Model decision surface
Compare AI models
Start with MiniMax M1 80k and Nemotron 3.5 Lightning, 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
MiniMax M1 80k vs Nemotron 3.5 Lightning
Live dataset updated 9/9/2026, 9:50:24 PM UTC
Open 1200×630 evidence receipt| Field | MiniMax M1 80k MiniMaxAI | Nemotron 3.5 Lightning NVIDIA |
|---|---|---|
| ModelCap position | #70 | #89 |
| Index score | 52.1 | 44.9 |
| Evidence | Estimatedglobal-corpus-prior over 180 held-out anchors (20%); launch card against 5 resolved peers on 9 rows (81%); exceeds every named peer on 1 of 9 rows; optimism haircut 0 from cross-lab-probe; shrunk 0.5 up toward the measured corpus | Measured1 public benchmark observation across 1 board |
| Input / 1M | Unavailable | $0.08 |
| Output / 1M | Unavailable | $0.20 |
| Pricing status | unavailable | fresh |
| Context | 1M | 262K |
| Providers | 0 | 2 |
| Weight access | Open weights | Restricted license |
Decision facts
- MiniMax M1 80k is #70; Nemotron 3.5 Lightning is #89 on the same current language board.
- Index scores are 52.1 for MiniMax M1 80k and 44.9 for Nemotron 3.5 Lightning. Their published uncertainty intervals overlap, so the rank difference alone does not establish a reliable capability advantage for your workload.
- Evidence differs: MiniMax M1 80k is Estimated; Nemotron 3.5 Lightning is Measured.
- Published context is 1,000,000 tokens for MiniMax M1 80k and 262,144 for Nemotron 3.5 Lightning.
- Weight access differs: MiniMax M1 80k is open; Nemotron 3.5 Lightning is restricted.
- ModelCap currently lists 0 providers for MiniMax M1 80k and 2 for Nemotron 3.5 Lightning.
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.