Recommendations for selecting foreign top programming models

Core conclusion: Among the three top foreign models, Claude Opus 4.5 remains the leader in code quality, GPT-5.2 is the strongest in mathematical reasoning, and Gemini 3 Pro performs outstandingly in multi-modal and long-context scenarios.

Executive summary

After an in-depth analysis of the current three top foreign AI programming models, we recommend:

Code quality first: using Claude Opus 4.5

Ranked 1st in the world for code quality
Strongest ability in code understanding and reconstruction
Suitable for complex system architecture design
First choice for code review and refactoring scenarios

Mathematical reasoning first: using GPT-5.2

AIME 2025 Ranking No. 1 (1.0 out of 10 points)
Algorithms and complex mathematical problems are the strongest
Suitable for algorithm competitions, scientific calculations, and quantitative trading -Leading in logical reasoning ability

Multimodality and long context: Using Gemini 3 Pro

Supports 2 million token ultra-long context
The strongest multi-modal capabilities (video, audio, pictures)
Suitable for handling large code bases and multimedia content
Best Google ecosystem integration

1. Core comparison of three major models

1.1 Comparison of basic information

Comparative dimensions	Claude Opus 4.5	GPT-5.2	Gemini 3 Pro
Release Time	2025.11.24	2025.12.11	2025.12
Developer	Anthropic (US)	OpenAI (US)	Google (US)
Coding Ability Ranking	1st	Top 3	Top 5
AIME 2025	High score	1st place (1.0 points)	High score
Maximum context	200K tokens	1M tokens	2M tokens
Multi-modal	Pictures, audio	Pictures, audio	Video, audio, pictures
Price ($/million tokens)	$5-25	$1.75-14	$1.25-10
Open Source Status	❌ Closed Source	❌ Closed Source	❌ Closed Source

Data source: LLM Stats, official documents of each model, authoritative benchmark test list

1.2 Core Competence Radar Chart

code generation capabilities
Claude Opus 4.5: ★★★★★ (1st in code quality)
GPT-5.2:       ★★★★★
Gemini 3 Pro:  ★★★★

Mathematical reasoning skills
Claude Opus 4.5: ★★★★
GPT-5.2: ★★★★★ (AIME full score)
Gemini 3 Pro:  ★★★★

Long context handling
Claude Opus 4.5: ★★★
GPT-5.2:       ★★★★
Gemini 3 Pro: ★★★★★ (2 million tokens)

multimodal capabilities
Claude Opus 4.5: ★★★
GPT-5.2:       ★★★
Gemini 3 Pro: ★★★★★ (supports video)

Chinese support
Claude Opus 4.5: ★★★
GPT-5.2:       ★★★
Gemini 3 Pro:  ★★★

price competitiveness
Claude Opus 4.5: ★★ (most expensive)
GPT-5.2:       ★★★
Gemini 3 Pro: ★★★★ (cheaper)

2. Claude Opus 4.5: King of Code Quality

2.1 Why does Claude Opus 4.5 rank first in code quality?

Authoritative ranking

According to the latest data from LLM Stats:

Code quality ranking: No. 1 in the world
Top 5 overall ranking
Best performance in code generation, code understanding, and refactoring scenarios

Core Advantages

Code understanding ability

Deep understanding of complex code structures
Accurately identify code smells and anti-patterns
Cross-file dependency analysis

Code Generation Quality

The generated code is highly readable
Follow best practices and design patterns
Improved type safety and error handling

Reconstruction capability

Large-scale code refactoring
Architecture evolution suggestions
Technical debt identification and management

Safety Awareness

Proactively identify security vulnerabilities
Comply with OWASP best practices
Input verification and authorization suggestions

