AI Coding Assistant Benchmark 2025: The Great Convergence
Based on rigorous evaluation of 65+ tests across 18 AI coding assistants and 5 major models. Data collected August 1st, 2025.
🏆 TL;DR: The Winners
Claude 4 Sonnet remains king, but the gap is shrinking fast. GitHub Copilot surprisingly topped the charts, while Qwen 3 Coder emerged as the dark horse challenger.
📊 Overall Rankings by Model
Claude 4 Sonnet: The Reigning Champion
| Rank | Tool | Score | Notes |
|---|---|---|---|
| 🥇 1 | GitHub Copilot | 26,574 | Massive improvement from previous versions |
| 🥈 2 | Cline | 26,214 | Margin of error difference |
| 🥉 3 | RooCode | 26,014 | Basically identical performance |
| 4 | Trey | 26,214 | Klein family convergence |
| 5 | Claude Code | ~26,000 | Surprisingly dropped from #1 |
| 6 | Windsurf | 25,800 | Solid performer |
| 7 | AMP Code | 25,600 | Decent but not exceptional |
Key Insight: Scores converged to 25,000-26,574 range. Only 7% difference from top to bottom.
o3: The Reasoning Powerhouse (But…)
| Rank | Tool | Score | Notes |
|---|---|---|---|
| 🥇 1 | Windsurf | 23,500 | Incredible tuning for o3 |
| 🥈 2 | Aider | 21,260 | Low cost, purpose-built |
| 🥉 3 | Cursor | 21,000 | Strong o3 integration |
| - | Most others | 0 | Failed to complete evals |
Reality Check: o3 is excellent at coding but terrible at driving agents. Most tools couldn’t even complete the benchmark.
Qwen 3 Coder: The Surprise Winner
| Rank | Tool | Score | Notes |
|---|---|---|---|
| 🥇 1 | Qwen Code | 25,898 | Direct Alibaba API = best experience |
| 🥈 2 | Trey | 25,214 | Excellent agent performance |
| 🥉 3 | Windsurf | 24,800 | Strong cross-model performer |
| 4 | RooCode | 25,610 | Klein family consistency |
| 5 | Cline | 25,610 | Basically identical to RooCode |
Pro Tip: Use Alibaba’s direct API. Third-party providers degrade performance significantly.
Gemini 2.5 Pro: The Lazy Genius
| Rank | Tool | Score | Notes |
|---|---|---|---|
| 🥇 1 | Aider | 20,680 | Works well with reasoning models |
| 🥈 2 | GitHub Copilot | 20,380 | Surprisingly good integration |
| 🥉 3 | RooCode | 19,516 | Needs specialized prompting |
Reality Check: Gemini is lazy and needs custom prompting. Many tools couldn’t handle it at all.
💡 Key Insights from the Trenches
The Great Convergence
“The scores have converged around this 25-26,000 point range. It’s like less than 2-3% difference between some of these.”
What This Means: The AI coding assistant race has matured. Tool choice now depends more on UX, cost, and specific workflow needs than raw performance.
Model Matters Most
“Sonnet 4—everybody has tuned to that, and the scores are starting to converge because everyone is catching up.”
What This Means: The underlying model is more important than the wrapper. But harness quality still matters significantly.
Prompting is Everything
“Gemini 2.5 Pro is kind of lazy, as is o3. A lot of it is the harness because there are some AI coding assistants that will do well.”
What This Means: The same model can perform drastically differently depending on how the tool prompts and controls it.
🔍 Model-Specific Analysis
Claude 4 Sonnet: The Reliable Choice
Strengths:
- ✅ Vision capabilities
- ✅ Excellent prompt caching (lower API costs)
- ✅ Consistent performance across tools
- ✅ Best overall ecosystem support
Weaknesses:
- ❌ Taking more shortcuts recently
- ❌ Needs specific prompting to avoid lazy behavior
Qwen 3 Coder: The Technical Specialist
Strengths:
- ✅ Exceptional coding performance (matches Claude 4)
- ✅ Larger context window than Claude
- ✅ Great with complex technical tasks
Weaknesses:
- ❌ Limited tool ecosystem
- ❌ Expensive without prompt caching
- ❌ Can be “tool call happy”
o3: The Reasoning Beast
Strengths:
- ✅ Incredible reasoning capabilities
- ✅ Excellent for complex logic
- ✅ Low API costs
Weaknesses:
- ❌ Poor at tool calls and agent control
- ❌ Most tools can’t handle it properly
- ❌ Very limited ecosystem support
🏅 Tool Spotlight: Unexpected Winners
GitHub Copilot: The Comeback Kid
“GitHub Copilot wins, which is nuts to me… They have really made the thing solid now. I’m impressed with the turnaround.”
