Hello, I'm Ryuta Hamamoto from TIMEWELL Inc.
On December 11, 2025, OpenAI released GPT-5.2, setting a new milestone for the AI industry. Developed under the codename "Garlic," this model comes in three variants — Instant, Thinking, and Pro — and is the first to exceed 90% on the ARC-AGI-1 benchmark.
Just four months had passed since the GPT-5 launch in August of that year. Amid intensifying competition from Google's Gemini 3 Pro (released November 18, 2025) and Anthropic's Claude Opus 4.5 (released November 2025), OpenAI reaffirmed its position as one of the "Big Three" frontier model providers.
This article breaks down each GPT-5.2 variant's characteristics, official benchmarks, API pricing, competitive comparisons, and guidance for enterprise use.
GPT-5.2 at a Glance
| Item | Details |
|---|---|
| Release Date | December 11, 2025 |
| Codename | Garlic |
| Model Lineup | Instant, Thinking, Pro |
| ARC-AGI-1 Score | 90%+ (industry first) |
| Context Length | 400,000 tokens |
| Max Output Tokens | 128,000 tokens |
| Knowledge Cutoff | August 31, 2025 |
| API Price (Input) | $1.75 / 1M tokens |
| API Price (Output) | $14.00 / 1M tokens |
The Evolution from GPT-5 to GPT-5.2
GPT-5 Launch (August 7, 2025)
On August 7, 2025, OpenAI officially released GPT-5 — its first major version upgrade in roughly eighteen months after GPT-4o. Key results included:
- AIME 2025: 94.6% (no tools)
- SWE-bench Verified: 74.9%
- Hallucination Reduction: ~45% fewer factual errors vs. GPT-4o with web search enabled
- Unified Architecture: A real-time router dynamically switches between a lightweight response mode and a deep-reasoning mode
GPT-5's biggest innovation was this "unified system" design. The router automatically selects the appropriate mode, so users receive the most relevant response without needing to choose a model themselves.
Competition with Gemini 3 Pro
On November 18, 2025, Google announced Gemini 3 Pro, which recorded 1,501 Elo on the LMArena leaderboard and achieved top scores on 19 out of 20 benchmarks. OpenAI responded by releasing GPT-5.2 on December 11.
GPT-5.2's Three-Model Lineup: A Detailed Breakdown
Model Comparison
| Item | GPT-5.2 Instant | GPT-5.2 Thinking | GPT-5.2 Pro |
|---|---|---|---|
| Characteristics | Fast, low-cost | Reasoning-focused | Highest performance |
| Primary Use Cases | Everyday tasks, chat | Complex analysis, problem-solving | Research, advanced specialist tasks |
| Response Speed | Fastest | Moderate | Takes time, highest quality |
| Strengths | Information retrieval, translation, technical docs | Spreadsheets, financial modeling, coding | Reduced critical errors in complex domains |
| Access Plan | Free (limited) and above | Plus and above | Pro ($200/mo) only |
GPT-5.2 Instant
Optimized for everyday use. According to OpenAI's official release, clear improvements were observed in the following areas:
- Improved accuracy for information retrieval questions
- Better quality how-to guides and walkthroughs
- More accurate technical document generation
- Improved translation quality
API pricing is $1.75/1M tokens for input and $14.00/1M tokens for output — roughly 40% higher than GPT-5 ($1.25/$10.00) — but the performance gains make it cost-effective.
GPT-5.2 Thinking
The reasoning-focused model, a successor to the older o1/o3 series. It employs a Chain-of-Thought approach, generating internal "reasoning tokens" to think through problems step by step.
Areas where OpenAI confirmed notable improvements in early testing:
- Spreadsheet formatting and financial modeling
- Coding tasks
- Summarization of long documents
- Planning and decision support
Note that reasoning tokens in the Thinking model are billed as output tokens, so costs increase for complex queries.
GPT-5.2 Pro
The highest-performing model, available exclusively on the ChatGPT Pro plan ($200/month). It achieves top scores across all benchmarks, with a significant reduction in "critical errors" in complex domains. Ideal for fields requiring high accuracy such as research, legal work, and healthcare.
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Benchmark Results — Industry-First Records
90%+ on ARC-AGI-1
GPT-5.2 Pro became the first model to exceed 90% on the ARC-AGI-1 (Verified) benchmark, which measures general reasoning ability.
| Model | ARC-AGI-1 Score |
|---|---|
| GPT-4o | 5% |
| o1 | ~25% |
| o3-preview | 87% |
| GPT-5.2 Pro | 90%+ |
| Human Baseline | 85% |
Notable results also emerged on the more challenging ARC-AGI-2 benchmark:
| Model | ARC-AGI-2 Score |
|---|---|
| Gemini 3 Pro | 31.1% |
| Claude Opus 4.5 | 37.6% |
| GPT-5.2 Thinking | 52.9% |
| GPT-5.2 Pro | 54.2% |
Comprehensive Benchmark Comparison
| Benchmark | GPT-5.2 Pro | Gemini 3 Pro | Claude Opus 4.5 |
|---|---|---|---|
| ARC-AGI-2 | 54.2% | 31.1% | 37.6% |
| GPQA Diamond | 92%+ | 91.9% | -- |
| SWE-bench Verified | Top tier | 76.2% | -- |
| Context Length | 400K | 1M | 200K |
| Output Tokens | 128K | 64K | -- |
Each model has distinct strengths. In 2026, "multi-model routing" — using the best model for each task — is becoming the dominant operational approach.
