GPT-5.1 Review: OpenAI's Benchmark Champion with 76.3% SWE-bench Score (November 2025)
GPT-5.1 achieved 76.3% on SWE-bench Verified and 94% on AIME 2025. See real performance data, adaptive reasoning, and how it compares to Claude 4.5 and Gemini 3.
Breaking: GPT-5.1 Released November 13, 2025
Just one day after GPT-5's debut, OpenAI released GPT-5.1 to their API platform on November 13, 2025, as "the next model in the GPT-5 series balancing intelligence and speed for agentic and coding tasks."
The results? 76.3% on SWE-bench Verified and 94.0% on AIME 2025—making it the second most intelligent LLM as of November 19, 2025 according to artificialanalysis.ai.
But how does it perform in real-world development? This comprehensive review breaks down verified benchmarks, developer feedback, and cost-effectiveness to help you decide if GPT-5.1 is right for your use case.
All benchmark data is sourced from OpenAI's official system card, independent testing platforms, and verified developer reports from November 2025.
The Big Picture: Where GPT-5.1 Stands
| Feature | GPT-5.1 | Claude Sonnet 4.5 | Gemini 3 Pro |
|---|---|---|---|
| Release Date | November 13, 2025 | September 2025 | November 18, 2025 |
| SWE-bench Verified | 76.3% | 77.2% (highest) | Not disclosed |
| AIME 2025 (Math) | 94.0% | Not disclosed | Not disclosed |
| Intelligence Rank | #2 (artificialanalysis.ai) | Not ranked | Not ranked |
| Adaptive Reasoning | Yes (dynamic thinking time) | No | No |
| Best For | Balanced intelligence & speed | Production reliability | Multimodal + speed |
Sources: OpenAI GPT-5.1 System Card, artificialanalysis.ai, November 2025
Core Innovation: Adaptive Reasoning
What Makes GPT-5.1 Different?
Unlike previous models that use a fixed amount of "thinking time" for every task, GPT-5.1 dynamically adapts how much time it spends thinking based on task complexity.
Example workflow:
| Task Complexity | Thinking Tokens Used | Response Time |
|---|---|---|
| Simple API call | ~100 tokens | <1 second |
| Medium refactoring | ~5,000 tokens | 3-5 seconds |
| Complex architecture design | ~50,000 tokens | 30-60 seconds |
Why this matters:
- Token efficiency: 30% fewer thinking tokens on average compared to GPT-5
- Cost savings: Only pay for the reasoning you need
- Faster simple tasks: "No reasoning" mode responds instantly on straightforward requests
Source: OpenAI, "GPT-5.1: A smarter, more conversational ChatGPT," November 2025
Benchmark Performance: The Numbers
SWE-Bench Verified: Real-World Coding
SWE-bench Verified tests AI models on actual GitHub issues from popular open-source repositories.
| Model | SWE-bench Verified Score | Improvement vs Predecessor |
|---|---|---|
| Claude Sonnet 4.5 | 77.2% | ~+35% vs Sonnet 4 |
| GPT-5.1 | 76.3% | +4.8% vs GPT-5 (72.8%) |
| GPT-5 | 72.8% | Baseline |
What this means: In a test of 500 real GitHub issues, GPT-5.1 successfully resolved 381 of them without human intervention—just 5 fewer than Claude Sonnet 4.5.
Winner: Claude Sonnet 4.5 (by a narrow margin)
Source: OpenAI GPT-5.1 System Card, November 2025
AIME 2025: Advanced Mathematics
The American Invitational Mathematics Examination (AIME) is a 15-question, 3-hour test taken by the top 5% of high school math students in the US.
| Model | AIME 2025 Score | Human Expert Equivalent |
|---|---|---|
| GPT-5.1 | 94.0% (14.1/15 questions) | Top 0.1% of high schoolers |
| GPT-5 | 94.6% | Top 0.1% of high schoolers |
| GPT-4o | ~13% | Average participant |
What this means: GPT-5.1 performs at near-human expert level in advanced mathematics, with virtually no degradation from GPT-5.
Winner: Tie (GPT-5.1 and GPT-5 both at 94%+)
Source: OpenAI System Card, November 2025
LiveCodeBench: Dynamic Programming Challenges
LiveCodeBench features coding problems that were published after the model's training cutoff—meaning the model couldn't have memorized solutions.
GPT-5.1 performance:
- Outperforms GPT-5 on LiveCodeBench (specific scores not disclosed)
- Demonstrates genuine reasoning rather than pattern matching
Source: Medium, "How GPT-5.1 compares to GPT-5," November 19, 2025
Cline's Diff Editing Benchmark: Code Modification Accuracy
Cline's benchmark tests how accurately models can modify existing code without introducing bugs.
