How Accurate Is GPT-3.5? ChatGPT's Older Model Reviewed

AI Summary: GPT-3.5 was the model behind ChatGPT's viral launch in late 2022, achieving roughly 70% on MMLU benchmarks. It performs well for general writing, simple Q&A, and customer service tasks, but falls behind GPT-4 and GPT-4o on complex reasoning, math, and accuracy-critical tasks. It remains useful and cost-effective for many simple applications. Summary created using 99helpers AI Web Summarizer

GPT-3.5 is the model that put AI assistants into the mainstream consciousness. When ChatGPT launched in November 2022, it ran on GPT-3.5 Turbo and quickly accumulated 100 million users in its first two months — a testament to just how capable even this earlier model was compared to what most people expected AI to be able to do. But in a world now defined by GPT-4o, o1, and competing models from Anthropic and Google, how accurate is GPT-3.5 in 2026, and is it still worth using?

GPT-3.5 Benchmark Performance

On the MMLU (Massive Multitask Language Understanding) benchmark, GPT-3.5 scores approximately 70%, compared to GPT-4's 86.4% and GPT-4o's similar performance level. This roughly 16-point gap reflects real-world accuracy differences across knowledge-intensive tasks. For the bar exam, GPT-3.5 scored around the 10th percentile of human test-takers — a result that sounds bad but was remarkable at the time, though it pales against GPT-4's 90th percentile performance.

On coding benchmarks, GPT-3.5 achieves approximately 48-67% on HumanEval, depending on the exact variant tested and the evaluation methodology. This is meaningfully below GPT-4o's 85%+ performance and reflects real limitations in code generation quality, particularly for complex algorithms and edge cases.

On mathematical reasoning benchmarks, GPT-3.5 scores significantly lower than GPT-4 variants, particularly on problems requiring multiple reasoning steps. Simple algebra and arithmetic are handled reasonably, but complex math problems expose the gap between GPT-3.5 and newer models clearly.

Where GPT-3.5 Still Performs Well

Despite its limitations relative to newer models, GPT-3.5 remains genuinely capable for many practical tasks. General writing assistance — drafting emails, summarizing text, basic content generation, and editing for clarity and grammar — is handled well. The model's language quality is high even if its factual reasoning is weaker than GPT-4.

Simple Q&A tasks, FAQ-style customer support, basic explanations of common concepts, and light coding assistance for straightforward problems all work adequately with GPT-3.5. For use cases where the primary requirement is language fluency rather than factual precision or complex reasoning, GPT-3.5 often provides sufficient quality at a lower cost.

The cost advantage is meaningful: GPT-3.5 Turbo API access is significantly cheaper per token than GPT-4o. For high-volume applications where accuracy requirements are modest and cost is a constraint, GPT-3.5 remains a rational choice.

Where GPT-3.5 Falls Short

GPT-3.5's limitations become apparent for tasks requiring complex reasoning, accurate factual responses, and nuanced analysis. Multi-step logical problems, complex coding tasks, detailed medical or legal explanations, and anything requiring accurate citation or data retrieval are areas where the gap between GPT-3.5 and GPT-4o is significant and practically meaningful.

Hallucination rates are also higher in GPT-3.5 than in GPT-4. The model is more likely to fabricate citations, invent statistics, and provide confident but wrong answers to questions at the edges of its knowledge. For accuracy-critical applications, this higher hallucination rate is a real concern.

Verdict

GPT-3.5 remains a capable model for simple language tasks and cost-sensitive applications but should be upgraded to GPT-4o for any work where accuracy, complex reasoning, or factual precision matters.

Trust Rating: GPT-3.5 6/10 for general tasks, 3/10 for complex reasoning or accuracy-critical work

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Frequently Asked Questions

Is GPT-3.5 still available?

Yes, GPT-3.5 Turbo remains available via OpenAI's API. It is no longer the default model in ChatGPT (which defaults to GPT-4o), but it is still accessible through the API for developers who prefer its lower cost for applicable use cases.

How much less accurate is GPT-3.5 than GPT-4?

The accuracy gap is significant on complex tasks. GPT-4 scores roughly 16 percentage points higher on MMLU, performs dramatically better on complex reasoning, and has meaningfully lower hallucination rates. For simple language tasks, the gap is smaller. For medical, legal, technical, or complex analytical tasks, always use GPT-4 or newer.

When does it make sense to use GPT-3.5 instead of GPT-4?

GPT-3.5 makes sense when: the task is simple language work (summarization, basic Q&A, email drafting), cost per token matters significantly, you're processing very high volumes, and the accuracy difference for your specific use case is not meaningful. For most accuracy-sensitive applications, the modest cost difference is worth paying for GPT-4o quality.