My take
Why I use GPT-4
GPT-4 is the model I default to when I don't have benchmark evidence pointing me elsewhere. It reasons reliably, follows instructions, handles vision, and integrates with tool calling - a strong all-rounder.
Want the broader stack philosophy? Read about how Sri picks tools or browse engineering insights.
Honest assessment
Strengths & tradeoffs
No tool is perfect. Here's what shines and what to watch for.
Strengths
- Strong reasoning and instruction following
- Native multimodal (text + image + audio)
- Reliable tool/function calling
- Mature ecosystem of integrations
- Predictable behavior across releases
Tradeoffs (honestly)
- Premium pricing relative to small open models
- Knowledge cutoff requires retrieval augmentation
- Subject to OpenAI rate limits and policy
Fit assessment
When to reach for GPT-4
Pick the right tool for the job.
Best fits
Multi-step agent workflows
Document understanding with vision
Code generation and review
Customer support copilots
Not ideal for
Bulk classification where small models suffice
On-device or air-gapped deployments
Common use cases
Resources
Learn more
Curated official docs, tutorials, and writing on GPT-4.
Services
Where I apply GPT-4
Engagements where this technology shows up regularly.
Stack
Pairs well with GPT-4
Tools and platforms I commonly combine with this one.
AI & ML
More in this category
Model providers, frameworks, and stores that power my AI work.
Need help with GPT-4?
Whether you're starting fresh or optimizing an existing implementation, I can help you get the most out of this technology. Read more in insights or get in touch.