GLM-5.3 vs Kimi K2-Thinking-0905
GLM-5.3 significantly outperforms across most benchmarks. Kimi K2-Thinking-0905 is 2.5x cheaper per token.
Zhipu AI · Moonshot AI · Updated for 2026
Which is better?
GLM-5.3 outperforms in 1 benchmarks (Humanity's Last Exam), while Kimi K2-Thinking-0905 is better at 0 benchmarks. GLM-5.3 significantly outperforms across most benchmarks.
On price, Kimi K2-Thinking-0905 is roughly 2.5x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
GLM-5.3 also accepts a larger context window (1,000,000 input tokens), making it the stronger choice for long documents and large codebases.
Based on current benchmark, pricing, and model metadata for 2026.
Choose GLM-5.3
- you want the strongest raw capability — it leads on 1 of 1 shared benchmarks
- you process long inputs — it offers a 1,000,000 token context window
- you want the most recent training data — it shipped Aug 2026
Choose Kimi K2-Thinking-0905
- cost matters — it's about 2.5x cheaper per token
- you need open weights you can self-host or fine-tune
At a glance
The differences that matter most.
Performance Benchmarks
Comparative analysis across standard metrics
GLM-5.3 outperforms in 1 benchmarks (Humanity's Last Exam), while Kimi K2-Thinking-0905 is better at 0 benchmarks.
GLM-5.3 significantly outperforms across most benchmarks.
Arena Performance
Playground indexes and blind preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, GLM-5.3 ($1.40/1M tokens) is 3.0x more expensive than Kimi K2-Thinking-0905 ($0.47/1M tokens).
For output processing, GLM-5.3 ($4.40/1M tokens) is 2.2x more expensive than Kimi K2-Thinking-0905 ($2.00/1M tokens).
In conclusion, GLM-5.3 is more expensive than Kimi K2-Thinking-0905.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Kimi K2-Thinking-0905 has 247.0B more parameters than GLM-5.3, making it 32.8% larger.
Context Window
Maximum input and output token capacity
GLM-5.3 accepts 1,000,000 input tokens compared to Kimi K2-Thinking-0905's 262,144 tokens. Kimi K2-Thinking-0905 can generate longer responses up to 262,144 tokens, while GLM-5.3 is limited to 128,000 tokens.
Release Timeline
When each model was launched
GLM-5.3 was released on 2026-08-14, while Kimi K2-Thinking-0905 was released on 2025-09-05.
GLM-5.3 is 11 months newer than Kimi K2-Thinking-0905.
Aug 14, 2026
1 weeks ago
11mo newerSep 5, 2025
11 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 ZAI. Kimi K2-Thinking-0905 is available from DeepInfra, Novita, Fireworks.
GLM-5.3
Kimi K2-Thinking-0905
Outputs Comparison
Judge for yourself.
Run your own prompts against GLM-5.3 and Kimi K2-Thinking-0905 side-by-side, then vote on the output you prefer.
FAQ
Common questions about GLM-5.3 vs Kimi K2-Thinking-0905.