In Development

OpenAI's Garlic Model

Next-generation large language model optimized for coding and reasoning tasks.
Expected to launch as GPT-5.2 or GPT-5.5 in Q1 2026.

Q1 2026
Expected Release
GPT-5.5
Possible Version
Coding & Reasoning
Focus Areas
Training
Status
Overview

What is the Garlic Model?

OpenAI is developing a new large language model codenamed "Garlic" to compete with Google's Gemini 3 and Anthropic's Opus 4.5. The model has shown exceptional performance in internal benchmarks for coding and reasoning tasks.

According to reports from The Information (December 2025), Chief Research Officer Mark Chen shared that Garlic has outperformed competing models in key areas. A notable technical breakthrough is the solution to pretraining challenges, allowing smaller models to be injected with more knowledge while improving efficiency.

Quick Facts

CodenameGarlic
DeveloperOpenAI
Key FigureMark Chen (CRO)
Target CompetitionGemini 3, Opus 4.5
Expected ReleaseQ1 2026
Possible VersionsGPT-5.2 / GPT-5.5
Related ModelShallotpeat
Internal StatusCode Red
Latest Signals

Development Signals

Key indicators and announcements about the Garlic model development.

Strategic

Code Red Declaration

OpenAI has declared 'Code Red' to address competitive pressure from Google and Anthropic.

Benchmark

Performance Claims

Internal tests show Garlic outperforming Gemini 3 and Opus 4.5 in coding and reasoning.

Technical

Pretraining Breakthrough

Novel approach allows smaller models to contain more knowledge with improved efficiency.

Timeline

Release Window

Expected public release in Q1 2026 as either GPT-5.2 or GPT-5.5.

Market

Market Pressure

Competitive response to Google's Gemini surge and rising AI industry competition.

Strategy

Deployment Goals

Focus on ChatGPT competitiveness and core model quality improvements.

Development Timeline

Key Milestones

Track the development progress of the Garlic model.

December 2025

Internal Announcement

Mark Chen shares Garlic's strong benchmark results with OpenAI team.

December 2, 2025

Code Red Initiative

Sam Altman declares Code Red, refocusing company on core model quality.

Q4 2025 - Q1 2026

Training & Testing

Continued pretraining and evaluation against competitors.

Q1 2026

Public Release

Expected launch as GPT-5.2 or GPT-5.5.

Competitive Analysis

Model Comparison

How Garlic compares to other frontier models.

DimensionGarlicGemini 3Claude 4·5GPT-5·1
Coding PerformanceExcellentVery GoodVery GoodGood
Reasoning AbilityExcellentVery GoodExcellentGood
Training EfficiencyHighMediumMediumMedium
Expected ReleaseQ1 2026ReleasedReleasedReleased
Performance

Expected Benchmarks

Projected performance metrics based on internal evaluations.

BenchmarkExpectedActual
SWE-bench>70%TBD
MMMU-Pro>80%TBD
Humanity's Last ExamTop TierTBD
HumanEval>95%TBD
MATH>90%TBD
GPQA Diamond>75%TBD

Data based on internal evaluations and industry reports. Official benchmarks pending public release.

Key Technical Features

What makes the Garlic model stand out from the competition.

Advanced Pretraining

Novel approach that injects more knowledge into smaller models while maintaining efficiency.

Superior Coding

Exceptional performance in code generation, debugging, and understanding large codebases.

Enhanced Reasoning

Advanced logical reasoning and problem-solving capabilities for complex tasks.

Cost Efficiency

Trained on smaller datasets while maintaining comparable sophistication to larger models.

Agentic Tasks

Designed to handle autonomous agent workflows and multi-step operations.

Safety First

Developed with built-in safety measures and responsible AI principles.

Applications

Practical Use Cases

How different user groups can leverage the Garlic model.

Developers & Engineers

  • Automated code generation and completion
  • Intelligent debugging and error resolution
  • Test case generation and coverage analysis
  • Documentation generation from code
  • Code review and optimization suggestions

Enterprise Teams

  • Cost-optimized AI reasoning at scale
  • Complex document processing and analysis
  • Automated workflow orchestration
  • Data extraction and transformation
  • Business process automation

Research & Data

  • Advanced mathematical reasoning
  • SQL query generation and optimization
  • Scientific literature analysis
  • Hypothesis generation and testing
  • Data synthesis and reporting
Preparation

Adoption Readiness Checklist

Prepare your organization for the Q1 2026 release.

Define Evaluation Framework

Establish benchmarks and success metrics for your specific use cases.

Budget Planning

Allocate resources for API costs and integration development.

Set Latency Targets

Define acceptable response times for your applications.

Review Security Requirements

Ensure compliance with data handling and privacy policies.

Prepare Integration Architecture

Design API integration patterns and fallback strategies.

Train Development Team

Upskill team on prompt engineering and model capabilities.

Frequently Asked Questions

Common questions about OpenAI's Garlic model.







Have more questions? Follow the latest updates from OpenAI.

References

Sources & References

Verified sources for the information presented on this page.