head-to-head

MoonshotAI: Kimi K3.1 Pro vs NVIDIA: Nemotron 3.5 Super VL (free)

Side-by-side comparison of specs, pricing, benchmark scores, and task rankings. Updated 2026-10-24.

MoonshotAI: Kimi K3.1 Pro NVIDIA: Nemotron 3.5 Super VL (free)
Vendormoonshotainvidia
Quality Score100100
Benchmark Score95.140.1
Input Price$2.00/MFree
Output Price$10.00/MFree
Context Window1,048,5761,000,000
Max Output943,718131,072
Tool Calling✓✓
Structured Output✓✓
Reasoning Mode✓✓
Vision✓✓
Audio--
Benchmark Scores
ai_index90.943.7

The verdict

For a sample job of 1 million input tokens and 250,000 output tokens, Nemotron 3.5 Super VL (free) costs $0 and Kimi K3.1 Pro costs $4.50, so Nemotron 3.5 Super VL (free) is free for the same work.

Both take in a similar amount of text: 1,048,576 and 1,000,000 tokens, about 1,573 and 1,500 pages.

On our blended benchmark score Kimi K3.1 Pro leads 95.1 to 40.1.

Across the 20 tasks where they differ, Kimi K3.1 Pro scores higher on 16 (SQL Generation, Code Review, Code Refactoring and others), Nemotron 3.5 Super VL (free) on 4 (Code Completion, JSON Extraction, Bulk Data Labeling and others).

Pick Kimi K3.1 Pro if you need benchmark performance or the stronger all-round task scores; pick Nemotron 3.5 Super VL (free) 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?

TaskMoonshotAI: Kimi K3.1 ProNVIDIA: Nemotron 3.5 Super VL (free)
SQL Generation 143 139
Code Review 149 140
Code Completion 119 132
Code Refactoring 150 143
Bug Fixing 153 144
Unit Test Generation 134 129
Code Documentation 137 135
Regex Writing 126 124
CI/CD Pipelines 130 125
Frontend Component Design 132 127
Data Analysis 137 130
CSV / Spreadsheet Cleanup 136 135
ETL Scripting 140 134
JSON Extraction 121 132
Bulk Data Labeling 118 130
OCR / Document Parsing 135 133
Table Extraction from PDFs 135 133
Long-Document Summarization 151 145
Short-Form Summarization 118 126
Blog Post Writing 131 127

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

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