GPT-5.1 performance:
- 7% improvement over previous best score
- State-of-the-art (SOTA) as of November 2025
What this means: When asked to modify 100 code files, GPT-5.1 makes 7 fewer errors than competing models.
Source: Axis Intelligence, "GPT-5.1: Technical Analysis," November 2025
Real-World Developer Experience
What Developers Are Saying
From independent surveys and testing:
Balanced Performance:
"GPT-5.1 is still the best all-rounder. The third-party integrations and plugins give it an edge for real-world workflows."
Speed vs Quality Trade-off:
"GPT-5.1 dynamically adapts reasoning time. For simple tasks, it's blazing fast. For complex problems, it takes its time—and the results show."
Ecosystem Advantage:
"The OpenAI ecosystem is unmatched. Claude might beat us on raw benchmarks, but GPT-5.1 integrates with everything we already use."
Source: Developer feedback aggregated from Reddit r/LocalLLaMA, Hacker News (November 2025)
Where GPT-5.1 Excels
1. General-Purpose Reasoning
- Handles diverse tasks without specialized prompting
- Strong performance across coding, math, writing, and analysis
2. Ecosystem Integrations
- OpenAI plugins (70+ available)
- Third-party tools (Zapier, Make, etc.)
- Extensive API ecosystem
3. Adaptive Speed
- Fast on simple tasks (instant responses)
- Deep reasoning on complex problems
- Token-efficient (30% fewer thinking tokens)
4. Balanced Cost-Performance
- Cheaper than GPT-5 on simple tasks (less reasoning time)
- Comparable performance to Claude 4.5 at potentially lower cost
Where GPT-5.1 Falls Short
Based on comparative testing:
❌ Raw Coding Accuracy - Claude 4.5 edges ahead by 0.9% on SWE-bench ❌ Multimodal Tasks - Gemini 3 Pro dominates on screen understanding ❌ UI/Frontend Speed - Gemini 3 is 15-20% faster on visual tasks ❌ Context Window - 400K tokens vs Gemini 3's 1M tokens
GPT-5.1 Variants: Choosing the Right Model
OpenAI released multiple GPT-5.1 variants for different use cases:
GPT-5.1 Instant (Standard)
- Best for: General-purpose tasks, balanced speed/accuracy
- Reasoning mode: Adaptive (dynamic thinking time)
- Use case: Web apps, chatbots, analysis
GPT-5.1 Thinking
- Best for: Complex reasoning tasks
- Reasoning mode: Extended (more thinking tokens)
- Use case: Research, advanced mathematics, architecture design
GPT-5.1-Codex-Max
- Best for: Coding and agentic workflows
- Token efficiency: 30% fewer thinking tokens than GPT-5.1-Codex (with same or better performance)
- Use case: Software development, code review, refactoring
Source: OpenAI, "Building more with GPT-5.1-Codex-Max," November 2025
Pricing: Not Yet Disclosed
As of November 26, 2025, OpenAI has not publicly disclosed GPT-5.1 pricing.
Historical context:
- GPT-4o: $5/$20 per million tokens (input/output)
- GPT-3.5 Turbo: $3/$6 per million tokens
Estimated pricing (based on historical patterns):
- GPT-5.1 Standard: Likely $5-8 / $20-30 per million tokens
- GPT-5.1-Codex-Max: Possibly premium tier ($10-15 / $40-60)
Note: Actual pricing may vary. Check OpenAI's official pricing page for updates.
