Kimi K2.5 vs Laguna XS 2.1
Kimi K2.5 leads the LLM Stats Score 38.8 to 24.4. Laguna XS 2.1 is 9.6x cheaper per token.
Moonshot AI · Poolside · Updated for 2026
Which is better?
Kimi K2.5 leads the overall LLM Stats Score 38.8 to 24.4, ranking #65 overall.
In the 4 individual benchmarks reported for both models, Kimi K2.5 wins 4; this is a narrower head-to-head signal than the composite indexes.
On price, Laguna XS 2.1 is roughly 9.6x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Laguna XS 2.1 also accepts a larger context window (262,144 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 Kimi K2.5
- overall performance matters — it scores 38.8 and ranks #65 on LLM Stats
- your work emphasizes reasoning and coding — it leads those capability indexes
- you value its reported benchmark strengths — it wins 4 of 4 exact shared results
Choose Laguna XS 2.1
- cost matters — it's about 9.6x cheaper per token
- you process long inputs — it offers a 262,144 token context window
- you want the most recent training data — it shipped Jul 2026
At a glance
The differences that matter most.
Individual benchmarks
40 reported for Kimi K2.5 · 4 for Laguna XS 2.1
Kimi K2.5 outperforms in 4 benchmarks (SWE-bench Multilingual, SWE-Bench Pro, SWE-Bench Verified, Terminal-Bench 2.0), while Laguna XS 2.1 is better at 0 benchmarks.
Kimi K2.5 significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, Kimi K2.5 ($0.60/1M tokens) is 6.0x more expensive than Laguna XS 2.1 ($0.10/1M tokens).
For output processing, Kimi K2.5 ($3.00/1M tokens) is 15.0x more expensive than Laguna XS 2.1 ($0.20/1M tokens).
In conclusion, Kimi K2.5 is more expensive than Laguna XS 2.1.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Kimi K2.5 has 967.0B more parameters than Laguna XS 2.1, making it 2930.3% larger.
Context Window
Maximum input and output token capacity
Laguna XS 2.1 accepts 262,144 input tokens compared to Kimi K2.5's 262,100 tokens. Only Kimi K2.5 specifies output context (262,100 tokens).
Input capabilities
Documented input modalities across available providers
Kimi K2.5 supports multimodal inputs, whereas Laguna XS 2.1 does not.
Kimi K2.5 can handle both text and other forms of data like images, making it suitable for multimodal applications.
Kimi K2.5
Laguna XS 2.1
License
Usage and distribution terms
Kimi K2.5 is licensed under MIT, while Laguna XS 2.1 uses OpenMDW License v1.1.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
OpenMDW License v1.1
Open weights
Release Timeline
When each model was launched
Kimi K2.5 was released on 2026-01-27, while Laguna XS 2.1 was released on 2026-07-02.
Laguna XS 2.1 is 5 months newer than Kimi K2.5.
Jan 27, 2026
7 months ago
Jul 2, 2026
2 months ago
5mo newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
Kimi K2.5 is available from Fireworks, Moonshot AI. Laguna XS 2.1 is available from Poolside.
Kimi K2.5
Laguna XS 2.1
Outputs Comparison
Judge for yourself.
Run your own prompts against Kimi K2.5 and Laguna XS 2.1 side-by-side, then vote on the output you prefer.
FAQ
Common questions about Kimi K2.5 vs Laguna XS 2.1.