head-to-head

DeepSeek: DeepSeek V4.1 Flash 1017 vs Meta: Muse Spark Open

Side-by-side comparison of specs, pricing, benchmark scores, and task rankings. Updated 2026-10-19.

DeepSeek: DeepSeek V4.1 Flash 1017 Meta: Muse Spark Open
Vendordeepseekmeta
Quality Score100100
Benchmark Score-63.9
Input Price$0.15/M$1.25/M
Output Price$0.60/M$4.25/M
Context Window1,048,5761,048,576
Max Output393,216943,718
Tool Calling✓✓
Structured Output✓✓
Reasoning Mode✓✓
Vision✓✓
Audio-✓
Benchmark Scores
ai_index-64.1

The verdict

For a sample job of 1 million input tokens and 250,000 output tokens, DeepSeek V4.1 Flash 1017 costs $0.30 and Muse Spark Open costs $2.31, so DeepSeek V4.1 Flash 1017 is about 7.7 times cheaper for the same work.

Both read up to 1,048,576 tokens at once, roughly 1,573 pages of text.

Only Muse Spark Open offers audio input and video input.

Across the 20 tasks where they differ, DeepSeek V4.1 Flash 1017 scores higher on 4 (Code Completion, JSON Extraction, Bulk Data Labeling and others), Muse Spark Open on 16 (SQL Generation, Code Review, Code Refactoring and others).

Pick DeepSeek V4.1 Flash 1017 if you need lower cost; pick Muse Spark Open if you need audio input, video input or 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?

TaskDeepSeek: DeepSeek V4.1 Flash 1017Meta: Muse Spark Open
SQL Generation 133 141
Code Review 132 144
Code Completion 131 120
Code Refactoring 136 146
Bug Fixing 136 148
Unit Test Generation 124 131
Code Documentation 131 136
Regex Writing 119 125
CI/CD Pipelines 120 127
Frontend Component Design 122 129
Data Analysis 124 133
CSV / Spreadsheet Cleanup 133 136
ETL Scripting 128 137
JSON Extraction 131 122
Bulk Data Labeling 129 120
OCR / Document Parsing 131 134
Table Extraction from PDFs 131 134
Long-Document Summarization 137 147
Short-Form Summarization 123 118
Blog Post Writing 121 129

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

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