LLMWise/Comparisons/Claude Haiku 4.5 vs GPT-5.2
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Claude Haiku 4.5 vs GPT-5.2: When Is Fast and Cheap Good Enough?

Not every task needs a frontier model. We compare Anthropic's ultra-fast budget option against OpenAI's flagship to help you decide when to splurge and when to save. Try both in LLMWise Compare mode.

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Claude Haiku 4.5
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Tie
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GPT-5.2
Head-to-head by dimension
DimensionClaude Haiku 4.5GPT-5.2Edge
SpeedClaude Haiku 4.5 is blazing fast, with sub-100ms time-to-first-token and extremely high throughput, making it one of the fastest models available from any provider.GPT-5.2 is reasonably quick for a frontier model but is significantly slower than Haiku, particularly on shorter prompts where Haiku's speed advantage is most pronounced.
CostClaude Haiku 4.5 is priced for volume, costing a small fraction of what frontier models charge per token. It is ideal for applications processing millions of requests.GPT-5.2 is 10-20x more expensive per token than Haiku. The cost difference makes Haiku the obvious choice for any task where it delivers acceptable quality.
CodingClaude Haiku 4.5 handles straightforward coding tasks like boilerplate generation, simple scripts, and code formatting surprisingly well for its size and speed.GPT-5.2 is significantly stronger at complex coding tasks, multi-file refactors, and architectural decisions that require deep understanding of the codebase.
Creative WritingClaude Haiku 4.5 can produce coherent short-form content but lacks the depth, creativity, and tonal range that frontier models bring to longer creative pieces.GPT-5.2 is dramatically better at creative writing, producing richer, more engaging content with natural variation in style and structure.
AnalysisClaude Haiku 4.5 is good at straightforward extraction, classification, and summarization tasks but struggles with nuanced analysis that requires deep reasoning.GPT-5.2 provides much deeper analysis with better handling of ambiguity, multiple perspectives, and complex multi-step reasoning chains.
Context HandlingClaude Haiku 4.5 supports a generous context window and maintains solid recall for its tier, though it cannot match frontier models on needle-in-a-haystack retrieval.GPT-5.2 handles large contexts with better information retrieval and less degradation as input length grows, making it more reliable for document-heavy tasks.
When to ChooseChoose Haiku for high-volume, latency-sensitive tasks: classification, routing, extraction, formatting, simple Q&A, and any pipeline where speed and cost matter more than peak quality.Choose GPT-5.2 for tasks where output quality directly impacts the end user: creative content, complex problem-solving, detailed analysis, and customer-facing interactions.tie
Verdict

This is not really a competition between equals. Claude Haiku 4.5 and GPT-5.2 serve different roles. Haiku is the workhorse for high-volume, cost-sensitive tasks where speed matters most. GPT-5.2 is the specialist for quality-critical work. The smartest approach is to use both: route simple tasks to Haiku and escalate complex ones to GPT-5.2. LLMWise makes this routing trivial.

Use LLMWise Compare mode to test both models on your own prompts in one API call.

Common questions

Can Claude Haiku 4.5 really replace GPT-5.2 for some tasks?
Absolutely. For classification, extraction, formatting, simple summarization, and routing decisions, Haiku delivers comparable results at a tiny fraction of the cost and latency. The key is knowing which tasks need frontier quality and which do not.
What is the best way to use both models together?
Use Claude Haiku 4.5 as your default for high-volume requests, then route complex queries to GPT-5.2 based on task type or difficulty. LLMWise's Auto mode can handle this routing automatically based on prompt analysis.
How can I compare them on my own prompts?
LLMWise Compare mode lets you send the same prompt to Claude Haiku 4.5 and GPT-5.2 simultaneously. The side-by-side view with latency and cost metrics makes it immediately clear which tasks benefit from the premium model and which run perfectly well on Haiku.

Try it yourself

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