head-to-head
Meta: Muse Spark 1.1 vs Google: Gemma 4 26B A4B
Side-by-side comparison of specs, pricing, benchmark scores, and task rankings. Updated 2026-07-17.
| Meta: Muse Spark 1.1 | Google: Gemma 4 26B A4B | |
|---|---|---|
| Vendor | meta | |
| Quality Score | 100 | 100 |
| Benchmark Score | - | 52.0 |
| Input Price | $1.25/M | $0.10/M |
| Output Price | $4.25/M | $0.30/M |
| Context Window | 1,048,576 | 262,144 |
| Max Output | - | 256,000 |
| Tool Calling | ✓ | ✓ |
| Structured Output | ✓ | ✓ |
| Reasoning Mode | ✓ | ✓ |
| Vision | ✓ | ✓ |
| Audio | ✓ | - |
| Benchmark Scores | ||
| ai_index | - | 42.4 |
| ai_index_agentic | - | 18.1 |
| ai_index_coding | - | 64.9 |
| eqbench | - | 70.0 |
Who wins by task?
| Task | Meta: Muse Spark 1.1 | Google: Gemma 4 26B A4B |
|---|---|---|
| SQL Generation | 133 | 154 |
| Code Review | 132 | 151 |
| Code Completion | 118 | 132 |
| Code Refactoring | 136 | 150 |
| Bug Fixing | 136 | 158 |
| Unit Test Generation | 124 | 141 |
| Code Documentation | 130 | 137 |
| Regex Writing | 118 | 130 |
| CI/CD Pipelines | 120 | 134 |
| Frontend Component Design | 122 | 137 |
| Data Analysis | 124 | 149 |
| CSV / Spreadsheet Cleanup | 133 | 144 |
| ETL Scripting | 128 | 142 |
| JSON Extraction | 122 | 142 |
| Bulk Data Labeling | 120 | 133 |
| OCR / Document Parsing | 131 | 139 |
| Table Extraction from PDFs | 131 | 139 |
| Long-Document Summarization | 137 | 149 |
| Short-Form Summarization | 114 | 129 |
| Blog Post Writing | 121 | 132 |
Scores reflect capability match + benchmark data + pricing for each task. Methodology →
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