GLM 5.3 vs Kimi K3

As of October 21, 2026, Kimi K3 costs 114% more per input token than GLM 5.3 ($3.00 vs $1.40 per 1M) and has a 1,048,576-token context window versus 1,000,000.

Prices from LiteLLM's price fileChecked October 21, 2026

GLM 5.3 vs Kimi K3 side by side

Headline prices in US dollars per 1M tokens: each model's own lab where it sells it, otherwise its cheapest provider. Source: LiteLLM model price file, as of October 21, 2026.
	GLM 5.3	Kimi K3
Input, per 1M tokens	$1.40	$3.00
Output, per 1M tokens	$4.40	$15.00
Cache read, per 1M tokens	$0.26	$0.30
Cache write, per 1M tokens	$0	–
Context window	1,000,000 tokens	1,048,576 tokens
Max output	128,000 tokens	1,048,576 tokens
Image input	Yes	Yes
Tool calling	Yes	Yes
Structured output (JSON)	Yes	Yes
Prompt caching	Yes	Yes
Reasoning	Yes	Yes
Providers on LiteLLM	17	15
Price shown is from	Z.ai	Moonshot AI
Added to LiteLLM	August 27, 2026	August 16, 2026

Cheapest provider for each

GLM 5.3: Sail at $0.98 input and $3.08 output per 1M tokens (sail/zai-org/GLM-5.3)
Kimi K3: Sail at $2.50 input and $12.50 output per 1M tokens (sail/moonshotai/Kimi-K3)

Benchmark scores

From the Epoch AI Benchmarking Hub (CC BY 4.0), data as of August 28, 2026. Some results were run by Epoch and others collected by Epoch from each benchmark's own leaderboard, linked in the first column. Each model's best reported reasoning setting is shown in brackets. Higher is better. Only benchmarks with a score for both models are shown.
Benchmark	GLM 5.3	Kimi K3
Coding and agents
FrontierCode	40.1% (max)	44.2%
FrontierSWE	30.2% (max)	25.9% (max)
APEX-Agents	56.6%	47.8%
Reasoning and knowledge
GPQA Diamond	90.9% (max)	93.1% (max)
SimpleQA Verified	41.0% (max)	50.6% (max)
Math
FrontierMath (tiers 1-3)	68.8% (max)	72.2% (max)
FrontierMath (tier 4)	29.3% (max)	39.0% (max)
OTIS Mock AIME 2024-2025	91.1% (max)	97.2% (max)

When to pick which

Pick GLM 5.3 for

Costs 53% less per input token: $1.40 vs $3.00 per 1M.

Pick Kimi K3 for

Returns up to 1,048,576 tokens per response, vs 128,000.

From differences in the data above only; where the data is equal, no reason is given.

Call GLM 5.3 or Kimi K3 with LiteLLM

Both use the OpenAI format through LiteLLM, so switching is a model name change. Set each provider's API key in the environment first.

Python SDK

from litellm import completion

messages = [{"role": "user", "content": "Hello!"}]

# GLM 5.3
response = completion(model="zai/glm-5.3", messages=messages)

# Kimi K3
response = completion(model="moonshot/kimi-k3", messages=messages)

# GLM 5.3, falling back to Kimi K3 if the call fails
response = completion(model="zai/glm-5.3", messages=messages, fallbacks=["moonshot/kimi-k3"])

FAQ

Which is cheaper, GLM 5.3 or Kimi K3?

GLM 5.3 is cheaper at 3 input tokens per output token: $2.15 per 1M tokens blended ($1.40 input, $4.40 output), versus $6.00 ($3.00 and $15.00) for Kimi K3, as of October 21, 2026.

Which has the larger context window, GLM 5.3 or Kimi K3?

Kimi K3 has the larger context window: 1,048,576 tokens, versus 1,000,000 for GLM 5.3.

Can I switch from GLM 5.3 to Kimi K3 without changing my code?

Yes. Through LiteLLM both use the OpenAI format, so switching means changing the model name from "zai/glm-5.3" to "moonshot/kimi-k3", or pointing a LiteLLM gateway model alias at the other model. You can also use one as a fallback for the other.