Model decision surface
Compare AI models
Start with Ling-2.6-1T 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-2.6-1T vs Nemotron 3 Super
Live dataset updated 8/17/2026, 11:13:20 PM UTC
Open 1200×630 evidence receipt| Field | Ling-2.6-1T InclusionAI | Nemotron 3 Super NVIDIA |
|---|---|---|
| ModelCap position | #74 | #75 |
| Index score | 36.0 | 35.8 |
| Evidence | Measured1 public benchmark observation across 1 board | Measured3 public benchmark observations across 3 boards |
| Input / 1M | $0.075 | $0.085 |
| Output / 1M | $0.625 | $0.40 |
| Pricing status | fresh | fresh |
| Context | 262K | 1M |
| Providers | 1 | 3 |
| Weight access | API only | Restricted license |
Decision facts
- Ling-2.6-1T is #74; Nemotron 3 Super is #75 on the same current language board.
- Index scores are 36.0 for Ling-2.6-1T and 35.8 for Nemotron 3 Super.
- Both positions use Measured evidence.
- Listed output price per 1M tokens is $0.63 for Ling-2.6-1T and $0.40 for Nemotron 3 Super.
- Published context is 262,144 tokens for Ling-2.6-1T and 1,000,000 for Nemotron 3 Super.
- Weight access differs: Ling-2.6-1T is none; Nemotron 3 Super is restricted.
- ModelCap currently lists 1 providers for Ling-2.6-1T 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.