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Model comparison
GLM-5.3 vs Kimi K3
Compare GLM-5.3 and Kimi K3 using the same provider-sourced text & reasoning rubric. No mystery score and no invented benchmark ranking.
Facts checked September 4, 2026
Estimate your cost
Set your usage. Your estimate updates as you type.
Example: 6,000 input tokens for 10 pages, plus a 500-token summary. Page lengths vary; adjust the numbers below.
One run sends your input to the model once and receives an answer. Tokens are pieces of text: input is what you send, output is the answer you receive.
Advanced options
How this estimate works
Estimates exclude taxes, tools, cache storage/writes, free allowances and custom discounts. Image estimates cover output only, not prompt or reference-image charges. Quality modes differ by model. Unlisted settings are not treated as free.
Quick take
GLM-5.3
Z.ai's open-weight long-context reasoning model for coding, tools, and agentic work across self-hosted and managed routes.
Best for
- Long-context coding agents
- Open-weight enterprise experiments
- Teams that want several inference-provider choices
Watch out for
Compare the exact checkpoint and host, not just the model name. Context, maximum output, speed, price, logging, and reasoning controls can all change by route.
Kimi K3
Moonshot AI's frontier multimodal model for million-token coding, reasoning, knowledge work, and tool-driven agents.
Best for
- Large codebase and document work
- Agents that repeatedly reuse a long context
- Multimodal reasoning through a direct or gateway API
Watch out for
Moonshot's public terms permit broad service-improvement uses of submitted content. Treat the provider route and enterprise agreement as a core requirement for confidential work.
Compare the published facts
GLM-5.3 vs Kimi K3
Values use each provider's own published units and limits. A blank means the provider did not publish a directly comparable value in the sources reviewed.
| Text & reasoning | GLM-5.3 | Kimi K3 |
|---|---|---|
| Context windowMaximum combined prompt and working context documented by the provider. | Up to 1.31M on OpenRouter; 1M on QwenCloud | 1M tokens |
| Maximum outputProvider-published response limit, where available. | Up to 262,144 tokens on OpenRouter | Not separately published for the direct API |
| Knowledge cutoffLatest reliable knowledge date explicitly published by the model provider. Search and connected tools can retrieve newer information but do not change the model's built-in cutoff. | Not published | Not published |
| Input priceCurrent standard list price per million input tokens unless noted. | From $1.15 / 1M on OpenRouter | $3 / 1M uncached; $0.30 cached |
| Output priceCurrent standard list price per million output tokens unless noted. | From $3.50 / 1M on OpenRouter | $15 / 1M |
| InputsMedia types accepted by the listed model endpoint. | Text | Text, image |
| Tools & agentsSelected native tools and agent-building capabilities, not an exhaustive list. | Tools, structured outputs, controllable reasoning on supported routes | Tools, agent workflows, reasoning levels, dynamic tool loading on supported routes |
How to choose
Compare the job, not the hype.
Start with the job you need to complete, then validate cost, access, and policy details on your exact provider route.
GLM-5.3
Self-hosted weights keep prompts inside infrastructure you control. QwenCloud says it does not retain API inputs or outputs for training; OpenRouter and other providers apply their own route policies.
Kimi K3
Moonshot's API privacy and model-use terms allow submitted content to be stored and used to provide, maintain, develop, and improve the service. Obtain appropriate enterprise terms before sending sensitive material.
Frequently asked questions
GLM-5.3 vs Kimi K3 FAQ
What is the main difference between GLM-5.3 and Kimi K3?
GLM-5.3: Z.ai's open-weight long-context reasoning model for coding, tools, and agentic work across self-hosted and managed routes. Kimi K3: Moonshot AI's frontier multimodal model for million-token coding, reasoning, knowledge work, and tool-driven agents.
Should I choose GLM-5.3 or Kimi K3?
Consider GLM-5.3 when your priority is Long-context coding agents. Consider Kimi K3 when your priority is Large codebase and document work. Test both with your own data and provider route before committing.
Is this GLM-5.3 vs Kimi K3 comparison based on Cody benchmarks?
No. This comparison aligns provider-published facts for the Text & reasoning category. It does not claim a universal winner or combine incompatible third-party benchmark scores.