OpenAI
OpenAI's coding agent — debugging, reviewing, deploying, not just writing the function.
400K tokens
कॉन्टेक्स्ट
128,000 tokens
अधिकतम आउटपुट
मध्यम
गति
Whole tasks across the lifecycle, not one snippet.
Reads real failures and works towards the cause.
Reviews a change against the intent behind it.
Takes images, so a broken UI can go in directly.
Tuned to this model — click any line to copy.
GPT-5.3 Codex is OpenAI's coding specialist, announced on 5 February 2026. It combines the coding strength of the Codex line with the general reasoning and professional knowledge of the wider GPT-5 series, and OpenAI's framing of it is deliberately broad: Codex moves from an agent that writes and reviews code to an agent that can do most of what a developer does on a computer.
That shows up in what it is tuned for. Debugging, deploying, monitoring, writing specs, editing copy, tests and metrics are all in scope, not just producing a function on request. It sets high marks on the benchmarks that measure real repository work rather than puzzle-solving — SWE-Bench Pro and Terminal-Bench in particular — and OpenAI reports it runs roughly 25% faster than GPT-5.2 Codex, which matters more than it sounds when a model is doing dozens of steps in a row.
It exposes adjustable reasoning effort, so the same model can answer quickly or think hard depending on what the task deserves, and it takes images as input, so a screenshot of a broken build or an unreadable chart can go straight into the thread. The context window runs to about 400K tokens with up to 128K tokens of output, enough to hold a large slice of a repository plus a long agent transcript.
On NinjaChat it is included in every plan. Pick it from the model list when the work is software, and switch to a general model when it is not.
शून्य से पहले नतीजे तक, एक मिनट से भी कम में।
01
Create a NinjaChat account and choose a plan
02
Open chat and pick GPT-5.3 Codex from the model list
03
Give it the repository context, the failure and the goal
04
Ask for a plan first on anything that spans files
ईमानदार तुलना — जहाँ {model} जीतता है, और जहाँ नहीं।
OpenAI's reasoning-effort control and wider tooling
Kimi K2.7 Code is open-weights and cheaper per token
Tuned specifically for software and agent runs
Terra is the better all-round generalist
Stronger on real repository benchmarks
GLM 5.2 costs less for everyday coding
हर NinjaChat plan में 50+ models, एक पूरा image studio, और वीडियो जनरेशन शामिल है।



एक ही सब्सक्रिप्शन में NinjaChat के सभी मॉडल शामिल हैं, GPT-5.3 Codex भी।