Best LLM for Data Extraction in 2026
High-volume extraction and classification reward models that are cheap, fast, and reliable with structured output. This list prioritizes affordable, tool-capable models that hold up at scale, so you can process millions of tokens without a flagship price tag.
Recommended models
qwen/qwen-turbo · dashscopevolcengine/doubao-seed-1-6-flash · Volcengineopenai/gpt-6-luna · OpenAIz-ai/glm-4.7-flashx · Zhipugoogle/gemini-2.5-flash-lite · googledeepseek/deepseek-v4-flash-0423 · DeepSeekNeed something more specific?
Open the interactive finder with this scenario pre-filled, then adjust your priorities and required capabilities to fine-tune the shortlist.
Refine in the finderHow to interpret this recommendation
Scoring weights
- Quality
- 16%
- Cost
- 56%
- Speed
- 10%
- Task fit
- 18%
Benchmark reference · 2026-07
Artificial Analysis Intelligence Index
Try your own task
Test shortlisted models on the same input. Compare correctness, consistency and actual usage cost; a larger context window does not guarantee memory or better answers.
What the score can tell you
Match scores combine catalog data, available benchmark references and heuristics. Quality includes release age; speed is an estimate, not measured request latency. Missing benchmarks use a model-family heuristic. These are recommendations, not task-specific test results.
Related questions
Frequently asked questions
How does the Model Finder pick models?+
It scores every non-deprecated model on Ofox across four axes — quality, cost, speed, and fit for your use case — then weights them by the priority you choose. Quality reflects model tier and capabilities, cost uses real per-token pricing, and fit measures whether a model is tuned for your task (coding, vision, long context, and so on).
Is it free? Do I need an account?+
Yes, it's completely free and runs in your browser — no login or API key needed to get recommendations. You only need an Ofox account when you're ready to actually call a model.
Are these real, up-to-date models?+
Every recommendation comes from the live Ofox catalog of 100+ models, refreshed continuously. The pricing and context windows shown are pulled directly from the catalog.
Why doesn't the cheapest model always rank first?+
Unless you pick 'Lowest cost', the finder balances price against quality and capability. A model that costs a little more but is much more capable will often score higher — just like a person would choose.
Can I use the recommended models with my existing code?+
Yes. Every model is available through one OpenAI-, Anthropic-, or Gemini-compatible endpoint. Change the base URL and API key and your existing SDK works unchanged.