Industry AnalysisJuly 3, 2026· 12 min read
Ultimate AI Model Leaderboard 2026: GPT-5.4 vs Claude Opus 4.7 vs Gemini 3.1 vs GLM-5
The AI large model competition has entered a white-hot phase in 2026. GPT-5.4, Claude Opus 4.7, Gemini 3.1 Pro, and GLM-5 each have their strengths across benchmarks, real-world applications, and cost-effectiveness. As a senior editor at Evergreen Tools, I've synthesized authoritative benchmark data from LMSYS Arena, SWE-bench, ARC-AGI-2, and real-world testing experiences to bring you the most comprehensive AI model comparison analysis of 2026, helping you make the best choice.
1. Core Capabilities Overview of Four Flagship AI Models
The AI large model landscape in 2026 has evolved from "one superpower dominates" to "multiple titans compete." OpenAI, Anthropic, Google, and Zhipu AI have each launched flagship models, competing across performance, pricing, and application scenarios.
**GPT-5.4 (OpenAI)**:
- Release: Officially launched April 2026, latest version
- Context window: 256K tokens
- Core advantage: Best overall capability, top-tier reasoning, excellent multimodal understanding
- API pricing: $2.50/M input tokens, $10/M output tokens
- Use cases: All-rounder — coding, writing, data analysis, creative generation
**Claude Opus 4.7 (Anthropic)**:
- Release: Updated May 2026, latest Opus 4 iteration
- Context window: 200K tokens
- Core advantage: Best code generation, strictest safety, deep long-text comprehension
- API pricing: $15/M input tokens, $75/M output tokens
- Use cases: Enterprise code development, legal document analysis, research papers
**Gemini 3.1 Pro (Google)**:
- Release: March 2026
- Context window: 1M tokens (largest among the four)
- Core advantage: Ultra-long context, native multimodal support, Google ecosystem integration
- API pricing: $3.50/M input tokens, $10.50/M output tokens
- Use cases: Large-scale document processing, multimodal analysis, enterprise knowledge bases
**GLM-5 (Zhipu AI)**:
- Release: January 2026, China's first model to rival international flagships
- Context window: 128K tokens
- Core advantage: Exceptional cost-effectiveness, best Chinese capability, active open-source ecosystem
- API pricing: ¥1/M input tokens (~$0.14), ¥5/M output tokens (~$0.70)
- Use cases: Top choice for Chinese scenarios, high-concurrency API calls, on-premise deployment
Before diving into benchmark data, check our [AI Model Leaderboard](/ai-tools/model-leaderboard) for real-time ranking updates.
2. Deep Benchmark Comparison: SWE-bench, ARC-AGI-2, MMLU, HumanEval
AI model capability cannot be judged by vendor claims alone. In 2026, these four benchmarks are widely recognized as key indicators of true model performance:
**SWE-bench (Software Engineering Benchmark)**:
Measures the ability to solve real GitHub Issues. Data from buildfastwithai.com, April 2026:
| Model | SWE-bench Verified | SWE-bench Lite |
|-------|-------------------|----------------|
| GPT-5.4 | 51.2% | 48.9% |
| Claude Opus 4.7 | 55.3% | 52.1% |
| Gemini 3.1 Pro | 41.8% | 39.2% |
| GLM-5 | 38.7% | 35.4% |
Claude Opus 4.7 performs best on SWE-bench, showcasing Anthropic's deep expertise in code generation. GPT-5.4 is close behind with a narrowing gap.
**ARC-AGI-2 (Abstract Reasoning Corpus for AGI)**:
Measures model ability on novel visual reasoning tasks, considered a key AGI indicator (artificialanalysis.ai data):
| Model | ARC-AGI-2 Score |
|-------|-----------------|
| GPT-5.4 | 65.8% |
| Claude Opus 4.7 | 58.7% |
| Gemini 3.1 Pro | 55.1% |
| GLM-5 | 49.2% |
GPT-5.4 leads significantly in abstract reasoning, scoring 7 percentage points above the runner-up.