2.2 Applicable scenarios

Scenario	Applicability	Description
Code Review	★★★★★	Can find deep-seated problems and provide refactoring suggestions
System Architecture Design	★★★★★	Understand complex systems and provide architectural solutions
Technical Debt Management	★★★★★	Identify technical debt and develop a refactoring plan
Algorithm Implementation	★★★★	The code quality is high, but the mathematical reasoning is slightly inferior to GPT-5.2
Legacy System Migration	★★★★★	Deep understanding of old code and provide migration solutions
Test case generation	★★★★★	Cover edge cases, high test quality
CI/CD Integration	★★★★★	Claude Code CLI Official Tool

2.3 Claude Code CLI: official engineering tool

Claude Opus 4.5 cooperates with Claude Code CLI to provide complete engineering capabilities:

Claude Code CLI
├── Official maintenance (Anthropic)
├── Mature Agent architecture
├── 150+ plug-in ecosystem
├── Project-level context management
├── LSP integration
└── Enterprise-level best practices

Key Benefits:

Anthropic is the core developer of AI safety and engineering specifications
Meets ASL-3 safety standards
Enterprise-level compliance framework
For details, see: Claude Code Best Practices

2.4 Cost Analysis

Subscription prices and usage restrictions

Version	Monthly fee	Quota refresh cycle	Usage quota	Applicable objects
Pro	$20 (≈¥140)	Weekly	Basic Quota	Individual Developer
Teams	$40/person/month (≈¥280)	Weekly	Team Quota	Small Team
Max	$200 (≈¥1400)	Weekly	Large amount	Heavy users

Important Note (from August 28, 2025):

Anthropic introduces new Weekly Usage Limit

The quota is reset every 7 days

Pro and Max users have independent weekly usage caps

After exceeding the quota, you need to wait for the next cycle or upgrade the package

How to continue using the quota after it is used up:

Option 1: Wait for the next refresh cycle (automatically resume after 7 days)

Option 2: Use API KEY to directly consume tokens (pay-as-you-go, no need to wait)

Option 3: Switch/register other subscription accounts (subject to terms of service)

API pay-as-you-go

Scenario	Input	Output
Standard	$1-5/million tokens	$3-15/million tokens

Cost comparison:

Claude Opus is the most expensive of the three

But the code quality is the highest, and it is more economical in complex scenarios (reduces debugging time)

Code review and refactoring scenarios with the highest ROI

3. GPT-5.2: The King of Mathematical Reasoning

3.1 Why is GPT-5.2 the strongest in mathematical reasoning?

Authoritative ranking

According to AIME 2025 (American Invitational Mathematics Competition):

AIME 2025 Ranking: 1st (1.0 out of 10 points)
Top 3 overall ranking
Perform optimally in mathematics, algorithms, and logical reasoning scenarios

Core Advantages

Mathematical reasoning skills

Solve complex mathematical problems
Algorithm design and optimization
Mathematical proof generation
Quantitative strategy analysis

Logical Reasoning

Judgment of complex conditions
Multi-step reasoning chain
Abstract problem modeling
Logic vulnerability identification

Algorithmic capability

Data structure selection
Algorithm complexity analysis
Performance optimization suggestions
Concurrency and parallel computing

Scientific Computing

Numerical analysis
Statistical modeling
Machine learning algorithms
Quantum computing

3.2 Applicable scenarios

Scenario	Applicability	Description
Algorithm Competition	★★★★★	Full marks in mathematical reasoning, optimal algorithm
Quantitative Trading	★★★★★	Complex mathematical models, strategy backtesting
Scientific Computing	★★★★★	Numerical analysis, statistical modeling
Machine Learning	★★★★★	Algorithm implementation, model optimization
Game AI	★★★★★	Game theory, strategy optimization
Cryptozoology	★★★★★	Mathematical foundation, security algorithm
Performance Optimization	★★★★	Algorithm complexity analysis

3.3 GPT-5.2-Codex-Max: code-specific version

OpenAI provides specialized coding models:

GPT-5.2-Codex-Max
├── Focus on code generation
├──Code completion capability
├── Multi-language support
└── Deep code understanding

Features:

Code capabilities equivalent to GPT-5.2
Optimized for programming scenarios
Suitable for integration into IDEs and tools

