Model decision surface
Compare AI models
Start with Jamba Large 1.7 and GPT-5.1-Codex-Max, 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
Jamba Large 1.7 vs GPT-5.1-Codex-Max
Live dataset updated 8/17/2026, 11:13:20 PM UTC
Open 1200×630 evidence receipt| Field | Jamba Large 1.7 AI21 Labs | GPT-5.1-Codex-Max OpenAI |
|---|---|---|
| ModelCap position | #110 | #109 |
| Index score | 22.5 | 22.5 |
| Evidence | Estimatedglobal corpus prior · leave-one-anchor-out calibrated | Estimatedpublisher corpus prior · leave-one-anchor-out calibrated |
| Input / 1M | $2.00 | $1.25 |
| Output / 1M | $8.00 | $10.00 |
| Pricing status | fresh | fresh |
| Context | 256K | 400K |
| Providers | 1 | 1 |
| Weight access | Gated access | API only |
Decision facts
- Jamba Large 1.7 is #110; GPT-5.1-Codex-Max is #109 on the same current language board.
- Index scores are 22.5 for Jamba Large 1.7 and 22.5 for GPT-5.1-Codex-Max.
- Both positions use Estimated evidence.
- Listed output price per 1M tokens is $8.00 for Jamba Large 1.7 and $10.00 for GPT-5.1-Codex-Max.
- Published context is 256,000 tokens for Jamba Large 1.7 and 400,000 for GPT-5.1-Codex-Max.
- Weight access differs: Jamba Large 1.7 is gated; GPT-5.1-Codex-Max is none.
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.