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고급 코딩 기능 128K의 긴 컨텍스트 파악 OpenAI의 최신 개발

이 모델의 약점은 무엇인가요?

비공개 폐쇄 라이선스 리서치 프리뷰 상태로 인한 불안정성 소스 코드 비공개

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복잡한 코드 자동 생성 대규모 프로젝트 분석 효율적인 디버깅 작업

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OpenAI독점

GPT-5.3-Codex-Spark (Research Preview)

Name: GPT-5.3-Codex-Spark (Research Preview)
Author: OpenAI

GPT-5.3-Codex-Spark (리서치 프리뷰)는 OpenAI에서 개발한 코딩 특화 AI 모델입니다. 128K 컨텍스트 윈도우를 탑재하고 있으며, 고급 프로그래밍 지원을 목표로 합니다.

파라미터

Undisclosed

컨텍스트

128K

라이선스

Proprietary

출시일

2026-02-12

API 가격

이 모델의 API 가격 정보는 현재 공개되지 않았습니다

강점

・고급 코딩 기능
・128K의 긴 컨텍스트 파악
・OpenAI의 최신 개발

약점

・비공개 폐쇄 라이선스
・리서치 프리뷰 상태로 인한 불안정성
・소스 코드 비공개

활용 사례

・복잡한 코드 자동 생성
・대규모 프로젝트 분석
・효율적인 디버깅 작업

심층 분석

Release Date

February 12, 2026

Context Window

128K tokens

Speed

1000+ tokens/second

Speed Improvement

15x faster than GPT-5.3 Codex flagship

Hardware

Cerebras WSE-3 (Wafer Scale Engine 3)

Terminal-Bench 2.0

77.3%

vs GPT-5.2-Codex 64%

Pricing

No change from standard GPT-5.3-Codex

Availability

ChatGPT Pro subscribers, API coming soon

강점

・Blazing fast at 1000+ tokens per second — 15x faster than flagship GPT-5.3 Codex
・First OpenAI model running on Cerebras WSE-3 hardware with 4 trillion transistors
・Terminal-Bench 2.0 score of 77.3% — higher than GPT-5.2-Codex (64%)
・Enables real-time steering — developers can interrupt and redirect mid-generation
・80% reduction in round-trip time via persistent WebSocket connections

약점

・Scores lower on SWE-Bench Pro and Terminal-Bench 2.0 than flagship GPT-5.3 Codex
・May struggle with complex, multi-file architecture changes
・Does NOT meet 'High capability' cybersecurity threshold under OpenAI's Preparedness Framework
・Not suitable for sensitive security logic or autonomous authentication tasks
・Research preview — limited availability (ChatGPT Pro only, API 'coming soon')

경쟁사 비교

Model	Arena	SWE	GPQA	Price
GPT-5.3 Codex (flagship)	N/A	~80%	~90%	$1.75/$14 per 1M tokens
GPT-5.2-Codex	N/A	~75%	~88%	$1.75/$14 per 1M tokens
Claude Sonnet 4.5	~1420	~72%	~89%	$3/$15 per 1M tokens
Cursor (varies)	N/A	Varies	N/A	$20/month subscription

개요

GPT-5.3-Codex-Spark is a research preview released February 12, 2026, delivering unprecedented coding speed at 1000+ tokens per second — 15x faster than the flagship GPT-5.3 Codex. It is the first OpenAI model to run on Cerebras WSE-3 hardware and achieves Terminal-Bench 2.0 score of 77.3%. It trades reasoning depth for speed, enabling real-time collaborative coding workflows.

벤치마크 및 성능

GPT-5.3-Codex-Spark achieves Terminal-Bench 2.0 accuracy of 77.3% (vs GPT-5.2-Codex's 64%) while running 15x faster at 1000+ tokens/second. It consumes approximately half the tokens of earlier models for certain output types. The model surpasses reasoning capabilities of both GPT-5.2-Codex and standard GPT-5.2. However, it scores lower than the flagship GPT-5.3 Codex on SWE-Bench Pro and Terminal-Bench 2.0. Software optimizations include 80% RTT reduction, 50% TTFT improvement, and 30% per-token overhead reduction via persistent WebSocket connections.

상세 비교

GPT-5.3-Codex-Spark is 15x faster than the flagship GPT-5.3 Codex but trades some reasoning depth for speed. It outperforms GPT-5.2-Codex on Terminal-Bench 2.0 (77.3% vs 64%) while being dramatically faster. It does not meet the 'High capability' cybersecurity threshold that the flagship achieves. Compared to Claude Sonnet 4.5, it offers much higher throughput but may trail on complex multi-step reasoning. The Cerebras hardware advantage eliminates inter-GPU bottlenecks.

커뮤니티 평가

The developer community has been highly enthusiastic about the 1000+ tok/s speed, describing it as shifting the workflow from batch-processing to live pair-programming. Early users praise the real-time steering capability (interrupt and redirect mid-generation). Some concern exists about the research preview status and limited availability. The self-development aspect (Spark helped create itself) has generated significant discussion about AI development acceleration.

활용 사례

Best for: rapid prototyping and iterative coding, real-time collaborative coding sessions, fast code generation and scaffolding, debugging with immediate feedback loops, quick code reviews, and interactive development workflows. Also good for: PRD writing, copy editing, user research, test generation, and metrics analysis. NOT suitable for: complex multi-file architecture changes, sensitive security code, autonomous authentication tasks, or tasks requiring maximum reasoning depth. Use GPT-5.3 Codex flagship for deep reasoning work.