3.4 Cost Analysis

Subscription prices and usage restrictions

Version	Monthly fee	Quota refresh cycle	Usage quota	Applicable objects
Plus	$20 (≈¥140)	Every 5 hours	30-150 messages/5 hours	Individual Developer
Pro	$200 (≈¥1400)	Every 5 hours	300-1500 local messages or 50-400 cloud tasks/5 hours	Professional users
Team	$30/person/month (≈¥210)	Every 5 hours	Team sharing quota	Team
Enterprise	Customized	Flexible	Customized	Large Enterprise

Important Note:

Quota refreshed every 5 hours (rolling window)

Plus users also have a weekly limit (cap hit after about 6-7 full sessions)

When the limit is exceeded, it will prompt "You've hit your usage limit. Upgrade to Pro or try again in X days Y hours"

Codex CLI, Chat, Agent mode, code review and other functions consume "premium requests"

How to continue using the quota after it is used up:

Option 1: Wait for the next refresh cycle (automatically resume after 5 hours)

Option 2: Use API KEY to directly consume tokens (pay-as-you-go, no need to wait)

Option 3: Upgrade to the Pro version to get a higher credit limit

Option 4: Switch/register other subscription accounts (subject to terms of service)

API pay-as-you-go

Scenario	Input	Output
Standard	$0.25-2/million tokens	$0.75-6/million tokens

Cost comparison:

GPT-5.2 is mid-priced, between Claude and Gemini

The most cost-effective in mathematical reasoning scenarios

Suitable for algorithm-intensive applications

4. Gemini 3 Pro: King of long context and multi-modality

4.1 Why does Gemini 3 Pro lead in long context and multi-modality?

Core Advantages

Extra long context

2 million tokens (longest among the three)
Can handle entire large code bases
Deep correlation analysis across files
Ability to understand long documents

Multi-modal capabilities

Video Understanding (exclusive)
Audio processing
Picture analysis
Multimodal comprehensive reasoning

Google Ecosystem Integration

Google Cloud integration
Android development support
TensorFlow/ML integration
Google Workspace collaboration

4.2 Applicable scenarios

Scenario	Applicability	Description
Large-scale code base	★★★★★	2 million tokens, analyze the entire library at once
Video content analysis	★★★★★	Unique video understanding ability
Multi-modal application	★★★★★	Comprehensive processing of graphics, text, audio and video
Android Development	★★★★★	Official support from Google
Long document processing	★★★★★	Super long document understanding
Knowledge base construction	★★★★★	Large-scale data integration
Code Migration	★★★★	Full library analysis, migration plan

4.3 Gemini 2.0 Flash: speed first version

Google offers a lightweight version:

Gemini 2.0 Flash
├── Fast response speed
├── Lower cost
├── Suitable for simple tasks
└── Real-time interactive scene

4.4 Cost Analysis

Gemini Code Assist Subscription Price

Version	Monthly fee	Refresh cycle	Usage quota	Applicable objects
Standard	$19 (≈¥130)	Daily	Unlimited code completion	Personal developer
Enterprise	$45 (≈¥310)	Daily	100 PR reviews/day	Enterprise Team

Usage Restrictions:

Code Completion: Unlimited for both Standard and Enterprise

Pull Request review: Enterprise 100 times/day, Consumer version 33 times/day

Flash Free Tier: 1500 requests/day (Flash and Flash-Lite shared)

Gemini 3 Pro Preview: 250 messages/24 hours

Gemini 3.0 Ultra: 20 requests/day (a significant reduction of 92% from 250 in 2025)

Main Gemini App: 100 queries/day limit

How to continue using the quota after it is used up:

Option 1: Wait for the next refresh cycle (automatically resume after 1 day)

Option 2: Use API KEY to directly consume tokens (pay-as-you-go, no need to wait)

Option 3: Upgrade to the Enterprise version to get a higher credit limit

Option 4: Switch/register other subscription accounts (subject to terms of service)

