head-to-head

Meta: Muse Spark 1.3 vs ByteDance Seed: Seed-2.0-Code

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

Meta: Muse Spark 1.3 ByteDance Seed: Seed-2.0-Code
Vendormetabytedance-seed
Quality Score100100
Benchmark Score81.7-
Input Price$1.25/M$0.50/M
Output Price$4.25/M$3.00/M
Context Window1,048,576262,144
Max Output943,718131,072
Tool Calling✓✓
Structured Output✓✓
Reasoning Mode✓✓
Vision✓✓
Audio--
Benchmark Scores
ai_index79.4-

The verdict

For a sample job of 1 million input tokens and 250,000 output tokens, Seed-2.0-Code costs $1.25 and Muse Spark 1.3 costs $2.31, so Seed-2.0-Code is about 1.9 times cheaper for the same work.

Muse Spark 1.3 reads up to 1,048,576 tokens at once, roughly 1,573 pages of text, against about 393 pages for Seed-2.0-Code.

Across the 20 tasks where they differ, Muse Spark 1.3 scores higher on 16 (SQL Generation, Code Review, Code Refactoring and others), Seed-2.0-Code on 4 (Code Completion, JSON Extraction, Bulk Data Labeling and others).

Muse Spark 1.3 was released in September 2026 and Seed-2.0-Code in August 2026.

Pick Muse Spark 1.3 if you need long documents or the stronger all-round task scores; pick Seed-2.0-Code 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?

TaskMeta: Muse Spark 1.3ByteDance Seed: Seed-2.0-Code
SQL Generation 143 130
Code Review 147 126
Code Completion 120 128
Code Refactoring 148 127
Bug Fixing 151 130
Unit Test Generation 133 121
Code Documentation 138 125
Regex Writing 126 119
CI/CD Pipelines 129 117
Frontend Component Design 131 122
Data Analysis 135 124
CSV / Spreadsheet Cleanup 136 128
ETL Scripting 139 122
JSON Extraction 122 131
Bulk Data Labeling 120 128
OCR / Document Parsing 135 128
Table Extraction from PDFs 135 128
Long-Document Summarization 150 129
Short-Form Summarization 118 123
Blog Post Writing 131 118

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

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