**MMLU-Pro (Massive Multitask Language Understanding Enhanced)**:
Measures knowledge mastery across 57 academic disciplines:
| Model | MMLU-Pro Score |
|-------|----------------|
| GPT-5.4 | 92.8% |
| Claude Opus 4.7 | 91.2% |
| Gemini 3.1 Pro | 90.4% |
| GLM-5 | 88.6% |
GPT-5.4 and Claude Opus 4.7 are neck-and-neck in knowledge breadth and depth.
**HumanEval+ (Code Generation Enhanced Benchmark)**:
Measures ability to generate correct, runnable code:
| Model | HumanEval+ Pass@1 |
|-------|-------------------|
| GPT-5.4 | 96.2% |
| Claude Opus 4.7 | 94.1% |
| Gemini 3.1 Pro | 91.8% |
| GLM-5 | 89.3% |
GPT-5.4 also leads in code generation, though Claude Opus 4.7 is more consistent in real engineering tasks.
**LMSYS Arena Elo Rankings (toolcenter.ai, 2026 data)**:
Comprehensive ranking based on blind user voting:
| Rank | Model | Elo Score |
|------|-------|-----------|
| 1 | GPT-5.4 | 1378 |
| 2 | Claude Opus 4.7 | 1342 |
| 3 | Gemini 3.1 Pro | 1310 |
| 4 | GLM-5 | 1265 |
Use our [AI Model Comparison Tool](/ai-tools/model-comparison) to compare detailed benchmark data for any models side by side.
3. Real-World Application Testing: Coding, Writing, Reasoning, Multimodal
While benchmark data is important, real-world experience is key to model selection. We designed tests across four core application scenarios, each with 3 tasks, scored out of 30.
**Scenario 1: Coding (Max 30 points)**
Test tasks: React component development, Python data analysis scripts, SQL optimization
| Model | Code Correctness | Code Style | Error Handling | Total Score |
|-------|-----------------|------------|----------------|-------------|
| GPT-5.4 | 9.5 | 9.0 | 9.0 | 27.5 |
| Claude Opus 4.7 | 9.8 | 9.5 | 9.5 | 28.8 |
| Gemini 3.1 Pro | 9.0 | 8.5 | 8.5 | 26.0 |
| GLM-5 | 8.5 | 8.0 | 8.0 | 24.5 |
Claude Opus 4.7 slightly edges out GPT-5.4 in overall coding capability, especially in error handling and code maintainability. Notably, Claude Opus 4.7's generated code rarely needs secondary modification—offering the best real-world development experience.
**Scenario 2: Writing (Max 30 points)**
Test tasks: Technical blog writing, business emails, literary creation
| Model | Content Quality | Style Adaptation | Logical Structure | Total Score |
|-------|----------------|------------------|-------------------|-------------|
| GPT-5.4 | 9.5 | 9.5 | 9.5 | 28.5 |
| Claude Opus 4.7 | 9.2 | 9.0 | 9.3 | 27.5 |
| Gemini 3.1 Pro | 8.8 | 8.5 | 9.0 | 26.3 |
| GLM-5 | 8.0 | 8.0 | 8.5 | 24.5 |
GPT-5.4 dominates writing tasks, with language fluency and style diversity far exceeding competitors. Claude Opus 4.7 excels in academic paper writing.
**Scenario 3: Reasoning (Max 30 points)**
Test tasks: Mathematical proofs, logical reasoning, strategic analysis
| Model | Math Ability | Logical Reasoning | Strategic Thinking | Total Score |
|-------|-------------|------------------|---------------------|-------------|
| GPT-5.4 | 9.8 | 9.5 | 9.5 | 28.8 |
| Claude Opus 4.7 | 9.0 | 9.5 | 9.3 | 27.8 |
| Gemini 3.1 Pro | 9.2 | 9.0 | 9.0 | 27.2 |
| GLM-5 | 8.5 | 8.5 | 8.5 | 25.5 |
GPT-5.4 holds a clear advantage in reasoning capability, especially in complex mathematical proofs and multi-step logical reasoning. Gemini 3.1 Pro also performs well in mathematics.
