Model decision surface
Compare AI models
Start with Ling 3.0 Flash VL and Laguna S 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
Ling 3.0 Flash VL vs Laguna S 2.1
Live dataset updated 9/15/2026, 8:34:26 PM UTC
Open 1200×630 evidence receipt| Field | Ling 3.0 Flash VL InclusionAI | Laguna S 2.1 Poolside |
|---|---|---|
| ModelCap position | #59 | #46 |
| Index score | 57.6 | 62.3 |
| Evidence | Measured1 public benchmark observation across 1 board | Estimated5 reported rows against measured corpus ladders (66%); global-corpus-prior over 193 held-out anchors (34%); shrunk 5.3 toward the measured corpus |
| Input / 1M | $0.06 | $0.09 |
| Output / 1M | $0.18 | $0.18 |
| Pricing status | fresh | fresh |
| Context | 131K | 1M |
| Providers | 1 | 1 |
| Weight access | Open weights | Restricted license |
Decision facts
- Ling 3.0 Flash VL is #59; Laguna S 2.1 is #46 on the same current language board.
- Index scores are 57.6 for Ling 3.0 Flash VL and 62.3 for Laguna S 2.1. Their published uncertainty intervals overlap, so the rank difference alone does not establish a reliable capability advantage for your workload.
- Evidence differs: Ling 3.0 Flash VL is Measured; Laguna S 2.1 is Estimated.
- Listed output price per 1M tokens is $0.18 for Ling 3.0 Flash VL and $0.18 for Laguna S 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 $0.21 for Ling 3.0 Flash VL versus $0.27 for Laguna S 2.1. Ling 3.0 Flash VL costs 22.2% 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 131,072 tokens for Ling 3.0 Flash VL and 1,048,576 for Laguna S 2.1.
- Weight access differs: Ling 3.0 Flash VL is open; Laguna S 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.