Kimi K2.5 vs Kimi K3
Kimi K3 leads the LLM Stats Score 53.3 to 38.9. Kimi K2.5 is 4.8x cheaper per token.
Moonshot AI · Moonshot AI · Updated for 2026
Which is better?
Kimi K3 leads the overall LLM Stats Score 53.3 to 38.9, ranking #9 overall.
In the 10 individual benchmarks reported for both models, Kimi K3 wins 10; this is a narrower head-to-head signal than the composite indexes.
On price, Kimi K2.5 is roughly 4.8x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Kimi K3 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 K2.5
- cost matters — it's about 4.8x cheaper per token
Choose Kimi K3
- overall performance matters — it scores 53.3 and ranks #9 on LLM Stats
- your work emphasizes reasoning and coding — it leads those capability indexes
- you value its reported benchmark strengths — it wins 10 of 10 exact shared results
- you process long inputs — it offers a 1,048,576 token context window
- you want the most recent training data — it shipped Jul 2026
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
40 reported for Kimi K2.5 · 31 for Kimi K3
Kimi K2.5 outperforms in 0 benchmarks, while Kimi K3 is better at 10 benchmarks (BrowseComp, CharXiv-R, DeepSearchQA, FrontierSWE, GPQA, Humanity's Last Exam, MathVision, MMMU-Pro, WorldVQA, ZEROBench).
Kimi K3 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 4.8x cheaper than Kimi K3 ($2.85/1M tokens).
For output processing, Kimi K2.5 ($3.00/1M tokens) is 4.8x cheaper than Kimi K3 ($14.25/1M tokens).
In conclusion, Kimi K3 is more expensive than Kimi K2.5.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Kimi K3 has 1800.0B more parameters than Kimi K2.5, making it 180.0% larger.
Context Window
Maximum input and output token capacity
Kimi K3 accepts 1,048,576 input tokens compared to Kimi K2.5's 262,100 tokens. Kimi K3 can generate longer responses up to 1,048,576 tokens, while Kimi K2.5 is limited to 262,100 tokens.
Input capabilities
Documented input modalities across available providers
Both Kimi K2.5 and Kimi K3 support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
Kimi K2.5
Kimi K3
License
Usage and distribution terms
Kimi K2.5 is licensed under MIT, while Kimi K3 uses Kimi K3 License.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Kimi K3 License
Open weights
Release Timeline
When each model was launched
Kimi K2.5 was released on 2026-01-27, while Kimi K3 was released on 2026-07-16.
Kimi K3 is 6 months newer than Kimi K2.5.
Jan 27, 2026
7 months ago
Jul 16, 2026
1 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. Kimi K3 is available from DeepInfra, Fireworks, Moonshot AI, Novita, Together.
Kimi K2.5
Kimi K3
Outputs Comparison
Judge for yourself.
Run your own prompts against Kimi K2.5 and Kimi K3 side-by-side, then vote on the output you prefer.
FAQ
Common questions about Kimi K2.5 vs Kimi K3.