Model decision surface
Compare AI models
Start with Ling-3.0-flash and Nemotron 3 Super, or choose any two current ranked language models. Compare capability evidence, price, context, provider availability, and weight access without pretending one field decides every use case.
Current public data
Ling-3.0-flash vs Nemotron 3 Super
Live dataset updated 8/18/2026, 3:36:20 AM UTC
Open 1200×630 evidence receipt| Field | Ling-3.0-flash InclusionAI | Nemotron 3 Super NVIDIA |
|---|---|---|
| ModelCap position | #41 | #75 |
| Index score | 53.0 | 35.8 |
| Evidence | Measured1 public benchmark observation across 1 board | Measured3 public benchmark observations across 3 boards |
| Input / 1M | $0.021 | $0.085 |
| Output / 1M | $0.063 | $0.40 |
| Pricing status | fresh | fresh |
| Context | 262K | 1M |
| Providers | 2 | 3 |
| Weight access | Open weights | Restricted license |
Decision facts
- Ling-3.0-flash is #41; Nemotron 3 Super is #75 on the same current language board.
- Index scores are 53.0 for Ling-3.0-flash and 35.8 for Nemotron 3 Super.
- Both positions use Measured evidence.
- Listed output price per 1M tokens is $0.06 for Ling-3.0-flash and $0.40 for Nemotron 3 Super.
- Published context is 262,144 tokens for Ling-3.0-flash and 1,000,000 for Nemotron 3 Super.
- Weight access differs: Ling-3.0-flash is open; Nemotron 3 Super is restricted.
- ModelCap currently lists 2 providers for Ling-3.0-flash and 3 for Nemotron 3 Super.
These are separate published fields, not a synthetic winner. ModelCap does not collapse price, access, context, and capability evidence into a hidden recommendation score.
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Each comparison page is a permanent, shareable URL with the same live figures as this tool: ModelCap Index position, API pricing, context window, provider count, weight access and every shared benchmark board.