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OpenAI

Chat with GPT-5.3 Codex online

OpenAI's coding agent — debugging, reviewing, deploying, not just writing the function.

GPT-5.3 Codex आज़माएं Plans देखें
790,000+ उपयोगकर्ताओं का भरोसा

400K tokens

कॉन्टेक्स्ट

128,000 tokens

अधिकतम आउटपुट

मध्यम

गति

आप इसे किस काम के लिए इस्तेमाल करेंगे

Agentic development

Whole tasks across the lifecycle, not one snippet.

Debugging

Reads real failures and works towards the cause.

Code review

Reviews a change against the intent behind it.

Screenshot to fix

Takes images, so a broken UI can go in directly.

Prompts to steal

Tuned to this model — click any line to copy.

GPT-5.3 Codex के बारे में

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.

GPT-5.3 Codex का उपयोग कैसे करें

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

बेहतर नतीजों के लिए टिप्स

  • Paste the real error output rather than describing it
  • Say explicitly which files are in scope
  • Attach a screenshot when the bug is visual
  • Switch to a general GPT-5 model for non-coding work

GPT-5.3 Codex बनाम alternatives

ईमानदार तुलना — जहाँ {model} जीतता है, और जहाँ नहीं।

Kimi K2.7 Code से तुलना

Model देखें

+OpenAI's reasoning-effort control and wider tooling

–Kimi K2.7 Code is open-weights and cheaper per token

GPT-5.6 Terra से तुलना

+Tuned specifically for software and agent runs

–Terra is the better all-round generalist

GLM 5.2 से तुलना

Model देखें

+Stronger on real repository benchmarks

–GLM 5.2 costs less for everyday coding

अक्सर पूछे जाने वाले सवाल

Chat से आगे — images और video

हर NinjaChat plan में 50+ models, एक पूरा image studio, और वीडियो जनरेशन शामिल है।

A real FLUX Pro Ultra outputA real Google Imagen 4 outputA real Seedream output
सभी मॉडल देखें →

GPT-5.3 Codex, और 50 अन्य।

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

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और models explore करें

Kimi K2.7 Code

Moonshot's coding specialist for long agent runs

→

GPT 5.6 Terra

OpenAI's newest everyday model balancing intelligence and speed

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GLM 5.2

कोडिंग, एजेंट्स और सिस्टम्स वर्क के लिए Z.ai का फ्लैगशिप

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