head-to-head

PrismML: Ternary Bonsai 2 9B vs Xiaomi: MiMo-V2.6-Pro

Side-by-side comparison of specs, pricing, benchmark scores, and task rankings. Updated 2026-11-02.

PrismML: Ternary Bonsai 2 9B Xiaomi: MiMo-V2.6-Pro
Vendorprism-mlxiaomi
Quality Score100100
Input Price$0.08/M$0.43/M
Output Price$0.13/M$0.87/M
Context Window262,1441,050,000
Max Output65,536131,072
Tool Calling✓✓
Structured Output✓✓
Reasoning Mode✓✓
Vision✓✓
Audio-✓

The verdict

For a sample job of 1 million input tokens and 250,000 output tokens, Ternary Bonsai 2 9B costs $0.11 and MiMo-V2.6-Pro costs $0.65, so Ternary Bonsai 2 9B is about 5.8 times cheaper for the same work.

MiMo-V2.6-Pro reads up to 1,050,000 tokens at once, roughly 1,575 pages of text, against about 393 pages for Ternary Bonsai 2 9B.

Only MiMo-V2.6-Pro offers audio input and video input.

Across the 18 tasks where they differ, Ternary Bonsai 2 9B scores higher on 4 (Regex Writing, JSON Extraction, Bulk Data Labeling and others), MiMo-V2.6-Pro on 14 (SQL Generation, Code Review, Code Completion and others).

Ternary Bonsai 2 9B was released in October 2026 and MiMo-V2.6-Pro in September 2026.

Pick Ternary Bonsai 2 9B if you need lower cost; pick MiMo-V2.6-Pro if you need long documents, 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?

TaskPrismML: Ternary Bonsai 2 9BXiaomi: MiMo-V2.6-Pro
SQL Generation 131 133
Code Review 126 132
Code Completion 129 131
Code Refactoring 127 136
Bug Fixing 130 136
Unit Test Generation 121 124
Code Documentation 126 131
Regex Writing 120 119
CI/CD Pipelines 117 120
CSV / Spreadsheet Cleanup 128 133
ETL Scripting 122 128
JSON Extraction 132 131
Bulk Data Labeling 129 129
OCR / Document Parsing 128 131
Table Extraction from PDFs 128 131
Long-Document Summarization 129 137
Short-Form Summarization 124 123
Blog Post Writing 119 121

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

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