Technical Specifications
400K Context Window
GPT-5.2's context length is 400,000 tokens — equivalent to roughly 300,000 words, or five to six typical books.
| Model | Context Length |
|---|---|
| GPT-4 | 8K / 32K |
| GPT-4 Turbo | 128K |
| GPT-5 | 256K |
| GPT-5.2 | 400K |
| Gemini 3 Pro | 1M |
While it falls short of Gemini 3 Pro's 1M tokens, 400K is more than sufficient for enterprise use — processing entire codebases, referencing multiple API specifications simultaneously, or analyzing large volumes of legal documents.
128K Output Tokens
Up to 128,000 output tokens, enabling one-shot generation of lengthy reports, detailed technical documentation, and large-scale code.
GPT-5.2-Codex — Agentic Coding
Released January 14, 2026
Following the main GPT-5.2 release, the coding-specialized GPT-5.2-Codex launched on January 14, 2026.
| Item | GPT-5.2-Codex |
|---|---|
| Release Date | January 14, 2026 |
| Characteristics | Agentic autonomous coding |
| Context Compression | Supported (for long sessions) |
| Security | Enhanced cybersecurity features |
How It Differs from Traditional Code Completion
Traditional approach: User writes code → AI suggests the next line → User approves
GPT-5.2-Codex agentic approach:
- User describes requirements
- Codex analyzes the entire codebase
- Automatically identifies and modifies necessary files
- Runs tests to verify
- Submits the completed code
Developers can now issue high-level instructions and delegate the implementation details to AI.
Pricing
ChatGPT Plans
| Plan | Monthly Price | GPT-5.2 Access |
|---|---|---|
| Free | Free | Instant (limited) |
| Plus | $20 | Instant + Thinking (limited) |
| Pro | $200 | All models, unlimited |
| Team | Custom | Team settings |
| Enterprise | Custom | Enterprise settings |
API Pricing
| Model | Input | Output |
|---|---|---|
| GPT-5.2 | $1.75 / 1M tokens | $14.00 / 1M tokens |
| GPT-5.2 (Cached Input) | $0.175 / 1M tokens | -- |
| Batch API | $0.875 / 1M tokens | $7.00 / 1M tokens |
Using the Batch API provides a 50% discount, significantly reducing costs for workloads that don't require real-time responses.
Competitive Comparison — The 2026 Frontier Model Era
As of February 2026, the AI industry operates in a GPT-5.2, Gemini 3 Pro, and Claude Opus 4.6 three-way landscape.
| Item | GPT-5.2 Pro | Gemini 3 Pro | Claude Opus 4.6 |
|---|---|---|---|
| Release Date | December 2025 | November 2025 | February 2026 |
| ARC-AGI-2 | 54.2% | 31.1% | -- |
| Context | 400K | 1M | 1M |
| Math (MathArena Apex) | -- | 23.4% | -- |
| Multimodal | Strong | Best-in-class (MMMU-Pro 81%) | -- |
| Coding | GPT-5.2-Codex | SWE-bench 76.2% | Multi-agent teams |
| Strengths | Reasoning, math | Multimodal, cost efficiency | Agents, coding |
Each model has clear strengths, and enterprises are encouraged to use the right tool for each task.
ZEROCK: Putting GPT-5.2 to Work in the Enterprise
Deploying cutting-edge AI models like GPT-5.2 in a corporate environment requires a solid foundation of security and governance.
ZEROCK, provided by TIMEWELL Inc., is an enterprise-grade AI platform built for exactly this purpose.
- GraphRAG: Structures internal knowledge so AI can reference it accurately
- AWS Domestic Servers: Data stays within Japan to meet security requirements
- Multi-Model Support: Switch between GPT-5.2, Claude, Gemini, and others based on the task
- Prompt Library: Share business-optimized prompts across the organization
- Knowledge Control: Leverage AI while preventing leakage of sensitive information
For organizations that want to use GPT-5.2 as an organizational asset rather than just a personal tool, a platform like ZEROCK is the key.
Summary
GPT-5.2 is OpenAI's new benchmark for AI in 2026.
- Released December 11, 2025 — advanced to compete with Gemini 3 Pro and Claude Opus 4.5
- Three-model lineup (Instant, Thinking, Pro) optimized for different use cases
- Industry-first 90%+ on ARC-AGI-1, and a commanding 54.2% on ARC-AGI-2 — well ahead of competitors
- 400K context, 128K output for large-scale document processing
- GPT-5.2-Codex (January 14, 2026) marks the arrival of fully agentic coding
- API pricing at $1.75 input / $14.00 output per 1M tokens; 50% discount via Batch API
- 2026 is the multi-model era — mixing GPT-5.2, Gemini 3 Pro, and Claude Opus 4.6 is becoming standard
With GPT-5.2, AI is evolving from a "tool" into a true "partner." For enterprises, the key question isn't which model to choose — it's how to embed AI into your operations. That strategic design is what will define competitive advantage in 2026.
References
- Introducing GPT-5.2 | OpenAI
- Introducing GPT-5.2-Codex | OpenAI
- Introducing GPT-5 | OpenAI
- GPT-5.2 Benchmarks (Explained) | Vellum
- GPT-5.2 & ARC-AGI-2: A Benchmark Analysis | IntuitionLabs
- Gemini 3: Introducing the latest Gemini AI model | Google Blog
- OpenAI API Pricing
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