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Start with Laguna XS 2.1 and Inkling Small, 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.

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Current public data

Laguna XS 2.1 vs Inkling Small

Live dataset updated 9/9/2026, 8:46:14 PM UTC

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Factual comparison of Laguna XS 2.1 and Inkling Small
Field	Laguna XS 2.1 Poolside	Inkling Small Thinking Machines
ModelCap position	#61	#64
Index score	54.1	53.3
Evidence	Estimated3 reported rows against measured corpus ladders (30%); global-corpus-prior over 182 held-out anchors (70%); shrunk 1.4 toward the measured corpus	Measured5 public benchmark observations across 5 boards
Input / 1M	$0.06	$0.45
Output / 1M	$0.12	$1.20
Pricing status	fresh	fresh
Context	262K	1M
Providers	1	3
Weight access	Restricted license	Open weights

Decision facts

Laguna XS 2.1 is #61; Inkling Small is #64 on the same current language board.
Index scores are 54.1 for Laguna XS 2.1 and 53.3 for Inkling Small. Their published uncertainty intervals overlap, so the rank difference alone does not establish a reliable capability advantage for your workload.
Evidence differs: Laguna XS 2.1 is Estimated; Inkling Small is Measured.
Listed output price per 1M tokens is $0.12 for Laguna XS 2.1 and $1.20 for Inkling Small. For 1,000 requests with 2,000 input and 500 output tokens each (2M input + 0.5M output), the listed-rate estimate is $0.18 for Laguna XS 2.1 versus $1.50 for Inkling Small. Laguna XS 2.1 costs 88.0% 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 Laguna XS 2.1 and 1,048,576 for Inkling Small.
Weight access differs: Laguna XS 2.1 is restricted; Inkling Small is open.
ModelCap currently lists 1 providers for Laguna XS 2.1 and 3 for Inkling Small.

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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