you need lower cost, benchmark performance or the stronger all-round task scores; pick Grok 4.20 if you need long documents.

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-5.6 LunaSpaceXAI: Grok 4.20
SQL Generation 171 144
Code Review 166 149
Code Completion 133 121
Code Refactoring 163 151
Bug Fixing 179 153
Unit Test Generation 154 134
Code Documentation 143 140
Regex Writing 136 127
CI/CD Pipelines 144 130
Frontend Component Design 146 131
Data Analysis 170 135
CSV / Spreadsheet Cleanup 154 138
ETL Scripting 154 141
JSON Extraction 149 123
Bulk Data Labeling 135 120
OCR / Document Parsing 146 135
Table Extraction from PDFs 146 135
Long-Document Summarization 159 153
Short-Form Summarization 132 119
Blog Post Writing 140 132

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

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