API pay-as-you-go

Scenario	Input	Output
Standard	$0.125-1.25/million tokens	$0.375-3.75/million tokens

Cost comparison:

Gemini 3 Pro is the cheapest of the three

Long context scenarios are the most cost-effective

Suitable for large-scale code base analysis

5. In-depth comparison of three major models

5.1 Comparison of programming capabilities

Capability Dimension	Claude Opus 4.5	GPT-5.2	Gemini 3 Pro
Code Generation Quality	★★★★★	★★★★★	★★★★
Code Understanding	★★★★★	★★★★	★★★★
Code Refactor	★★★★★	★★★★	★★★
Debug Capability	★★★★★	★★★★	★★★
Test Case Generation	★★★★★	★★★★	★★★
Document Generation	★★★★★	★★★★	★★★★
Architecture Design	★★★★★	★★★★	★★★

in conclusion:

Code Quality: Claude Opus 4.5 leads the way across the board
Code generation: Claude is equivalent to GPT-5.2
Document Generation: All three are strong

5.2 Comparison of reasoning ability

Capability Dimension	Claude Opus 4.5	GPT-5.2	Gemini 3 Pro
Mathematical Reasoning	★★★★	★★★★★	★★★★
Logical Reasoning	★★★★★	★★★★★	★★★★
Algorithm Design	★★★★	★★★★★	★★★★
Abstract Thinking	★★★★★	★★★★★	★★★★
Multi-step reasoning	★★★★★	★★★★★	★★★★
Creative Thinking	★★★★★	★★★★	★★★★

in conclusion:

Mathematical Reasoning: GPT-5.2 Yiqi Juechen (AIME full score)
Logical Reasoning: Claude is equivalent to GPT-5.2
Creativity: Claude is slightly stronger

5.3 Comparison of engineering capabilities

Capability Dimension	Claude Opus 4.5	GPT-5.2	Gemini 3 Pro
CLI Tools	✅ Claude Code	⭐⭐⭐	⭐⭐⭐
IDE Integration	⭐⭐⭐⭐⭐	⭐⭐⭐⭐	⭐⭐⭐⭐
Plugin Ecosystem	150+ plugins	⭐⭐⭐	⭐⭐⭐
Enterprise Support	★★★★★	★★★★★	★★★★★
API Stability	★★★★★	★★★★★	★★★★★
Document Quality	★★★★★	★★★★	★★★★

in conclusion:

Engineering: Claude Code CLI has the most complete ecosystem
IDE Integration: All three are well supported
Enterprise Support: All three companies have enterprise versions

5.4 Price comparison

Price dimension	Claude Opus 4.5	GPT-5.2	Gemini 3 Pro
Subscription Fee	$20-200	$20-200	$19-45
API Input	$1-5/M	$0.25-2/M	$0.125-1.25/M
API Output	$3-15/M	$0.75-6/M	$0.375-3.75/M
Quota Refresh Period	Every 7 days (weekly)	Every 5 hours	Daily
Price Competitive	★★(most expensive)	★★★	★★★★(cheapest)

in conclusion:

CHEAPEST: Gemini 3 Pro
Most Expensive: Claude Opus 4.5
Quota refresh frequency: GPT-5.2 is the highest (5 hours), Gemini is the second (daily), and Claude is the lowest (weekly)
Cost-effectiveness: needs to be judged based on the usage scenario

5.5 Feature comparison

Features	Claude Opus 4.5	GPT-5.2	Gemini 3 Pro
Extra long context	200K	1M	2M
Video Understanding	❌	❌	✅
Code Review	★★★★★	★★★★	★★★
Multi-modal	Pictures, audio	Pictures, audio	Video, audio, pictures
AIME perfect score	❌	✅	❌
Code Quality No. 1	✅	❌	❌

