Jerry Liu说别急着用前沿模型做文档OCR，LlamaParse在表格图表上准确率涨了15%，还能自己搭ParseBench跑评测。
LlamaIndex CEO Jerry Liu称，Gemini 3 Flash是当前原始文档解析最强的前沿模型，但Flash系列涨价3倍，视觉识别能力停滞。GPT-5.5到5.6、Gemini 3.5 Flash到3.6 Flash、Opus 4.8到5的迭代均未提升文档理解基准。混合方案如LlamaParse结合专用VLM与文本引擎，表格和图表准确率提升15%。LlamaParse推出ParseBench评测框架，用户可在parsebench.ai配置自有文档测试。
The best "raw" frontier model for document parsing is gemini 3 flash, but the issue is that since th...
The best "raw" frontier model for document parsing is gemini 3 flash, but the issue is that since then the flash models have gotten 3x more expensive while flatlining on visual recognition across complex documents. This has been the case for every frontier model including the latest OpenAI/Anthropic models - see the diagram below for GPT (since then we've also benchmarked 5.6) In the meantime, hybrid approaches like LlamaParse that blend specialized VLMs with a text engine offer better performance; our own LlamaParse accuracy has increased 15% over tables and charts. If you have document OCR needs and are thinking about using a frontier model, you might as well come check out LlamaParse! cloud.llamaindex.ai We have a full eval harness through ParseBench that you can configure over your own docs: parsebench.ai Jerry Liu @jerryjliu0 Document OCR is not Getting Commoditized (by Frontier Models) The most common question I get is whether frontier models are going to eat all document processing solutions - just screenshot the page and feed it to your favorite frontier model. 1️⃣ Frontier models are flatlining in document understanding performance. Incremental releases in every model version (gpt 5.5 -> 5.6 sol, Gemini 3.5 flash -> 3.6 flash, opus 4.8 -> opus 5) are not improving visual understanding benchmarks. 2️⃣ The Pareto frontier for document OCR is much higher than the frontier models, and will always remain much higher. We’ve carefully tuned our agentic and cost-effective modes to solve a long tail of complex edge cases (dense tables, charts) that frontier models don’t care about. Also for equivalent performance, there’s always ways to get much lower cost. 3️⃣ Even if they were getting better, you can distill / posttrain them into much more parameter efficient models for a fraction of the cost. Different document pages can be routed to different processors of varying complexity. 4️⃣ Every startup is doing the same thing right now. Focusing on one task means you can always hillclimb that task more effectively than a general model over the task, in terms of accuracy/cost/latency. Check out the blog: llamaindex.ai/blog/document-… LlamaParse has gotten a LOT better in the past few months. Come check it out! cloud.llamaindex.ai 🔗 View Quoted Tweet 💬 1 🔄 0 ❤️ 1 👀 191 📊 1 ⚡