Claude Opus 4.7 for data extraction
Claude Opus 4.7 is the #2 pick 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
- #2 of 5
- Context
- 500K tokens
- Output / 1M
- Pricing not published
- Released
- Feb 2026
Why Claude Opus 4.7 fits this task
Three things about Claude Opus 4.7 that map directly onto what this task rewards: Excellent long-context recall and citation discipline. Beyond the task-specific fit, Claude Opus 4.7 also brings strongest published swe-bench verified scores in agent settings and best-in-class writing quality and voice control, 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 Claude Opus 4.7 scores on each axis
Where Claude Opus 4.7 costs you: premium pricing relative to gpt-5 line. 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
- Strongest published SWE-bench Verified scores in agent settings
- Best-in-class writing quality and voice control
- Excellent long-context recall and citation discipline
- Robust tool-use across long agent loops
Tracked weaknesses
- Premium pricing relative to GPT-5 line
- More conservative refusal patterns on edge content than peers
When to pick something else
If you can pay slightly more or accept slightly different tradeoffs, GPT-5.5 from OpenAI ranks one position higher and tends to win on the hardest cases. OpenAI's mid-cycle GPT-5 refresh, improved reasoning, tool use, and multimodal grounding over the 2025 launch.
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Other models for data extraction
- GPT-5.5 for data extraction
OpenAI's mid-cycle GPT-5 refresh, improved reasoning, tool use, and multimodal grounding over the 2025 launch.
Read guide - Claude Sonnet 4.6 for data extraction
Anthropic's mid-tier 4.6 release, the workhorse model behind most production Anthropic deployments.
Read guide - Gemini 3 Pro for data extraction
Google's late-2025 flagship, set new benchmarks on long-context, vision, and reasoning at competitive pricing.
Read guide - GPT-5 for data extraction
OpenAI's unified flagship combining GPT-line breadth with built-in reasoning, replacing both GPT-4o and the o-series for most users.
Read guide
Claude Opus 4.7 for other use cases
Direct comparisons
Frequently asked
Is Claude Opus 4.7 good for data extraction?
Claude Opus 4.7 is ranked #2 on LLMDex's data extraction list. Anthropic's mid-2026 flagship, ahead on SWE-bench, agent reliability, and writing quality.How much does Claude Opus 4.7 cost for data extraction?
Anthropic has not published per-token pricing for Claude Opus 4.7 at the time of writing.What's a cheaper alternative to Claude Opus 4.7 for data extraction?
The next ranked model on this task is Claude Sonnet 4.6. Compare both before committing.When should I NOT use Claude Opus 4.7 for data extraction?
Tracked weakness: Premium pricing relative to GPT-5 line. If that constraint is binding for your workload, the next-ranked model on this task is the safer pick.
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