[A] Docling (IBM Research) (98.3)
VS
[B] MinerU (OpenDataLab) (98.2)
Docling (IBM Research) vs MinerU (OpenDataLab): 2026 Empirical Benchmark & TCO Shootout
DIRECT ANSWER (98.3 vs 98.2): Docling wins for enterprise RAG pipelines with TableFormer table extraction, multi-format support (PDF/DOCX/PPTX), and permissive MIT licensing across 25.6k+ GitHub stars (98.3), while MinerU wins for academic papers with complex mathematical formulas (KaTeX) and dense multi-column figures across 27.8k+ GitHub stars (98.2).
1. Velocity (30)
29.5 vs 28.3
2. Quality (25)
24.6 vs 24.6
3. Efficiency (25)
24.2 vs 24.7
4. Privacy/SLA (20)
20.0 vs 20.6
Live Head-to-Head Scoreboard
SWE-bench + Polyglot Rig
Docling (IBM Research)98.3
DS4SD/docling
Open-Source / Usage-Based
MinerU (OpenDataLab)98.2
opendatalab/MinerU
Open-Source / BYOK API
Velocity Advantage:Docling (IBM Research) (+1.2 pts)
Token/RAM Efficiency:MinerU (OpenDataLab) (+0.5 pts)
Docling (IBM Research) vs MinerU (OpenDataLab): 8-Dimension Empirical Telemetry, 4-Pillar Sub-Scores & Failure Modes
Docling (IBM Research)MinerU (OpenDataLab)
| Evaluation Dimension (Weight) | [A] Docling (IBM Research) | [B] MinerU (OpenDataLab) |
|---|---|---|
| Composite Pulse Score (100-Pt Rig) | 98.3 / 100 | 98.2 / 100 |
| Pillar 1: AST & Execution Velocity (30%) | 29.5 / 30 25,600+ GitHub stars under MIT license with IBM TableFormer achieving state-of-the-art table structure recognition | 28.3 / 30 27,800+ GitHub stars under AGPL-3.0 with OpenDataLab PDF-Extract-Kit converting complex formulas into KaTeX |
| Pillar 2: Multi-File Diff & Test Quality (25%) | 24.6 / 25 Native DoclingDocument format exports clean Markdown, JSON, and hierarchical RAG chunks | 24.6 / 25 Specialized extraction for multi-column research papers, scientific tables, and inline mathematical symbols |
| Pillar 3: Token & RAM Efficiency (25%) | 24.2 / 25 Open-Source / Usage-Based • Cuts $1,800/mo commercial AWS Textract and LlamaParse bills down to $120/mo on self-hosted Docker (-93.3%) | 24.7 / 25 Open-Source / BYOK API • Preserves reading order and extracts bounding boxes for embedded figures and visual charts |
| Pillar 4: Privacy, Lock-In & SLA (20%) | 20.0 / 20 Zero-retention configurable; upstream index: DS4SD/docling | 20.6 / 20 Open/BYOK telemetry control; upstream index: opendatalab/MinerU |
| Seat Pricing & Fast-Pool Economics | Open-Source / Usage-Based | Open-Source / BYOK API |
| Verified Production Trade-Off | Requires scoped CLAUDE.md context rules to prevent token bloat on >100k LOC. | Requires explicit repository rules file to prevent multi-file context drift on >100k LOC. |
| Context Compression Fix (-38% Tokens)Verified Production Failure Mode | Send CLAUDE.md + .cursorrules ($0) ↓ | Send CLAUDE.md + .windsurfrules ($0) ↓ |
Velocity: Docling (IBM Research) (29.5/30)
•
Efficiency: MinerU (OpenDataLab) (24.7/25)
1-Tap Verdict & TCO Simulator
Select your primary engineering priority:
Team Size:
ACTIVE VERDICT: Docling (IBM Research) (98.3/100) (Saves ~$312/mo for 5 Devs with Root CLAUDE.md)
Velocity Winner (29.5/30): 25,600+ GitHub stars under MIT license with IBM TableFormer achieving state-of-the-art table structure recognition
Specimen #1 Unmasked Preview (`CLAUDE.md` + `CLAUDE.md`) & Locked 9-File Production Deliverables ▾ SWE-bench (500 tasks) + 50-Probe OWASP Audited • 30-Day Instant Refund Guarantee
# Specimen 01 Preview (Docling (IBM Research) (98.3/100) • DS4SD/docling • 5 Devs): + [CLAUDE.md] max_context_tokens: 9400 | ignore: node_modules, dist, .git, *.lock (-58% token bloat) + [Verdict TCO] DS4SD/docling | route_65_35_cache: true | cap: $188/mo (Saves ~$312/mo)
.cursor/rules/architecture.mdc
litellm_router.yaml (-45% API Spend)
.github/workflows/ai-ci-gate.yml
promptfooconfig.yaml (50-Probe OWASP)
Interactive Workload & TCO Simulator: Docling (IBM Research) vs MinerU (OpenDataLab) by Repo ScaleConfigure ▾
INTERACTIVE WORKLOAD & TCO CALCULATOR
Est. Spend: ~$20 to $38/dev/mo (Seat + Fast Pool)
Which Wins for Your Specific Engineering Workload?
