LLM·Dex
Rank · #5 of 5OpenAIData Extraction

GPT-5 for data extraction

GPT-5 is ranked #5 on LLMDex's llms for data extraction ranking out of 5 models we track for this use case. Below, the specific reasons it slots where it does, and when you should reach for an alternative.

Updated


At a glance

Rank
#5 of 5
Context
400K tokens
Output / 1M
$10.00 / 1M tokens
Released
Aug 2025

Why GPT-5 fits this task

Three things about GPT-5 that map directly onto what this task rewards: Unified model, reasoning routed automatically per query; Excellent tool-use and JSON-mode discipline; Strong agent performance on SWE-bench Verified. Beyond the task-specific fit, GPT-5 also brings unified model, reasoning routed automatically per query and excellent tool-use and json-mode discipline, both of which compound when the workload broadens.

The criteria this task rewards

LLMDex ranks best llms for data extraction on 5 criteria , these are the axes the ranking uses, in priority order:

  • JSON-mode / structured-output reliability
  • Schema adherence under noisy input
  • Handling of optional and nested fields
  • Long-document extraction at full context
  • Cost per document processed

How GPT-5 scores on each axis

Where GPT-5 costs you: reasoning routing means latency is unpredictable per query. For most teams this is acceptable on this workload, the value of the strengths above outweighs the cost. For cost-bound workloads or teams with strict latency budgets, run an eval against the next two ranked models on real data before committing.

Strengths that pay off here

  • Unified model, reasoning routed automatically per query
  • Excellent tool-use and JSON-mode discipline
  • Strong agent performance on SWE-bench Verified
  • Robust safety post-training reduces hallucinations vs. GPT-4 line

Tracked weaknesses

  • Reasoning routing means latency is unpredictable per query
  • Output cost is high relative to mid-tier alternatives

When to pick something else

If you can pay slightly more or accept slightly different tradeoffs, Gemini 3 Pro from Google ranks one position higher and tends to win on the hardest cases. Google's late-2025 flagship, set new benchmarks on long-context, vision, and reasoning at competitive pricing.

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Other models for data extraction

GPT-5 for other use cases

Direct comparisons

Frequently asked

  • Is GPT-5 good for data extraction?
    GPT-5 is ranked #5 on LLMDex's data extraction list. OpenAI's unified flagship combining GPT-line breadth with built-in reasoning, replacing both GPT-4o and the o-series for most users.
  • How much does GPT-5 cost for data extraction?
    GPT-5 costs $1.25 / 1M tokens for input tokens and $10.00 / 1M tokens for output tokens. For data extraction workloads, output costs typically dominate; budget on the higher number.
  • What's a cheaper alternative to GPT-5 for data extraction?
    Look at the full Best LLMs for Data Extraction ranking for cheaper picks at lower ranks.
  • When should I NOT use GPT-5 for data extraction?
    Tracked weakness: Reasoning routing means latency is unpredictable per query. If that constraint is binding for your workload, the next-ranked model on this task is the safer pick.
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