Meta: Muse Wonder vs DeepSeek: DeepSeek V4.1 Flash (batch)
Side-by-side comparison of specs, pricing, benchmark scores, and task rankings. Updated 2026-10-13.
| Meta: Muse Wonder | DeepSeek: DeepSeek V4.1 Flash (batch) | |
|---|---|---|
| Vendor | meta | deepseek |
| Quality Score | 100 | 100 |
| Benchmark Score | 90.2 | 66.3 |
| Input Price | $4.00/M | $0.11/M |
| Output Price | $20.00/M | $0.34/M |
| Context Window | 1,048,576 | 1,048,576 |
| Max Output | 943,718 | 131,072 |
| Tool Calling | ✓ | ✓ |
| Structured Output | ✓ | ✓ |
| Reasoning Mode | ✓ | ✓ |
| Vision | ✓ | ✓ |
| Audio | ✓ | - |
| Benchmark Scores | ||
| ai_index | 86.4 | 65.1 |
The verdict
For a sample job of 1 million input tokens and 250,000 output tokens, DeepSeek V4.1 Flash (batch) costs $0.20 and Muse Wonder costs $9.00, so DeepSeek V4.1 Flash (batch) is about 45.9 times cheaper for the same work.
Both read up to 1,048,576 tokens at once, roughly 1,573 pages of text.
Only Muse Wonder offers audio input and video input.
On our blended benchmark score Muse Wonder leads 90.2 to 66.3.
Across the 20 tasks where they differ, Muse Wonder scores higher on 13 (SQL Generation, Code Review, Code Refactoring and others), DeepSeek V4.1 Flash (batch) on 7 (Code Completion, Code Documentation, Regex Writing and others).
Muse Wonder was released in October 2026 and DeepSeek V4.1 Flash (batch) in September 2026.
Pick Muse Wonder if you need audio input, video input or benchmark performance; pick DeepSeek V4.1 Flash (batch) 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?
| Task | Meta: Muse Wonder | DeepSeek: DeepSeek V4.1 Flash (batch) |
|---|---|---|
| SQL Generation | 142 | 141 |
| Code Review | 148 | 144 |
| Code Completion | 116 | 133 |
| Code Refactoring | 149 | 146 |
| Bug Fixing | 152 | 148 |
| Unit Test Generation | 134 | 131 |
| Code Documentation | 135 | 137 |
| Regex Writing | 123 | 126 |
| CI/CD Pipelines | 130 | 127 |
| Frontend Component Design | 132 | 129 |
| Data Analysis | 137 | 133 |
| CSV / Spreadsheet Cleanup | 135 | 136 |
| ETL Scripting | 140 | 137 |
| JSON Extraction | 119 | 131 |
| Bulk Data Labeling | 114 | 129 |
| OCR / Document Parsing | 135 | 134 |
| Table Extraction from PDFs | 135 | 134 |
| Long-Document Summarization | 149 | 148 |
| Short-Form Summarization | 115 | 127 |
| Blog Post Writing | 130 | 129 |
Scores reflect capability match + benchmark data + pricing for each task. Methodology →