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light estimateLast updated 2026-08-20

LlamaIndex vs Z.ai

LlamaParse vs GLM-OCR for ocr & document extraction. Computed from public benchmarks with dated sources; updated 2026-08-20.

Head to head
LlamaParse compared with GLM-OCR per decision axis
AxisLlamaParseGLM-OCREdge
Price$3.75 per 1000 pages*—*—
Score—95.22—
Max pages—100—
tables✓✓—
handwriting✓✓—
JSON✓✓—

* token-/credit-priced — the headline understates real per-unit cost, so no price edge is awarded.

Strengths & caveats
LlamaIndexFlexible parse modes tuned for RAG at a confirmed $1.25 per 1000 credits: Fast 1 credit (~$1.25/1000 pages), Cost-effective 3 credits (~$3.75/1000), Agentic 10 credits (~$12.50/1000) and Agentic Plus 45 credits (~$56.25/1000); strong markdown/JSON, tables and multimodal, 10K free monthly credits and free re-parses of the same file within a 48-hour cache window. Per-page cost swings 1x-45x by mode, so the $3.75/1000 figure (Cost-effective) is only one tier — flagged vergelijkbaar=false; layout extraction adds +3 credits per page on top. No published OmniDocBench score (null).Z.aiHighest published independent OmniDocBench composite of any hosted API in this table (95.22 on v1.6; Z.ai cites 94.62 on v1.5), callable at api.z.ai/api/paas/v4/layout_parsing with text, markdown and image-link output, HTML table reconstruction and handwriting support; the underlying 0.9B model is also self-hostable, and throughput is quoted at 1.86 PDF pages/second. Priced per token ($0.03 per million tokens for both input and output), not per page, so no comparable $/1000-pages rate exists without estimating — excluded from the price axis. Tight caps (100 pages per document, PDF 50MB, single image 10MB) rule it out for large documents, the documented language list is narrower than the hyperscalers', and China-hosted inference may raise data-residency questions for EU/US buyers.
Sources