Why It Won:
- Massive improvements to the underlying system
- Excellent Claude 4 Sonnet integration
- Stable, reliable performance
Windsurf: The Dark Horse
“Windsurf, whatever they’ve done, they have tuned it incredibly well with o3.”
Why It’s Special:
- Exceptional model-specific tuning
- Strong performance across multiple models
- Surprising o3 optimization
Aider: The Efficiency Expert
“The cost is so low… Aider’s cost is significantly lower than most of the other ones.”
Why It Matters:
- Purpose-built for reasoning models
- Extremely cost-effective
- Works well with o3 and Gemini 2.5 Pro
⚠️ Reality Check: What the Scores Don’t Tell You
Beyond Performance Metrics
“This is measuring like one dimension, so I’ll be very curious to see what everyone’s feedback is on this.”
Consider These Factors:
- Speed: Some tools are significantly faster
- Cost: API usage varies dramatically
- UX: Developer experience matters
- Features: Vision, model selection, customization
- Reliability: Some tools crash or hang
Model-Specific Quirks
- Zed: Burns tokens like crazy, runs forever
- Qwen 3 Coder: Tool call happy, needs different prompting
- Claude 4: Taking shortcuts, needs explicit instruction
- o3: Excellent reasoning but poor agent control
🛠️ Practical Recommendations
For Most Developers
Top 3 Picks:
- GitHub Copilot (Claude 4 Sonnet) - Most reliable
- RooCode (Claude 4 Sonnet) - Advanced features, great customization
- Cline (Claude 4 Sonnet) - Solid CLI option
For Budget-Conscious Users
Top 2 Picks:
- Aider (o3 or Gemini 2.5 Pro) - Incredibly cost-effective
- Qwen Code (Qwen 3 Coder via Alibaba) - Great performance/price ratio
For Bleeding Edge
Top 2 Picks:
- Qwen Code (Qwen 3 Coder) - Matches Claude 4 performance
- Windsurf (o3) - Exceptional reasoning integration
📈 Looking Forward
The August 2025 Landscape
Current State:
- Performance convergence makes tool choice more about UX
- Model ecosystem diversity is increasing
- Cost optimization becoming critical
What’s Next:
- Better o3 integrations coming
- Qwen 3 Coder ecosystem growth
- Continued Claude 4 optimization
Bottom Line: The AI coding assistant wars have evolved from performance battles to ecosystem and UX competition. Choose based on your specific needs, not just benchmark scores.
📋 Complete Results Table
Claude 4 Sonnet Results
GitHub Copilot 26,574 ████████████████████ 100%
Cline 26,214 ███████████████████▌ 99%
RooCode 26,014 ███████████████████▎ 98%
Trey 26,214 ███████████████████▌ 99%
Claude Code ~26,000 ███████████████████▎ 98%
Windsurf 25,800 ███████████████████ 97%
AMP Code 25,600 ██████████████████▌ 96%
Kilo 25,400 ██████████████████ 96%
Augment 25,200 █████████████████▌ 95%
Zed 24,800 █████████████████ 93%
Aider 24,600 ████████████████▌ 93%
Cross-Model Performance Heatmap
Claude4 Qwen3 o3 Gemini Kimi
GitHub Copilot 26,574 N/A FAIL 20,380 N/A
Windsurf 25,800 24,800 23,500 FAIL N/A
RooCode 26,014 25,610 FAIL 19,516 25,610
Cline 26,214 25,610 FAIL 19,400 25,610
Aider 24,600 N/A 21,260 20,680 N/A
Cursor 25,000 N/A 21,000 18,800 N/A
Evaluation methodology: 40% unit tests, 30% static analysis, 20% LLM judge, 10% load testing. All scores represent averages across multiple runs with variance accounting.
Related: AI Safety Considerations • Economic Impact • Performance Optimization