GPT-5.2 produces the most polished and readable summaries of any LLM, with strong audience adaptation and structured output. Here's how it performs across different summarization scenarios.
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GPT-5.2 is an excellent summarization model that produces the most readable, well-structured summaries among current LLMs. It excels at adjusting summary detail and tone for different audiences, from executive briefs to technical digests. It trails Claude Sonnet 4.5 on raw faithfulness, where Claude's lower hallucination rate makes it the safer choice for legal, medical, or compliance-sensitive documents. Gemini 3 Flash is faster and cheaper for high-volume batch summarization. GPT-5.2 is the top choice when summary readability and polish matter most.
GPT-5.2 consistently produces the most polished, well-written summaries. Its output reads naturally, flows logically, and avoids the stilted phrasing that other models sometimes produce when condensing dense source material.
GPT-5.2 adjusts summary complexity, vocabulary, and emphasis based on the target audience. It can produce an executive brief, a technical digest, and a customer-facing overview from the same source document, each appropriately tailored.
When you need summaries in specific formats, such as bullet points, numbered key takeaways, TLDR plus detailed sections, or JSON, GPT-5.2 follows formatting instructions precisely and consistently.
GPT-5.2 can summarize documents in one language and output the summary in another, or summarize multilingual source material into a single coherent output. This cross-lingual capability is valuable for international teams.
GPT-5.2 occasionally introduces details or emphasis not present in the source material, particularly when summarizing technical or specialized documents. Claude Sonnet 4.5 is more faithful to source content.
For very long documents, Claude Sonnet 4.5's 200K token context window can process more source material in a single pass. GPT-5.2 may require document chunking for the longest inputs, which can reduce summary coherence.
For batch summarization of hundreds or thousands of documents, GPT-5.2's per-token pricing is significantly higher than Gemini 3 Flash, which handles routine summarization tasks adequately at a lower cost.
Specify your target audience and desired summary length explicitly in the prompt to get the most useful output on the first try.
For compliance-sensitive documents, use LLMWise Compare mode to cross-check GPT-5.2 summaries against Claude Sonnet 4.5 for faithfulness.
Use structured output mode to produce JSON-formatted summaries that can be ingested by downstream systems or dashboards.
When summarizing very long documents, break them into logical sections and summarize each, then ask GPT-5.2 to synthesize the section summaries into a final overview.
Include specific instructions about what to prioritize, for example 'focus on financial impact' or 'emphasize timeline and milestones', to get more targeted summaries.
How GPT-5.2 stacks up for summarization workloads based on practical evaluation.
Claude Sonnet 4.5
Compare both models for summarization on LLMWise
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