GLM-5 vs GPT-5.3 Codex
GLM-5 and GPT-5.3 Codex are closely matched at 37.1 and 36.5 on the LLM Stats Score. GLM-5 is 3.1x cheaper per token.
Zhipu AI · OpenAI · Updated for 2026
Which is better?
GLM-5 and GPT-5.3 Codex are closely matched on the overall LLM Stats Score at 37.1 and 36.5.
In the 1 individual benchmarks reported for both models, GPT-5.3 Codex wins 1; this is a narrower head-to-head signal than the composite indexes.
On price, GLM-5 is roughly 3.1x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
GPT-5.3 Codex also accepts a larger context window (400,000 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
- cost matters — it's about 3.1x cheaper per token
- you want the most recent training data — it shipped Feb 2026
- you need open weights you can self-host or fine-tune
Choose GPT-5.3 Codex
- you value its reported benchmark strengths — it wins 1 of 1 exact shared results
- you process long inputs — it offers a 400,000 token context window
At a glance
The differences that matter most.
Individual benchmarks
5 reported for GLM-5 · 6 for GPT-5.3 Codex
GLM-5 outperforms in 0 benchmarks, while GPT-5.3 Codex is better at 1 benchmark (Terminal-Bench 2.0).
GPT-5.3 Codex 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, GLM-5 ($1.00/1M tokens) is 1.8x cheaper than GPT-5.3 Codex ($1.75/1M tokens).
For output processing, GLM-5 ($3.20/1M tokens) is 4.4x cheaper than GPT-5.3 Codex ($14.00/1M tokens).
In conclusion, GPT-5.3 Codex is more expensive than GLM-5.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
GPT-5.3 Codex accepts 400,000 input tokens compared to GLM-5's 200,000 tokens. Both models can generate responses up to 128,000 tokens.
Input capabilities
Documented input modalities across available providers
GPT-5.3 Codex supports multimodal inputs, whereas GLM-5 does not.
GPT-5.3 Codex can handle both text and other forms of data like images, making it suitable for multimodal applications.
GLM-5
GPT-5.3 Codex
License
Usage and distribution terms
GLM-5 is licensed under MIT, while GPT-5.3 Codex uses a proprietary license.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Proprietary
Closed source
Release Timeline
When each model was launched
GLM-5 was released on 2026-02-11, while GPT-5.3 Codex was released on 2026-02-05.
GLM-5 is 0 month newer than GPT-5.3 Codex.
Feb 11, 2026
7 months ago
6d newerFeb 5, 2026
7 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 is available from FriendliAI, ZAI. GPT-5.3 Codex is available from OpenAI.
GLM-5
GPT-5.3 Codex
Outputs Comparison
Judge for yourself.
Run your own prompts against GLM-5 and GPT-5.3 Codex side-by-side, then vote on the output you prefer.
FAQ
Common questions about GLM-5 vs GPT-5.3 Codex.