Inkling-Small vs Laguna S 2.1
Inkling-Small and Laguna S 2.1 are closely matched at 39.3 and 41.4 on the LLM Stats Score. Laguna S 2.1 is 4.2x cheaper per token.
Thinking Machines Lab · Poolside · Updated for 2026
Which is better?
Inkling-Small and Laguna S 2.1 are closely matched on the overall LLM Stats Score at 39.3 and 41.4.
In the 3 individual benchmarks reported for both models, Laguna S 2.1 wins 2; this is a narrower head-to-head signal than the composite indexes.
On price, Laguna S 2.1 is roughly 4.2x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Laguna S 2.1 also accepts a larger context window (1,048,576 input tokens), making it the stronger choice for long documents and large codebases.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose Inkling-Small
- you want the most recent training data — it shipped Jul 2026
Choose Laguna S 2.1
- you value its reported benchmark strengths — it wins 2 of 3 exact shared results
- cost matters — it's about 4.2x cheaper per token
- you process long inputs — it offers a 1,048,576 token context window
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
24 reported for Inkling-Small · 6 for Laguna S 2.1
Inkling-Small outperforms in 1 benchmarks (Toolathlon), while Laguna S 2.1 is better at 2 benchmarks (SWE-Bench Pro, Terminal-Bench 2.1).
Laguna S 2.1 shows notably better performance in the majority of benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, Inkling-Small ($0.30/1M tokens) is 3.0x more expensive than Laguna S 2.1 ($0.10/1M tokens).
For output processing, Inkling-Small ($1.20/1M tokens) is 6.0x more expensive than Laguna S 2.1 ($0.20/1M tokens).
In conclusion, Inkling-Small is more expensive than Laguna S 2.1.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Inkling-Small has 158.0B more parameters than Laguna S 2.1, making it 133.9% larger.
Context Window
Maximum input and output token capacity
Laguna S 2.1 accepts 1,048,576 input tokens compared to Inkling-Small's 256,000 tokens. Only Inkling-Small specifies output context (256,000 tokens).
Input capabilities
Documented input modalities across available providers
Inkling-Small supports multimodal inputs, whereas Laguna S 2.1 does not.
Inkling-Small can handle both text and other forms of data like images, making it suitable for multimodal applications.
Inkling-Small
Laguna S 2.1
License
Usage and distribution terms
Inkling-Small is licensed under Apache 2.0, while Laguna S 2.1 uses OpenMDW License v1.1.
License differences may affect how you can use these models in commercial or open-source projects.
Apache 2.0
Open weights
OpenMDW License v1.1
Open weights
Release Timeline
When each model was launched
Inkling-Small was released on 2026-07-30, while Laguna S 2.1 was released on 2026-07-21.
Inkling-Small is 0 month newer than Laguna S 2.1.
Jul 30, 2026
4 weeks ago
1w newerJul 21, 2026
1 months ago
Knowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
Inkling-Small is available from Thinking Machines Lab. Laguna S 2.1 is available from Poolside.
Inkling-Small
Laguna S 2.1
Outputs Comparison
Judge for yourself.
Run your own prompts against Inkling-Small and Laguna S 2.1 side-by-side, then vote on the output you prefer.
FAQ
Common questions about Inkling-Small vs Laguna S 2.1.