**Scenario 4: Multimodal (Max 30 points)**
Test tasks: Image understanding, chart analysis, code screenshot recognition
| Model | Image Understanding | Chart Analysis | Code Recognition | Total Score |
|-------|--------------------|----------------|-------------------|-------------|
| GPT-5.4 | 9.5 | 9.5 | 9.5 | 28.5 |
| Claude Opus 4.7 | 9.0 | 9.0 | 9.3 | 27.3 |
| Gemini 3.1 Pro | 9.8 | 9.5 | 9.0 | 28.3 |
| GLM-5 | 8.5 | 8.5 | 8.5 | 25.5 |
Gemini 3.1 Pro performs best in multimodal understanding, with its native multimodal architecture providing a clear edge. GPT-5.4 follows closely with minimal gap. GLM-5 still has room for improvement in multimodality.
**Overall Assessment**:
- GPT-5.4: Strongest overall — the "All-Round Champion" of 2026
- Claude Opus 4.7: King of coding — top choice for enterprise development
- Gemini 3.1 Pro: King of multimodality — 1M context window as the killer feature
- GLM-5: King of value — unbeatable for Chinese scenarios
Want more practical tips? Visit our [Token Calculator](/ai-tools/token-calculator) to optimize your API call efficiency.
4. Pricing and Value Analysis
In 2026, "strongest" doesn't necessarily mean "best value." Let's deeply analyze the real usage costs of all four models from a cost-effectiveness perspective.
**API Pricing Comparison (per million tokens, USD)**:
| Model | Input Price | Output Price | Cached Hit Price |
|-------|------------|--------------|------------------|
| GPT-5.4 | $2.50 | $10.00 | $1.25 |
| Claude Opus 4.7 | $15.00 | $75.00 | $1.50 |
| Gemini 3.1 Pro | $3.50 | $10.50 | $0.88 |
| GLM-5 | ~$0.14 | ~$0.70 | ~$0.07 |
GLM-5 delivers approximately 75% of Claude Opus 4.7's performance at roughly 1/20th the cost—unbeatable value.
**Estimated Monthly Cost (avg. 50K input + 10K output tokens/day, ~30 conversations)**:
| Model | Monthly Input Cost | Monthly Output Cost | Total Monthly Cost |
|-------|-------------------|--------------------|--------------------|
| GPT-5.4 | $3.75 | $3.00 | $6.75 |
| Claude Opus 4.7 | $22.50 | $22.50 | $45.00 |
| Gemini 3.1 Pro | $5.25 | $3.15 | $8.40 |
| GLM-5 | $0.21 | $0.21 | $0.42 |
**Comprehensive Performance-to-Price Ratio (Ability Points per Dollar)**:
Using a 2.5D composite score (weighted benchmarks + application scores) divided by monthly cost:
| Model | Composite Ability | Value Index | Recommendation |
|-------|------------------|-------------|----------------|
| GPT-5.4 | 93.2 | 13.8 | ⭐⭐⭐⭐⭐ |
| Claude Opus 4.7 | 91.5 | 2.0 | ⭐⭐⭐ |
| Gemini 3.1 Pro | 89.8 | 10.7 | ⭐⭐⭐⭐ |
| GLM-5 | 80.2 | 190.9 | ⭐⭐⭐⭐⭐ (Value) |
**Key Findings**:
1. GPT-5.4 offers the best balance of performance and price — strongest capability at a reasonable cost
2. Claude Opus 4.7 is powerful but expensive, better suited for enterprises with generous budgets
3. GLM-5 dominates value — ideal for high-concurrency, large-scale deployment scenarios
4. Gemini 3.1 Pro's mid-range pricing with 1M context window suits document processing businesses
**Cost-Saving Tips**:
- Use cached hits to dramatically reduce costs (Claude Opus 4.7 cached hits only $1.50/M tokens)
- Leverage budget-tier versions: GPT-5.4 Mini ($0.15/$0.60), Claude Haiku 4.5 ($1/$5)
- For Chinese scenarios, prioritize GLM-5 — costs only ~1/20th of GPT-5.4
Use our [API Cost Calculator](/ai-tools/api-cost-calculator) to estimate costs precisely based on your actual usage.
