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ChatGPT-4 vs ChatGPT-5 Comparison (August 2025)
GPT-4 vs GPT-5 — Side-by-Side Comparison
Concise comparison with concrete examples and presentation-ready visuals. Use Print → Save as PDF for a handout.
Feature
GPT-4
GPT-5
Concrete Example
Context Window
8K–32K tokens (~6–25k words)
May lose early document details on long inputs.
Up to ~200K tokens (~150k words)
Can keep coherence across very long documents.
GPT-4 can summarize a 50‑page report but may miss early sections; GPT-5 can summarize a 200‑page book and cross-reference Chapter 2 in Chapter 18.
Reasoning Depth
Good at 3–5 step reasoning; struggles with very long chains.
Handles 10+ reasoning steps more reliably.
In a multi-variable economic model, GPT-4 may lose track after 3–4 interacting constraints; GPT-5 can keep track of all constraints and provide consistent conclusions.
Factual Accuracy
Moderate factual accuracy; higher hallucination rate on complex queries.
Lower error rate with more internal cross-checking and uncertainty flags.
GPT-4 might confuse dates of related historical events; GPT-5 is likelier to indicate uncertainty and suggest checking reputable sources.
Multimodality
Limited image input in many deployments; weaker image reasoning.
Native text+image reasoning with stronger visual detail interpretation.
Given a historical map photo, GPT-4 may describe it generally; GPT-5 can identify era, region, and cartographic style with greater confidence.
Language Fluency
Strong for high-resource languages; weaker in low-resource or mixed-language prompts.
Better code-switching and low-resource language fluency.
An Arabic question with embedded English technical terms may be mistranslated by GPT-4; GPT-5 preserves nuanced meaning across both languages.
Adaptation to Tone
Good at matching tone but sometimes formulaic.
More nuanced adaptation to audience and editorial style guides.
For an op-ed submission, GPT-4 may produce a generic voice; GPT-5 can mirror the journal's style and target readership more precisely.
Creativity
Capable of original creative outputs but may repeat patterns.
More coherent creativity across long-form narratives.
In a 10‑chapter fictional outline, GPT-4 might drift in character traits; GPT-5 maintains consistent personalities and plot threads.
Speed
Slower with very large inputs and complex tasks.
Optimized for long prompts; often faster end-to-end on large workloads.
A 30K-word analysis may take noticeably longer on GPT-4; GPT-5 typically returns a complete cross-referenced result faster.
Limitations
More prone to hallucinations; loses track with extreme context lengths.
Still hallucinates on some queries but less often; can sometimes over-confidently state subtle errors.
Both models can produce incorrect citations if not connected to live sources; GPT-5 will more often include uncertainty markers and recommend verification.
Sources: Based on model release notes, developer documentation, and empirical evaluations. If you want, I can add an annotated reference list (papers, blog posts, benchmarks) directly into this page.