OpenAI o3 vs GPT-4 (4.0): A No-Nonsense Comparison
Bottom line up-front: OpenAI’s o3 vs GPT-4 (4.0)
OpenAI’s o3 (April 2025) is a brand-new “reasoning” model with a 200 K-token context window, a fresher May 2024 knowledge cut-off, native vision I/O, adjustable reasoning modes, and lower per-token prices than the original GPT-4 (“4.0”) from March 2023. GPT-4 still wins on mature benchmarks and instruction-following polish, but o3’s vast context, newer data, multimodal workflow and cheaper pricing make it the more attractive choice when you need big context or integrated image reasoning. Below is the fact-checked comparison.
1 · Core Specs at a Glance
| Feature | o3 | GPT-4 (4.0) |
|---|---|---|
| First release | 16 Apr 2025 | 14 Mar 2023 |
| Knowledge cut-off | 31 May 2024 | Sept 2021 |
| Context window | 200 K tokens | 8 K (default) / 32 K Turbo |
| Vision I/O | Native “think-with-images” pipeline | Only via GPT-4o/Turbo |
| Price (per 1 M tokens) | Input $10 / Output $40 | Input $30 / Output $60 |
| Reasoning modes | Low · Medium · High | Single mode |
| Fine-tuning | Not yet public | Public preview since late 2024 |
2 · Performance Benchmarks
2.1 Reasoning (ARC-AGI)
Independent ARC-Prize tests put o3-medium at 53 % on ARC-AGI-1—state-of-the-art for a public model—while GPT-4 (4.0) wasn’t formally run on that suite.
2.2 STEM & Coding
OpenAI cites o3’s 87.5 % MathVista and 69 % SWE-Bench pass rates—metrics GPT-4 (text-only) doesn’t publish.
2.3 Early Third-Party Checks
Epoch and TechCrunch saw production o3 scoring ~10 % on FrontierMath—below OpenAI’s private demos—highlighting marketing vs shipped gaps.
3 · Practical Differences You’ll Feel
- Latency & Throughput: o3’s three reasoning levels trade off speed vs accuracy; GPT-4 is slower but more consistent.
- Instruction-Following: Some testers report o3 occasionally “drifts” from strict formats, while GPT-4 classic stays on script.
- Multimodal: o3 natively handles images; GPT-4 needs the o/Turbo upgrade.
- Rate Limits: o3 has higher caps for Plus/Pro/API users than GPT-4 classic.
4 · Cost Reality Check
A 25 K-token o3 prompt+answer costs ~$0.125 vs $0.25 on GPT-4 classic—dramatic savings for long-context tasks.
5 · Limitations & Open Questions
- Fine-tuning gap: GPT-4 supports preview fine-tuning; o3 does not yet.
- Benchmark variance: Public o3 underperforms earlier “preview” demos.
- Instruction drift: Occasional formatting slips with o3 vs GPT-4.
- Latency spikes: o3-high can time-out on long prompts.
6 · When to Pick Which
| Use Case | Better Pick | Why |
|---|---|---|
| Long doc analysis | o3 | 200 K context + cheaper |
| Code review | GPT-4 (4.0) | Mature instruction-following |
| Image troubleshooting | o3 | Native vision reasoning |
| Strict guardrails | GPT-4 (4.0) | Proven safety record |
| Budget summary | o3 | ~⅓ cost of GPT-4 |
Key Takeaways
• Bigger window, fresher data, lower cost: o3 is built for huge contexts and multimodal.
• Benchmark crown remains with GPT-4 classic on MMLU/HellaSwag/HumanEval.
• For long docs, STEM tasks, or vision workflows—o3 is your pick. For rock-solid general AI—GPT-4 wins.
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