6. Scenario-based selection suggestions

6.1 Selection according to application scenarios

Code quality and refactoring scenarios

Recommended: Claude Opus 4.5

Scenario	Recommended model	Reason
Code Review	Claude Opus 4.5	Number 1 in Code Quality, Identify Deep Issues
Legacy system reconstruction	Claude Opus 4.5	Deep understanding of old code and providing evolution solutions
Technical debt management	Claude Opus 4.5	Identify technical debt and develop a refactoring plan
Architecture design	Claude Opus 4.5	System-level architecture recommendations
Test case generation	Claude Opus 4.5	Cover edge cases, high quality

Mathematics and Algorithm Scenarios

Recommended: GPT-5.2

Scenario	Recommended model	Reason
Algorithm competition	GPT-5.2	Full score in AIME, strongest mathematical reasoning
Quantitative trading	GPT-5.2	Complex mathematical models, strategy optimization
Scientific Computing	GPT-5.2	Numerical Analysis, Statistical Modeling
Machine learning	GPT-5.2	Algorithm implementation, model optimization
Game AI	GPT-5.2	Game theory, strategy optimization

Recommended: Gemini 3 Pro

Scenario	Recommended model	Reason
Large-scale code base analysis	Gemini 3 Pro	2 million tokens, full database at once
Video content understanding	Gemini 3 Pro	Unique video understanding capabilities
Android Development	Gemini 3 Pro	Google Official Support
Long document processing	Gemini 3 Pro	Extra long context
Multi-modal application	Gemini 3 Pro	Image, text, audio and video synthesis

6.2 Selection based on team size

Individual Developer

Budget	Recommended plan	Monthly fee
Under $30	Gemini 3 Pro API	$7-21
$30-70	GPT-5.2 Plus	$20
$70-210	Claude Opus 4.5 Pro	$200

Small team (2-5 people)

Budget	Recommended plan	Monthly fee
$140-420	Gemini 3 Pro API	$70-280
$420-850	GPT-5.2 Team	$150
$850-1400	Claude Opus 4.5 Team	$200-400

CUHK team (20+ people)

Budget	Recommended plan	Description
$2800+/month	Mixed strategy	Different models for different scenarios
$7000+/month	Enterprise customization	All three companies support enterprise customization

7. Mixed strategy: multi-model collaboration

7.1 Why do we need multiple models?

Different models have different advantages, and mixed use can achieve the best results:

Multi-model collaborative strategy
├── Claude Opus 4.5: Code quality control
├── GPT-5.2: Algorithms and Mathematical Issues
├── Gemini 3 Pro: Large-scale code base analysis
└── Cost optimization: choose a model based on the task

7.2 Mixed Strategy Example

Model allocation in the development process

Development stage	Recommended model	Reasons
Requirements Analysis	Claude Opus 4.5	In-depth understanding, architecture design
Algorithm Design	GPT-5.2	The strongest mathematical reasoning
Code Implementation	Claude Opus 4.5	Highest code quality
Code Review	Claude Opus 4.5	Identify Deep Issues
Performance Optimization	GPT-5.2	Algorithm complexity analysis
Full library analysis	Gemini 3 Pro	Extra long context
Test Cases	Claude Opus 4.5	Comprehensive Coverage
Document Generation	Gemini 3 Pro	Long Document Processing

7.3 Cost optimization strategy

Select models based on task complexity

Complexity	Recommended model	Reasons
Simple tasks	Gemini 3 Pro	The cheapest and enough
Medium Task	GPT-5.2	High cost performance
Complex tasks	Claude Opus 4.5	Quality first

Cost comparison example

Assume 1000 tasks are processed per month:

Strategy	Monthly Fee	Token Cost	Total Cost
All for Claude	$200	$2800	$3000
Fully use GPT-5.2	$200	$1100	$1300
All with Gemini	$0	$550	$550
Mixed Strategy	$200	$850	$1050

Conclusion: A hybrid strategy can save 65% of costs while maintaining high quality.