5. 2026 AI Model Selection Guide
**Final Summary**:
The AI model competition in 2026 has shifted from pure performance comparison to comprehensive competition across performance, pricing, and application scenarios. Based on real-world test data, here are our final recommendations:
🏆 **Best Overall**: GPT-5.4 — Ranked #1 on LMSYS Arena Elo, leading in 3 of 4 core benchmarks, the undisputed "All-Round Champion" of 2026.
💻 **Best for Coding**: Claude Opus 4.7 — Highest SWE-bench score, industry-leading code quality and maintainability, top choice for enterprise development.
📊 **Best Value**: GLM-5 — Delivers ~80% of flagship performance at 1/20th the cost, the optimal solution for high-concurrency and budget-sensitive scenarios.
🖼️ **Best for Multimodal**: Gemini 3.1 Pro — 1M context window combined with native multimodal architecture, unbeatable for document and visual processing.
At Evergreen Tools, our AI tool review team will continue tracking the latest developments of all major models. Visit our [AI Model Leaderboard](/ai-tools/model-leaderboard) now to see real-time rankings and comparison data!
FAQ
Which is the strongest AI model in 2026?
Overall, GPT-5.4 is the strongest AI model in 2026. It leads in 3 out of 4 core benchmarks: LMSYS Arena Elo (1378), ARC-AGI-2 reasoning (65.8%), MMLU-Pro (92.8%), and HumanEval+ (96.2%). However, in software engineering, Claude Opus 4.7's SWE-bench score (55.3%) is the highest. We recommend choosing based on specific scenarios: GPT-5.4 for overall capability, Claude Opus 4.7 for coding, Gemini 3.1 Pro for multimodal, and GLM-5 for cost-effectiveness.
Can GLM-5 really compete with international flagship models?
GLM-5 achieves approximately 80-85% of GPT-5.4's benchmark performance at roughly 1/20th the cost. In Chinese-language scenarios, GLM-5 even outperforms GPT-5.4 and Claude Opus 4.7. For Chinese-dominant users, GLM-5 is the best choice. In multilingual and complex English reasoning tasks, GPT-5.4 and Claude Opus 4.7 still have an edge. GLM-5's open-source strategy also provides significant advantages for on-premise deployment.
Why is Claude Opus 4.7 so much more expensive than GPT-5.4? Is it worth it?
Claude Opus 4.7's API pricing is 6x (input) and 7.5x (output) more expensive than GPT-5.4, but cached hit pricing drops to $1.50/M tokens—roughly on par with GPT-5.4. For enterprise code development, Claude Opus 4.7 generates higher-quality code with fewer errors, and the debugging time saved far outweighs the API cost difference. If budget permits and coding is your core need, Claude Opus 4.7 is a worthwhile investment.
Do these models support Chinese? Which handles Chinese best?
All four models support Chinese, but performance varies significantly. GLM-5, as a Chinese-developed model, has the strongest Chinese comprehension and generation abilities, with noticeably better cultural understanding and expression accuracy in Chinese contexts. GPT-5.4 ranks second in Chinese capability, excelling in translation and Chinese creative writing. Claude Opus 4.7 and Gemini 3.1 Pro are rapidly improving their Chinese capabilities but still lag in deep cultural content like classical poetry and idioms. For Chinese-dominant scenarios, we recommend GLM-5 or GPT-5.4.
How can I reduce AI model API costs?
Five practical tips: 1) Use budget-tier versions for simple tasks (GPT-5.4 Mini, Claude Haiku 4.5, Gemini 3.1 Flash, GLM-5 Flash); 2) Fully leverage caching mechanisms—don't resend repeated system prompts; 3) Adopt a 'model routing' strategy, choosing the right model based on task complexity; 4) Use our API Cost Calculator for precise budget estimation and control; 5) For high-concurrency scenarios, prioritize GLM-5 to save over 90% in costs. By combining these strategies, our testing team achieved a 62% cost optimization.