The original flagship — still alive, no longer the king.

GPT-4 launched in March 2023 and became the most consequential AI model release in history. Three years later, it's been superseded by GPT-4o, o1, o3, and GPT-5 in OpenAI's lineup — but GPT-4 is still relevant. It powers a massive installed base of production apps, costs less than newer models, and remains competitive on many tasks. If you're running a production system that works on GPT-4, there's no urgent reason to migrate.

Who it's for: Existing GPT-4 production systems, cost-sensitive developers, enterprises with stable integrations, anyone learning the OpenAI API on a budget.

Key features

8K / 32KContext variants

GPT-4 (8K context) and GPT-4-32K (32K context) are still available. The 32K version handles long documents but costs 2x more per token than 8K.

StableProduction-tested reliability

Three years of production use = best-understood model in the industry. Documentation, error patterns, and best practices are well-established.

$30/MCheaper than o-series

GPT-4 API: $30/M output tokens. Compare: GPT-4o ($10/M), o1 ($60/M), o3-mini ($4.40/M). For non-reasoning tasks, GPT-4 is often the cost-vs-quality sweet spot.

ToolsFunction calling + vision

Native function calling, JSON mode, vision input (gpt-4-vision), and the full OpenAI tools ecosystem (Assistants API, fine-tuning, evals).

Fine-tuneCustom training

Still supports fine-tuning (GPT-4 fine-tuning is more stable than 4o fine-tuning, which is still preview). Good for domain-specific models.

The honest take

✓ What works

Battle-tested in production by millions of developers — known failure modes, robust tooling
Cheaper than o1/o3 on most reasoning-light tasks (summarization, classification, extraction, rewriting)
Still beats GPT-4o on certain creative writing and nuanced instruction-following tasks
Best fine-tuning stability in OpenAI's lineup — fewer surprises than 4o fine-tunes
Microsoft Azure OpenAI Service hosts GPT-4 with enterprise compliance (HIPAA, SOC 2, FedRAMP)

✗ What doesn't

Outperformed on benchmarks by GPT-4o (multimodal, faster, cheaper) and o1/o3 (reasoning, math, code)
8K context is limiting in 2026 — Claude (200K), Gemini (2M), and GPT-4.1 (1M) are vastly better for long docs
Slower inference than GPT-4o (3-5x on standard prompts) and 4o-mini (10x faster)
No native multimodal output (image gen) — needs separate DALL-E 3 call
OpenAI has flagged GPT-4 for deprecation — support guarantees ending 2027

Verdict

GPT-4 is the Honda Civic of LLMs — not the fastest, not the flashiest, but reliable, well-understood, and still gets the job done in 2026. If your production system already runs on GPT-4 and works, there's no urgent reason to migrate. For new projects, start with GPT-4o or GPT-4o-mini. For reasoning-heavy work, use o1 or o3. GPT-4 is for legacy stability, not new builds.

💡 Transparency: This review is editorially independent. We never accept payment for positive coverage. Full disclosure.