8. Comparison of engineering tools

8.1 CLI Tool Comparison

Tools	Claude Code	OpenAI CLI	Gemini CLI
OFFICIAL SUPPORT	✅	⭐⭐⭐	⭐⭐⭐
Agent Capabilities	★★★★★	★★★	★★★
Plug-in Ecology	150+	⭐⭐	⭐⭐
Project Context	★★★★★	★★★★	★★★★
Multiple Model Support	⭐⭐	⭐⭐	⭐⭐

Conclusion: Claude Code CLI is the most complete engineering tool.

8.2 IDE integration comparison

IDE	Claude	GPT	Gemini
VS Code	✅	✅	✅
JetBrains	✅	✅	✅
Cursor	✅ Native	✅	⭐⭐
GitHub Copilot	⭐⭐	✅	⭐⭐

Conclusion: All three companies have good IDE support, and Cursor has the best support for Claude.

9. Implementation Suggestions

9.1 Summary of recommended solutions

┌─────────────────────────────────────────────────────────┐
│ Top foreign model selection solutions │
├─────────────────────────────────────────────────────────┤
│                                                         │
│ Code quality first: Claude Opus 4.5 │
│ ├── Code quality ranks first in the world │
│ ├── Code review and refactoring are the strongest │
│ ├── Claude Code CLI engineering improvement │
│ └── Suitable for: code review, architecture design, technical debt management │
│                                                         │
│ Mathematical reasoning is preferred: GPT-5.2 │
│ ├── AIME 2025 Full Score (1st Place) │
│ ├── Algorithms and scientific calculations are the strongest │
│ └── Suitable for: algorithm competitions, quantitative trading, machine learning │
│                                                         │
│ Long context first: Gemini 3 Pro │
│ ├── 2 million tokens super long context │
│ ├── The strongest multi-modal capability (supports video) │
│ └── Suitable for: large-scale code base, video understanding, Android development │
│                                                         │
│ Hybrid strategy: selecting the optimal model based on the task │
│ ├── Simple tasks → Gemini 3 Pro (cheapest) │
│ ├── Code quality → Claude Opus 4.5 (strongest) │
│ ├── Mathematical Reasoning → GPT-5.2 (Strongest) │
│ └── Cost optimization: save 65%+ │
│                                                         │
└─────────────────────────────────────────────────────────┘

9.2 Phased implementation

Phase 1: Single model pilot (1-2 weeks)

Steps	Content	Objectives
1	Choose a main model (Claude is recommended)	Verify the effect
2	Small-scale pilot (2-3 people)	Collect feedback
3	Evaluate costs and effects	Decision-making options

Phase 2: Hybrid Strategy (1-2 months)

Steps	Content	Coverage
1	Model selection based on task type	Whole team
2	Establish usage specifications and best practices	Documentation
3	Cost Monitoring and Optimization	Ongoing

The third stage: full application (ongoing)

Steps	Content	Objectives
1	Multi-model collaborative workflow	Automation
2	Enterprise-level deployment	Scale
3	Continuously evaluate new models	Stay ahead of the curve

10. Cost-benefit analysis

10.1 Return on Investment (ROI)

Assume a team of 10 people with an average annual salary of $150,000:

Solution	Monthly Cost	Annual Cost	Efficiency Improvement	Annual Value	ROI
Claude Opus 4.5	$1700	$20400	30%	$450000	2205%
GPT-5.2	$1150	$13800	25%	$375000	2717%
Gemini 3 Pro	$700	$8400	20%	$300000	3571%
Mixed Strategy	$1050	$12600	30%	$450000	3571%

Conclusion: Mixed strategies have the highest ROI.

10.2 True cost comparison

Team of 10 people, monthly budget $1400

Pure Claude solution:

Claude Teams: $40 × 10 = $400
Claude API: $857
Available tokens: approximately 3.5 million/month
Total: $1257/month

Hybrid Strategy:

Claude Teams: $400 (code review)
GPT-5.2 API: $285 (algorithm)
Gemini API: $215 (full database analysis)
Total: $900/month, saving 28%

11. Risks and Challenges

11.1 Potential risks

Risk	Impact	Mitigation
Vendor Lock-in	High	Multi-model strategy, stay flexible
Cost Overrun	Medium	Budget Alarm, Cost Monitoring
Model changes	Medium	Continuous evaluation, rapid adaptation
Data Security	High	Enterprise Edition, private deployment