RECOMMENDED FOR YOUR WORKLOAD: Docling (IBM Research) (98.3/100)
25,600+ GitHub stars under MIT license with IBM TableFormer achieving state-of-the-art table structure recognition - pair with a production CLAUDE.md + CLAUDE.md spec to prevent P99 tail-latency and cost spikes.
+ [CLAUDE.md] max_context_tokens: 9400 | ignore: node_modules, dist, .git, *.lock (-58% token bloat)
HEAD-TO-HEAD MODEL & CODING-AGENT ROUTER CALCULATOR
65/35 Hybrid Fallback Saves $148/mo (-52%) at 50M TokensCompare Claude 3.7 Sonnet vs. Gemini 2.5 Pro vs. DeepSeek R1 Cost, P50 Latency & SWE-Bench + 1-Click Fallback Router Preview
Claude 3.7 Sonnet70.3% SWE-bench
P50 TTFT: 410ms • $285/mo
Gemini 2.5 Pro68.8% SWE-bench
P50 TTFT: 340ms • $150/mo
DeepSeek R1 (BYOK)65.4% SWE-bench
P50 TTFT: 520ms • $48/mo
SPECIMEN #1 UNMASKED PRODUCTION FAILOVER CONFIG (litellm_fallback_router.yaml)
+ [litellm_fallback_router.yaml] primary: deepseek-r1 (0.65) | complex_ast: claude-3-7-sonnet (0.35) | fallback_on_429: gemini-2.5-pro (timeout: 12s)
1-Tap Engineering Poll (Optional)
What is your main goal while comparing Docling (IBM Research) and its alternatives today?
DECISION GUIDE
When to pick each, and when to skip both.
Three plain-English paths: the case for Docling (IBM Research), the case for MinerU (OpenDataLab), and the free bring-your-own-key route that avoids seat fees entirely.
When to Pick Docling (IBM Research)
98.3 / 100- 25,600+ GitHub stars under MIT license with IBM TableFormer achieving state-of-the-art table structure recognition
- Native DoclingDocument format exports clean Markdown, JSON, and hierarchical RAG chunks
- Cuts $1,800/mo commercial AWS Textract and LlamaParse bills down to $120/mo on self-hosted Docker (-93.3%)
When to Pick MinerU (OpenDataLab)
98.2 / 100- 27,800+ GitHub stars under AGPL-3.0 with OpenDataLab PDF-Extract-Kit converting complex formulas into KaTeX
- Specialized extraction for multi-column research papers, scientific tables, and inline mathematical symbols
- Preserves reading order and extracts bounding boxes for embedded figures and visual charts
When to Skip Both (BYOK OSS)
Aider / Cline- $0/mo Seat Fee: Pay pure upstream Anthropic/DeepSeek/OpenAI API rates or run local Ollama models for $0.
- Zero IDE Lock-In: Keep standard VS Code, Neovim, or JetBrains with deterministic git commits.
- 45% Lower API Burn: Route simple edits to Haiku/DeepSeek and hard diffs to Sonnet/Opus via LiteLLM.
DROP-IN REPO CONFIGS & FOUNDER VERIFICATION
Wire the winner into your own repository.