Head-to-Head: GPT-5.1 vs Competitors
GPT-5.1 vs Claude Sonnet 4.5
| Metric | GPT-5.1 | Claude 4.5 | Winner |
|---|---|---|---|
| SWE-bench Verified | 76.3% | 77.2% | Claude (+0.9%) |
| AIME 2025 (Math) | 94.0% | Not disclosed | GPT-5.1 (verified) |
| Adaptive Reasoning | Yes | No | GPT-5.1 |
| Ecosystem | Extensive | Limited | GPT-5.1 |
| Long-Session Focus | Not disclosed | 30+ hours | Claude |
Choose GPT-5.1 if: You value ecosystem integrations, adaptive speed, and balanced performance Choose Claude 4.5 if: Raw coding accuracy and long-session reliability are critical
GPT-5.1 vs Gemini 3 Pro
| Metric | GPT-5.1 | Gemini 3 Pro | Winner |
|---|---|---|---|
| Overall Benchmarks | Strong | 19/20 wins | Gemini 3 |
| SWE-bench Verified | 76.3% | Not disclosed | GPT-5.1 (verified) |
| Context Window | 400K tokens | 1M tokens | Gemini 3 |
| Multimodal | Image only | Audio, video, screen | Gemini 3 |
| Ecosystem | Extensive | Google-focused | GPT-5.1 |
Choose GPT-5.1 if: You need OpenAI's ecosystem and proven coding benchmarks Choose Gemini 3 Pro if: Multimodal tasks, massive context, or speed are priorities
Source: TechRadar, The Algorithmic Bridge, comparative testing November 2025
How to Access GPT-5.1
For Developers (API Access)
- Visit platform.openai.com
- Generate API key
- Use model identifier:
gpt-5.1orgpt-5.1-codex-max
Example API call:
import openai
response = openai.ChatCompletion.create(
model="gpt-5.1",
messages=[
{"role": "user", "content": "Refactor this React component to use hooks"}
],
reasoning_effort="adaptive" # New parameter for GPT-5.1
)
For Non-Developers
- ChatGPT interface: chat.openai.com (select GPT-5.1 from model dropdown)
- ChatGPT Plus/Pro subscription: $20-60/month for higher limits
Use Case Recommendations
✅ Best Use Cases for GPT-5.1:
- General Business Workflows - Balanced performance across diverse tasks
- Teams on OpenAI Ecosystem - Already using ChatGPT, plugins, or integrations
- Cost-Sensitive Projects - Adaptive reasoning reduces token costs on simple tasks
- Multi-Step Reasoning - Complex planning requiring deep thinking
- Mathematical Problems - 94% on AIME 2025 (near-human expert)
❌ Not Ideal For:
- Highest Coding Accuracy - Claude 4.5 edges ahead on SWE-bench
- Multimodal Tasks - Gemini 3 Pro dominates on audio/video/screen understanding
- Massive Context - 400K tokens vs Gemini 3's 1M tokens
- Budget-Conscious Exploration - No free tier (unlike Gemini 3)
The Token Efficiency Advantage
GPT-5.1-Codex-Max Real-World Performance
On SWE-bench Verified with 'medium' reasoning effort:
| Model | Score | Thinking Tokens Used | Efficiency |
|---|---|---|---|
| GPT-5.1-Codex-Max | Better than GPT-5.1-Codex | 30% fewer | Best |
| GPT-5.1-Codex | Baseline | Baseline | Good |
What this means:
- Same or better results with 30% cost reduction
- Faster response times on simple coding tasks
- Only uses deep reasoning when truly needed
Source: OpenAI, "Building more with GPT-5.1-Codex-Max," November 2025
Real-World Cost Estimate
Scenario: Startup building a code review tool
Assumptions:
- 100,000 API calls per month
- Average input: 2,000 tokens (code + context)
- Average output: 1,000 tokens (suggestions)
- Using GPT-5.1-Codex-Max with adaptive reasoning
Estimated monthly cost (based on GPT-4o pricing as reference):
- Input: 100K × 2K tokens = 200M tokens → $1,000-1,600
- Output: 100K × 1K tokens = 100M tokens → $2,000-3,000
- Total: $3,000-4,600/month
With 30% token efficiency vs GPT-5.1-Codex:
- New total: $2,100-3,220/month
- Savings: $900-1,380/month
What's Next: GPT-5.2 and Beyond
Based on OpenAI's historical release patterns (minor updates every 2-4 months):
GPT-5.2 ETA: Q1 2026 (January-March 2026)
Predicted improvements:
- Further token efficiency gains (35-40% reduction)
- Native audio understanding (matching Gemini 3)
- Improved long-context performance (500K tokens)
- Enhanced agentic capabilities
Data Sources & Verification
Primary Sources:
- OpenAI Official System Card: "GPT-5.1 Instant and GPT-5.1 Thinking System Card Addendum"
- OpenAI: "GPT-5.1: A smarter, more conversational ChatGPT" (November 2025)
- OpenAI: "Building more with GPT-5.1-Codex-Max" (November 2025)
- Axis Intelligence: "GPT-5.1: Technical Analysis, Benchmarks, and Performance Comparison" (November 2025)
- Medium (Barnacle Goose): "How GPT-5.1 compares to GPT-5" (November 19, 2025)
- artificialanalysis.ai: LLM Intelligence Rankings (November 19, 2025)
Benchmark Verification:
- SWE-bench Verified: Official leaderboard at swe-bench.github.io
- AIME 2025: Verified via OpenAI System Card
- LiveCodeBench: Independent benchmark platform
- Cline's Diff Editing: Community-verified benchmark
Last Updated: November 26, 2025
Disclaimer: Model performance varies by task complexity and prompting strategy. Pricing estimates are based on historical patterns and may not reflect actual GPT-5.1 costs. Always verify with OpenAI's official pricing page.