Why did GPT-4 Turbo get worse at coding

You're not imagining it — GPT-4 Turbo really did get worse at coding tasks between late 2023 and mid-2024. Developers noticed the drop immediately: messier code structure, more hallucinated functions, incomplete solution

Why did GPT-4 Turbo get worse at coding

You're not imagining it — GPT-4 Turbo really did get worse at coding tasks between late 2023 and mid-2024. Developers noticed the drop immediately: messier code structure, more hallucinated functions, incomplete solutions that once worked perfectly.

What's actually happening

OpenAI updated the GPT-4 Turbo model multiple times throughout 2024, and several of these updates reduced coding performance. The model snapshot you're using today (`gpt-4-turbo-2024-04-09`) behaves differently than the original `gpt-4-1106-preview` release from November 2023.

Here's what changed. OpenAI prioritised reducing costs and increasing speed with each update. The `gpt-4-turbo-2024-04-09` version runs faster and costs less per token than earlier snapshots, but it also produces shorter, less thorough responses. When coding, this manifests as incomplete error handling, missing edge cases, and less verbose comments explaining the logic.

The knowledge cutoff also matters. GPT-4 Turbo's training data cuts off in April 2023, meaning it doesn't know about library updates, framework changes or new syntax introduced after that date. If you're asking it to work with recent versions of React, TypeScript or Python packages, it'll confidently generate outdated code patterns.

Temperature and top_p settings also shifted between versions. Even if you didn't change your API parameters, the same temperature value produces different output randomness across model snapshots. This affects code generation directly — higher effective randomness means more creative but less reliable syntax.

How to fix it

1. Switch to GPT-4o for coding tasks

GPT-4o (`gpt-4o-2024-08-06` or later) consistently outperforms GPT-4 Turbo on programming benchmarks. Go to your API dashboard or ChatGPT settings and explicitly select GPT-4o. In the API, change your model parameter from `gpt-4-turbo` to `gpt-4o`. You'll see immediate improvements in code structure and accuracy.

2. Pin an older GPT-4 Turbo snapshot if you need it

If your workflow depends on GPT-4 Turbo behaviour from late 2023, specify `gpt-4-1106-preview` directly in your API calls instead of using the rolling `gpt-4-turbo` alias. This locks you to November 2023 performance characteristics. Note that OpenAI will deprecate old snapshots eventually — check platform.openai.com/docs/deprecations for sunset dates.

3. Adjust your temperature down to 0.3 or lower

Coding tasks need deterministic output. Set `temperature: 0.3` or even `temperature: 0` in your API requests. In ChatGPT, you can't control temperature directly, but you can say "use minimal creativity" or "generate deterministic code" in your prompt. This reduces random variations in syntax.

4. Make your prompts more explicit about versions

Instead of "write a React component", specify "write a React 18.2 component using functional syntax and hooks". Instead of "fix this Python code", write "fix this Python 3.11 code without using deprecated methods". The model performs better when you constrain the solution space with exact version numbers and style requirements.

5. Compare outputs across models

Before committing code, test the same prompt against both GPT-4 Turbo and GPT-4o. If you're seeing quality differences between what worked last month and today, you might be hitting model behaviour changes from an undocumented update. Document which snapshot produced which output.

If that doesn't work

If GPT-4o still underperforms for your specific coding use case, you're hitting model capability limits rather than configuration issues. Send feedback through platform.openai.com/account/feedback with specific examples: the prompt you used, the output you got, and the output you expected. Include your model version, temperature settings and any custom instructions.

For business-critical applications experiencing sudden quality drops, contact OpenAI support through the platform help widget. Include your organisation ID, the exact API model string you're calling, and examples of the degraded output with timestamps. Response times average 2-4 business days.

Questions people actually ask

Q: Will GPT-4 Turbo get better again or is this permanent?

A: OpenAI won't roll back model changes. The current GPT-4 Turbo snapshot is final. Future improvements go into new models like GPT-4o or whatever comes next. If you need better coding performance today, switch models rather than waiting for updates.

Q: Why does the free ChatGPT version give worse code than it used to?

A: Free ChatGPT now uses GPT-4o mini by default, which is faster but less capable than the GPT-4 you might have accessed during trials. Upgrade to Plus for consistent GPT-4o access, or check if you're hitting usage caps that switch you to older models.

Q: Can I still access the original GPT-4 for coding?

A: Yes — use `gpt-4-0613` in API calls. It's slower and costs more, but it maintains the reasoning depth from the June 2023 release. ChatGPT Plus users get original GPT-4 by selecting "GPT-4" instead of "GPT-4 Turbo" in the model dropdown, though availability varies.

What to remember

  • GPT-4 Turbo sacrificed some coding quality for speed and cost in 2024 updates
  • GPT-4o now outperforms GPT-4 Turbo on most programming tasks
  • Pin specific model snapshots in API calls if you need consistent behaviour
  • Lower your temperature to 0.3 or below for deterministic code generation
  • Specify exact library versions and syntax preferences in your prompts

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*openai-support.com is an independent resource, not affiliated with OpenAI Inc.*

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