Model decision surface
Compare AI models
Start with Ling-2.6-1T and Ling-3.0-flash, 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 Ling-3.0-flash
Live dataset updated 8/17/2026, 11:13:20 PM UTC
Open 1200×630 evidence receipt| Field | Ling-2.6-1T InclusionAI | Ling-3.0-flash InclusionAI |
|---|---|---|
| ModelCap position | #74 | #42 |
| Index score | 36.0 | 53.0 |
| Evidence | Measured1 public benchmark observation across 1 board | Measured1 public benchmark observation across 1 board |
| Input / 1M | $0.075 | $0.021 |
| Output / 1M | $0.625 | $0.063 |
| Pricing status | fresh | fresh |
| Context | 262K | 262K |
| Providers | 1 | 2 |
| Weight access | API only | Open weights |
Decision facts
- Ling-2.6-1T is #74; Ling-3.0-flash is #42 on the same current language board.
- Index scores are 36.0 for Ling-2.6-1T and 53.0 for Ling-3.0-flash.
- Both positions use Measured evidence.
- Listed output price per 1M tokens is $0.63 for Ling-2.6-1T and $0.06 for Ling-3.0-flash.
- Published context is 262,144 tokens for Ling-2.6-1T and 262,144 for Ling-3.0-flash.
- Weight access differs: Ling-2.6-1T is none; Ling-3.0-flash is open.
- ModelCap currently lists 1 providers for Ling-2.6-1T and 2 for Ling-3.0-flash.
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.