Kimi K2.6 vs LongCat-2.5
LongCat-2.5 leads the LLM Stats Score 50.0 to 43.2. LongCat-2.5 is 2.7x cheaper per token.
Moonshot AI · Meituan · Updated for 2026
Which is better?
LongCat-2.5 leads the overall LLM Stats Score 50.0 to 43.2, ranking #20 overall.
In the 4 individual benchmarks reported for both models, LongCat-2.5 wins 3; this is a narrower head-to-head signal than the composite indexes.
On price, LongCat-2.5 is roughly 2.7x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
LongCat-2.5 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 Kimi K2.6
- you need open weights you can self-host or fine-tune
Choose LongCat-2.5
- overall performance matters — it scores 50.0 and ranks #20 on LLM Stats
- your work emphasizes reasoning and agents — it leads those capability indexes
- you value its reported benchmark strengths — it wins 3 of 4 exact shared results
- cost matters — it's about 2.7x cheaper per token
- you process long inputs — it offers a 1,048,576 token context window
- you want the most recent training data — it shipped Nov 2026
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
28 reported for Kimi K2.6 · 23 for LongCat-2.5
Kimi K2.6 outperforms in 1 benchmarks (Claw-Eval), while LongCat-2.5 is better at 3 benchmarks (BrowseComp, CharXiv-R, MathVision).
LongCat-2.5 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, Kimi K2.6 ($0.75/1M tokens) is 2.5x more expensive than LongCat-2.5 ($0.30/1M tokens).
For output processing, Kimi K2.6 ($3.50/1M tokens) is 2.9x more expensive than LongCat-2.5 ($1.20/1M tokens).
In conclusion, Kimi K2.6 is more expensive than LongCat-2.5.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
LongCat-2.5 has 600.0B more parameters than Kimi K2.6, making it 60.0% larger.
Context Window
Maximum input and output token capacity
LongCat-2.5 accepts 1,048,576 input tokens compared to Kimi K2.6's 262,144 tokens. Both models can generate responses up to 131,072 tokens.
Input capabilities
Documented input modalities across available providers
Both Kimi K2.6 and LongCat-2.5 support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
Kimi K2.6
LongCat-2.5
Release Timeline
When each model was launched
Kimi K2.6 was released on 2026-04-20, while LongCat-2.5 was released on 2026-11-01.
LongCat-2.5 is 7 months newer than Kimi K2.6.
Apr 20, 2026
6 months ago
Nov 1, 2026
4 days ago
6mo 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 K2.6 is available from DeepInfra, Fireworks, Moonshot AI, Novita, Together. LongCat-2.5 is available from Meituan.
Kimi K2.6
LongCat-2.5
Outputs Comparison
Judge for yourself.
Run your own prompts against Kimi K2.6 and LongCat-2.5 side-by-side, then vote on the output you prefer.
FAQ
Common questions about Kimi K2.6 vs LongCat-2.5.