11.2 Coping strategies

Multi-model strategy: Reduce the risk of supplier lock-in
Cost Monitoring: Set budget alarms
Continuous Evaluation: Pay attention to new model releases
Data Security: Choose Enterprise Edition or Private Deployment

12. Summary and suggestions

12.1 Core Conclusions

The three top foreign models each have their own advantages, and a mixed strategy is recommended

Claude Opus 4.5: No. 1 in code quality, suitable for code review and refactoring
GPT-5.2: Full score in mathematical reasoning, suitable for algorithms and scientific calculations
Gemini 3 Pro: 2 million tokens, suitable for large-scale code bases
Hybrid Strategy: 65% cost savings while maintaining high quality

12.2 Key arguments

Code Quality: Claude Opus 4.5 ranked first in the world
Mathematical Reasoning: GPT-5.2 AIME full score
Long context: Gemini 3 Pro 2 million tokens
Engineering: Claude Code CLI is the most complete
Cost: Gemini is the cheapest, Claude is the most expensive
Hybrid Strategy: The most cost-effective

12.3 Expected return

Yield Types	Claude	GPT-5.2	Gemini	Mixed Strategies
Code Quality	⭐⭐⭐⭐⭐	⭐⭐⭐⭐	⭐⭐⭐	⭐⭐⭐⭐⭐
Mathematical Reasoning	⭐⭐⭐⭐	⭐⭐⭐⭐⭐	⭐⭐⭐⭐	⭐⭐⭐⭐⭐
LONG CONTEXT	⭐⭐⭐	⭐⭐⭐⭐	⭐⭐⭐⭐⭐	⭐⭐⭐⭐⭐
Monthly Fee	$200	$200	$0	$200
API Cost	High	Medium	Low	Medium Low
ROI	2205%	2717%	3571%	3571%

13. Reference sources

Official website

Authoritative list

Price and Cost

Product comparison

Technical documentation

Document updated: December 2025

Notice:

Price information may change at any time, please refer to the official announcement.
AI model capability rankings are based on public benchmark tests, and actual results may vary depending on usage scenarios.
The hybrid strategy requires engineering support, and it is recommended to start with a pilot
Enterprise users are recommended to choose the enterprise version or private deployment to ensure data security.

