Model decision surface
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Start with Relace Apply 3 and Sakana Namazu, 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
Relace Apply 3 vs Sakana Namazu
Live dataset updated 8/17/2026, 11:24:34 PM UTC
Open 1200×630 evidence receipt| Field | Relace Apply 3 Relace | Sakana Namazu Sakana AI |
|---|---|---|
| ModelCap position | #154 | #157 |
| Index score | 22.5 | 22.5 |
| Evidence | Estimatedglobal corpus prior · leave-one-anchor-out calibrated | Estimatedglobal corpus prior · leave-one-anchor-out calibrated |
| Input / 1M | $0.85 | $0.95 |
| Output / 1M | $1.25 | $4.00 |
| Pricing status | fresh | fresh |
| Context | 256K | 262K |
| Providers | 1 | 1 |
| Weight access | API only | API only |
Decision facts
- Relace Apply 3 is #154; Sakana Namazu is #157 on the same current language board.
- Index scores are 22.5 for Relace Apply 3 and 22.5 for Sakana Namazu.
- Both positions use Estimated evidence.
- Listed output price per 1M tokens is $1.25 for Relace Apply 3 and $4.00 for Sakana Namazu.
- Published context is 256,000 tokens for Relace Apply 3 and 262,144 for Sakana Namazu.
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.