Model decision surface
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Start with Mistral Large 3 2512 and Laguna XS 2.1, 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
Mistral Large 3 2512 vs Laguna XS 2.1
Live dataset updated 9/9/2026, 9:50:24 PM UTC
Open 1200×630 evidence receipt| Field | Mistral Large 3 2512 Mistral AI | Laguna XS 2.1 Poolside |
|---|---|---|
| ModelCap position | #55 | #60 |
| Index score | 56.5 | 54.9 |
| Evidence | Measured2 public benchmark observations across 2 boards | Estimated3 reported rows against measured corpus ladders (30%); global-corpus-prior over 180 held-out anchors (70%); shrunk 1.3 toward the measured corpus |
| Input / 1M | $0.50 | $0.06 |
| Output / 1M | $1.50 | $0.12 |
| Pricing status | fresh | fresh |
| Context | 262K | 262K |
| Providers | 1 | 1 |
| Weight access | API only | Restricted license |
Decision facts
- Mistral Large 3 2512 is #55; Laguna XS 2.1 is #60 on the same current language board.
- Index scores are 56.5 for Mistral Large 3 2512 and 54.9 for Laguna XS 2.1. Their published uncertainty intervals overlap, so the rank difference alone does not establish a reliable capability advantage for your workload.
- Evidence differs: Mistral Large 3 2512 is Measured; Laguna XS 2.1 is Estimated.
- Listed output price per 1M tokens is $1.50 for Mistral Large 3 2512 and $0.12 for Laguna XS 2.1. For 1,000 requests with 2,000 input and 500 output tokens each (2M input + 0.5M output), the listed-rate estimate is $1.75 for Mistral Large 3 2512 versus $0.18 for Laguna XS 2.1. Laguna XS 2.1 costs 89.7% less in this scenario. This excludes caching, batch discounts, prompt-length tiers, tool charges and retries; verify the selected endpoint before budgeting.
- Published context is 262,144 tokens for Mistral Large 3 2512 and 262,144 for Laguna XS 2.1.
- Weight access differs: Mistral Large 3 2512 is none; Laguna XS 2.1 is restricted.
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.