Conclusion
GPT-5.5 is the April 2026 benchmark king—Terminal-Bench 82.7%, GDPval 84.9%, CyberGym 81.8%, comprehensively leading Claude Opus 4.7.
But it has a fatal weakness: on the AA-Omniscience hallucination rate test, 86% of questions produce seemingly reasonable but actually wrong answers. Claude Opus 4.7’s hallucination rate on the same test is 36%.
This means: GPT-5.5’s “confident wrong” is 2.4x higher than Claude Opus 4.7. If your workflow cannot tolerate “sounding confidently wrong,” this data matters more than any benchmark.
Test Dimensions
Terminal-Bench 2.0: GPT-5.5 Wins Big
| Metric | GPT-5.5 | Claude Opus 4.7 | Gap |
|---|---|---|---|
| Terminal-Bench 2.0 | 82.7% | 69.4% | +13.3% |
| GDPval (Data Analysis) | 84.9% | 80.3% | +4.6% |
| CyberGym (Security) | 81.8% | 73.1% | +8.7% |
GPT-5.5 (codename “Spud”) is the first truly retrained model since GPT-4.5. OpenAI used 6 “fake releases” to shield resources, and when it struck, it pulled ahead on terminal operations, multi-step Agents, and automation tasks.
AA-Omniscience Hallucination Rate: Claude Opus 4.7 Crushes
The core design of AA-Omniscience testing: ask the model questions it “shouldn’t know the answer to” (made-up events, fictional people), and see if it “confidently fabricates answers.”
- GPT-5.5: 86% hallucination rate—fabricates a reasonable-sounding answer most of the time
- Claude Opus 4.7: 36% hallucination rate—more inclined to say “I don’t know”
This gap isn’t a “small improvement”—it’s a generational difference. For scenarios requiring high reliability (medical, financial, legal), an 86% hallucination rate is unacceptable.
MCP Atlas Tool Invocation Capability
| Model | MCP Atlas Score | Rank |
|---|---|---|
| Claude Opus 4.7 | 79.1% | 1st |
| Gemini 3.1 Pro | 78.2% | 2nd |
| GPT-5.5 | 75.3% | 3rd |
GPT-5.5 ranks last on MCP (Model Context Protocol) tool invocation. Interestingly, analysts note “this isn’t a bug to fix—it’s a battlefield to bypass.” OpenAI’s strategy may be to build a Super App, rebuilding the tool ecosystem within its own walls, making MCP “unnecessary.”
Pricing
| Model | Input Price | Output Price | Relative to GPT-5.5 |
|---|---|---|---|
| GPT-5.5 | $30/1M tokens | $60/1M tokens | Baseline |
| Claude Opus 4.7 | $15/1M tokens | $75/1M tokens | Half input price |
| DeepSeek V4 Pro | $0.14/1M tokens | $0.50/1M tokens | 1/166 |
GPT-5.5’s price is 166x that of DeepSeek V4 Pro. For high-volume invocation scenarios, this gap directly reflects in operational costs.
Selection Guide
Choose GPT-5.5 if:
- Your core need is terminal operations and automation tasks
- You need the strongest multi-step Agent capability
- Your workflow has a “human review” step that can catch hallucinations
- Budget isn’t the primary constraint
Choose Claude Opus 4.7 if:
- You need high-reliability answers (finance, legal, medical)
- Model output directly impacts decisions in your workflow
- You need the best MCP tool invocation capability
- You value “knowing what it doesn’t know”
Hybrid Approach:
- Coding Agent: GPT-5.5 (strong Terminal-Bench) + Claude Opus 4.7 (low hallucination rate, reliable code review)
- Data Analysis: GPT-5.5 (strong GDPval) + human validation
- Daily Assistant: Claude Opus 4.7 (low hallucination rate, safer) + DeepSeek V4 Flash (low-cost fallback)
An Overlooked Truth
The OpenAI vs Anthropic competition has entered a “specialized” era. GPT-5.5 is the ultimate “executor”—terminal operations, multi-step tasks, automation flows, it’s better than you at all of them. But it’s also the ultimate “confident one”—even when wrong, it speaks confidently.
Claude Opus 4.7 is the more “cautious” competitor—it may not be #1 on every benchmark, but its answers are more reliable.
The key question: does your scenario need “execution power” or “reliability”?
If your workflow can tolerate some errors (with review steps, rollback mechanisms), GPT-5.5’s performance advantage is worth considering. If your output directly impacts decisions without a review step, Claude Opus 4.7’s low hallucination rate is better insurance.