How Does GPT 5.5 Compare to DeepSeek V4?

TL;DR

GPT 5.5 and DeepSeek V4 trade wins rather than producing a clear overall champion: GPT 5.5 scored 82.7% on Agentic Terminal Coding, while DeepSeek V4 Pro reached 61.2% on SimpleBench at a fraction of Opus 4.7’s cost. GPT 5.5 also lacks API access, limiting apples-to-apples testing. Read on for the benchmark caveats, cost considerations, and cybersecurity results behind the comparison.

Transcript

In the last 20 hours in AI, we have gotten two new models that could influence how a billion people use AI. In my mind, GBT 5.5 is OpenAI's allout attempt to keep the AI crown from slipping too anthropic, while today's Deep Seek V4 is China's answer to both. And in the swirl of headlines you are seeing today, you might have missed up to 50 data poi... Read More

Key Insights

• GPT 5.5 is OpenAI's latest model, aiming to maintain its leadership in AI.
• DeepSeek V4 is China's response to global AI competition, featuring open weights.
• GPT 5.5 shows mixed performance, excelling in some benchmarks but lagging in others.
• DeepSeek V4 supports a context length of 1 million tokens, enhancing its utility.
• Performance per dollar is a critical metric, with DeepSeek V4 offering cost efficiency.
• GPT 5.5 lacks API access, limiting external validation of its performance.
• Both models face challenges with hallucination rates and benchmark consistency.
• Compute scarcity is a growing issue, impacting AI development and deployment.

Questions & Answers

Q: How does GPT 5.5 compare with DeepSeek V4?

The available results do not establish one clear winner across every task. GPT 5.5 performs strongly on Agentic Terminal Coding and ARC-AGI 2, while DeepSeek V4 Pro delivers a 61.2% SimpleBench score at an absolute fraction of the cost of Opus 4.7. Direct comparison is limited because GPT 5.5 has no API access.

Q: How well does GPT 5.5 perform on coding benchmarks?

GPT 5.5 trails Opus 4.7 by around 6% and Mythos Preview by almost 20% on Agentic Coding SWE-bench Pro. On Agentic Terminal Coding, however, GPT 5.5 scores 82.7%, narrowly exceeding Mythos Preview’s 82.0%. These conflicting results show why its coding ability cannot be judged from one benchmark.

Q: Why is GPT 5.5 difficult to evaluate independently?

GPT 5.5 has no API access at the time discussed, even though the presenter received early access. Consequently, almost all cited benchmark scores are self-reported by OpenAI, and GPT 5.5 could not be tested on the presenter’s private SimpleBench benchmark.

Q: What does DeepSeek V4 Pro score on SimpleBench?

DeepSeek V4 Pro scores 61.2% on the presenter’s private SimpleBench benchmark. That places it within 1 or 2% of Opus 4.7 at an absolute fraction of the cost. SimpleBench tests common-sense reasoning through tricky spatiotemporal questions.

Q: Why does performance per dollar matter when comparing these AI models?

Benchmark performance can rise when more inference compute is spent, so score alone does not capture efficiency. The comparison therefore emphasizes intelligence per token or per dollar, especially when a model performs well in relevant domains while using fewer tokens. DeepSeek V4 Pro’s SimpleBench result is highlighted because it approaches Opus 4.7 at a fraction of the cost.

Q: How does GPT 5.5 perform on reasoning and knowledge benchmarks?

Without tools, GPT 5.5 is beaten by Opus 4.7, Mythos, and Gemini 3.1 Pro on Humanity’s Last Exam, which combines obscure academic knowledge with advanced reasoning. On the pattern-recognition benchmark ARC-AGI 2, GPT 5.5 beats Claude Opus 4.6 and 4.7 across all settings while achieving higher scores at much lower cost.

Q: How capable is GPT 5.5 at cybersecurity tasks?

The UK AI Security Institute judges GPT 5.5 the strongest-performing model overall on its narrow cyber tasks, though within the margin of error. On an end-to-end 32-step corporate-network attack simulation, GPT 5.5 completes the task in one of 10 attempts, compared with three of 10 for Mythos. The simulation would take an expert 20 hours.

Q: Is GPT 5.5 clearly better than Mythos Preview?

No apples-to-apples comparison is available. GPT 5.5 trails Mythos Preview by almost 20% on SWE-bench Pro but edges it 82.7% to 82.0% on Agentic Terminal Coding. The comparison also concerns GPT 5.5 rather than GPT 5.5 Pro, which the transcript says is coming to the API very soon.

Summary & Key Takeaways

• GPT 5.5 aims to retain OpenAI's AI leadership but shows mixed results across benchmarks. It excels in specific areas like coding and cybersecurity but underperforms in others. The model is not yet available for API access, making independent validation difficult.

• DeepSeek V4, China's latest AI model, offers impressive features like a 1 million token context length and cost efficiency. Despite some limitations in reasoning and coding, it competes strongly against other models, emphasizing long document data curation.

• The AI landscape is marked by compute scarcity, affecting model development and deployment. Performance per dollar is becoming a crucial metric, with DeepSeek V4 demonstrating significant cost efficiency. Both models face challenges in hallucination rates and benchmark consistency.