GLM-5.3 vs Kimi K3
GLM-5.3 and Kimi K3 are closely matched at 53.6 and 53.8 on the LLM Stats Score. GLM-5.3 is 2.8x cheaper per token.
Zhipu AI · Moonshot AI · Updated for 2026
Which is better?
GLM-5.3 and Kimi K3 are closely matched on the overall LLM Stats Score at 53.6 and 53.8.
In the 9 individual benchmarks reported for both models, Kimi K3 wins 5; this is a narrower head-to-head signal than the composite indexes.
On price, GLM-5.3 is roughly 2.8x 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 GLM-5.3
- cost matters — it's about 2.8x cheaper per token
- you want the most recent training data — it shipped Aug 2026
Choose Kimi K3
- you value its reported benchmark strengths — it wins 5 of 9 exact shared results
- 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
17 reported for GLM-5.3 · 31 for Kimi K3
GLM-5.3 outperforms in 4 benchmarks (AutomationBench, Humanity's Last Exam, PostTrainBench, SWE-Marathon), while Kimi K3 is better at 5 benchmarks (DeepSWE 1.1, FrontierSWE, Program Bench, Terminal-Bench 2.1, Toolathlon).
Kimi K3 has a slight edge in benchmark performance.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, GLM-5.3 ($1.40/1M tokens) is 2.1x cheaper than Kimi K3 ($3.00/1M tokens).
For output processing, GLM-5.3 ($4.40/1M tokens) is 3.4x cheaper than Kimi K3 ($15.00/1M tokens).
In conclusion, Kimi K3 is more expensive than GLM-5.3.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Kimi K3 has 2047.0B more parameters than GLM-5.3, making it 271.8% larger.
Context Window
Maximum input and output token capacity
Kimi K3 accepts 1,048,576 input tokens compared to GLM-5.3's 1,000,000 tokens. Kimi K3 can generate longer responses up to 1,048,576 tokens, while GLM-5.3 is limited to 131,072 tokens.
Input capabilities
Documented input modalities across available providers
Kimi K3 supports multimodal inputs, whereas GLM-5.3 does not.
Kimi K3 can handle both text and other forms of data like images, making it suitable for multimodal applications.
GLM-5.3
Kimi K3
License
Usage and distribution terms
GLM-5.3 is licensed under GLM-5.3 License, while Kimi K3 uses Kimi K3 License.
License differences may affect how you can use these models in commercial or open-source projects.
GLM-5.3 License
Open weights
Kimi K3 License
Open weights
Release Timeline
When each model was launched
GLM-5.3 was released on 2026-08-14, while Kimi K3 was released on 2026-07-16.
GLM-5.3 is 1 month newer than Kimi K3.
Aug 14, 2026
3 weeks ago
4w newerJul 16, 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
GLM-5.3 is available from FriendliAI, Novita, ZAI. Kimi K3 is available from Fireworks, Moonshot AI, Novita, Together.
GLM-5.3
Kimi K3
Outputs Comparison
Judge for yourself.
Run your own prompts against GLM-5.3 and Kimi K3 side-by-side, then vote on the output you prefer.
FAQ
Common questions about GLM-5.3 vs Kimi K3.