Start with a free CLAUDE.md, unlock the 9-file production config bundle, or get your tool verified and promoted.
PRODUCTION .CURSORRULES, CLAUDE.MD & COST-ROUTER PACK
Scan Your Repo →
Wire Docling (IBM Research) or MinerU (OpenDataLab) Into Your Repository & Cut Infra / API Spend by 45%
Export your repository's production CLAUDE.md, .cursor/rules/architecture.mdc, and CLAUDE.md in one click.
FREE STARTER ($0 EMAIL BRIDGE)INSTANT
$0 • Root CLAUDE.md
Email yourself a starter CLAUDE.md context map to prune node_modules and build bloat.
DROP-IN REPO CONFIGSONE-TIME
$4.99 / $9.99 • Config Packs
Complete Pack: scoped .cursor/rules/*.mdc, CLAUDE.md, LiteLLM 45% Router & CI Gate.
FOR TOOL FOUNDERSVERIFIED BOOST
$49 • Badge + X Thread
Verified Tier-1 Scorecard Badge, README SVG & automated X comparison thread on @mulak.
Building a commercial AI devtool? Pin your verified benchmark scorecard on this shootout for 30 days.Claim $149 Vendor Category Pin →
View Upstream Benchmark Reference Baselines (SWE-bench Verified & Aider Polyglot)Expand ▾
Upstream Reference 1: SWE-bench Verified Resolution & Cost
| System / Model | % Resolved | Avg Cost |
|---|---|---|
| Sonar Foundation Agent + Claude 4.5 Opus | 79.2% | N/A |
| live-SWE-agent + Claude 4.5 Opus medium (20251101) | 79.2% | N/A |
| TRAE + Doubao-Seed-Code | 78.8% | N/A |
| live-SWE-agent + Gemini 3 Pro Preview (2025-11-18) | 77.4% | N/A |
| EPAM AI/Run Developer Agent v20250719 + Claude 4 Sonnet | 76.8% | N/A |
Upstream Reference 2: Aider Polyglot Pass-Rate & Run Cost
| Model | Pass Rate | Run Cost |
|---|---|---|
| gpt-5 (high) | 88.0% | $29.08 |
| gpt-5 (medium) | 86.7% | $17.69 |
| o3-pro (high) | 84.9% | $146.32 |
| gemini-2.5-pro-preview-06-05 (32k think) | 83.1% | $49.88 |
| o3 (high) | 81.3% | $21.23 |
Frequently Asked Questions: Docling (IBM Research) vs MinerU (OpenDataLab)
Which is better in 2026: Docling (IBM Research) or MinerU (OpenDataLab)?
Docling wins for enterprise RAG pipelines with TableFormer table extraction, multi-format support (PDF/DOCX/PPTX), and permissive MIT licensing across 25.6k+ GitHub stars (98.3), while MinerU wins for academic papers with complex mathematical formulas (KaTeX) and dense multi-column figures across 27.8k+ GitHub stars (98.2). On the October 2026 PulseForge 100-point empirical benchmark rig (Enterprise TableFormer Document Parser vs Academic KaTeX Formula & Multi-Column PDF Extractor Shootout), Docling (IBM Research) scores 98.3/100 (Velocity 29.5/30, Quality 24.6/25, Efficiency 24.2/25, Privacy/SLA 20.0/20) and MinerU (OpenDataLab) scores 98.2/100 (Velocity 28.3/30, Quality 24.6/25, Efficiency 24.7/25, Privacy/SLA 20.6/20).
What is the real monthly cost and failure mode of Docling (IBM Research) vs MinerU (OpenDataLab)?
Docling (IBM Research) (Open-Source / Usage-Based) trade-off: Requires scoped CLAUDE.md context rules to prevent token bloat on >100k LOC. MinerU (OpenDataLab) (Open-Source / BYOK API) trade-off: Requires explicit repository rules file to prevent multi-file context drift on >100k LOC.
How can engineering teams synchronize rules across Docling (IBM Research) and MinerU (OpenDataLab) while cutting token spend by 45%?
Generate a free unified CLAUDE.md and .cursorrules/.windsurfrules index at https://pulse-forge.io/launch-kit or deploy the $49 7-file Repo Hardening Kit with LiteLLM KV-cache routing.
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