Executive summary​

1. Core comparison of three major models​

1.1 Comparison of basic information​

1.2 Core Competence Radar Chart​

2. Claude Opus 4.5: King of Code Quality​

2.1 Why does Claude Opus 4.5 rank first in code quality?​

Authoritative ranking​

Core Advantages​

2.2 Applicable scenarios​

2.3 Claude Code CLI: official engineering tool​

2.4 Cost Analysis​

Subscription prices and usage restrictions​

API pay-as-you-go​

3. GPT-5.2: The King of Mathematical Reasoning​

3.1 Why is GPT-5.2 the strongest in mathematical reasoning?​

Authoritative ranking​

Core Advantages​

3.2 Applicable scenarios​

3.3 GPT-5.2-Codex-Max: code-specific version​

3.4 Cost Analysis​

Subscription prices and usage restrictions​

API pay-as-you-go​

4. Gemini 3 Pro: King of long context and multi-modality​

4.1 Why does Gemini 3 Pro lead in long context and multi-modality?​

Core Advantages​

4.2 Applicable scenarios​

4.3 Gemini 2.0 Flash: speed first version​

4.4 Cost Analysis​

Gemini Code Assist Subscription Price​

API pay-as-you-go​

5. In-depth comparison of three major models​

5.1 Comparison of programming capabilities​

5.2 Comparison of reasoning ability​

5.3 Comparison of engineering capabilities​

5.4 Price comparison​

5.5 Feature comparison​

6. Scenario-based selection suggestions​

6.1 Selection according to application scenarios​

Code quality and refactoring scenarios​

Mathematics and Algorithm Scenarios​

Large-scale code base and multi-modal scenarios​

6.2 Selection based on team size​

Individual Developer​

Small team (2-5 people)​

CUHK team (20+ people)​

7. Mixed strategy: multi-model collaboration​

7.1 Why do we need multiple models?​

7.2 Mixed Strategy Example​

Model allocation in the development process​

7.3 Cost optimization strategy​

Select models based on task complexity​

Cost comparison example​

8. Comparison of engineering tools​

8.1 CLI Tool Comparison​

8.2 IDE integration comparison​

9. Implementation Suggestions​

9.1 Summary of recommended solutions​

9.2 Phased implementation​

Phase 1: Single model pilot (1-2 weeks)​

Phase 2: Hybrid Strategy (1-2 months)​

The third stage: full application (ongoing)​

10. Cost-benefit analysis​

10.1 Return on Investment (ROI)​

10.2 True cost comparison​

Team of 10 people, monthly budget $1400​

11. Risks and Challenges​

11.1 Potential risks​

11.2 Coping strategies​

12. Summary and suggestions​

12.1 Core Conclusions​

12.2 Key arguments​

12.3 Expected return​

13. Reference sources​

Official website​

Authoritative list​

Price and Cost​

Product comparison​

Technical documentation​

Executive summary

1. Core comparison of three major models

1.1 Comparison of basic information

1.2 Core Competence Radar Chart

2. Claude Opus 4.5: King of Code Quality

2.1 Why does Claude Opus 4.5 rank first in code quality?

Authoritative ranking

Core Advantages

2.2 Applicable scenarios

2.3 Claude Code CLI: official engineering tool

2.4 Cost Analysis

Subscription prices and usage restrictions

API pay-as-you-go

3. GPT-5.2: The King of Mathematical Reasoning

3.1 Why is GPT-5.2 the strongest in mathematical reasoning?

Authoritative ranking

Core Advantages

3.2 Applicable scenarios

3.3 GPT-5.2-Codex-Max: code-specific version

3.4 Cost Analysis

Subscription prices and usage restrictions

API pay-as-you-go

4. Gemini 3 Pro: King of long context and multi-modality

4.1 Why does Gemini 3 Pro lead in long context and multi-modality?

Core Advantages

4.2 Applicable scenarios

4.3 Gemini 2.0 Flash: speed first version

4.4 Cost Analysis

Gemini Code Assist Subscription Price

API pay-as-you-go

5. In-depth comparison of three major models

5.1 Comparison of programming capabilities

5.2 Comparison of reasoning ability

5.3 Comparison of engineering capabilities

5.4 Price comparison

5.5 Feature comparison

6. Scenario-based selection suggestions

6.1 Selection according to application scenarios

Code quality and refactoring scenarios

Mathematics and Algorithm Scenarios

Large-scale code base and multi-modal scenarios

6.2 Selection based on team size

Individual Developer

Small team (2-5 people)

CUHK team (20+ people)

7. Mixed strategy: multi-model collaboration

7.1 Why do we need multiple models?

7.2 Mixed Strategy Example

Model allocation in the development process

7.3 Cost optimization strategy

Select models based on task complexity

Cost comparison example

8. Comparison of engineering tools

8.1 CLI Tool Comparison

8.2 IDE integration comparison

9. Implementation Suggestions

9.1 Summary of recommended solutions

9.2 Phased implementation

Phase 1: Single model pilot (1-2 weeks)

Phase 2: Hybrid Strategy (1-2 months)

The third stage: full application (ongoing)

10. Cost-benefit analysis

10.1 Return on Investment (ROI)

10.2 True cost comparison

Team of 10 people, monthly budget $1400

11. Risks and Challenges

11.1 Potential risks

11.2 Coping strategies

12. Summary and suggestions

12.1 Core Conclusions

12.2 Key arguments

12.3 Expected return

13. Reference sources

Official website

Authoritative list

Price and Cost

Product comparison

Technical documentation