Llama 4 vs Mistral OCR 4
Pricing, benchmarks, and use case comparison
Quick take
- •Llama 4 is meaningfully stronger at coding (72 vs 5 on our capability index).
- •Mistral OCR 4 is meaningfully stronger at cost efficiency (96 vs 82).
- •Llama 4 is open-weights (free to self-host); Mistral OCR 4 is paid API only.
Specs comparison
| Llama 4 | Mistral OCR 4 | |
|---|---|---|
| Provider | Meta | Mistral AI |
| Type | Open source | Closed source |
| Context window | ✓Up to 10M tokens (Scout); ~1M tokens (Maverick) | Not announced |
| Input / 1M tokens | ✓Free (self-host) | 4000 |
| Output / 1M tokens | Free (self-host) | 4000 |
| Release date | 2025-04 | 2026-06 |
Benchmarks
| Benchmark | Llama 4 | Mistral OCR 4 |
|---|---|---|
| Scout context window | 10M tokens | - |
| Scout size | 17B active / 109B total (16 experts) | - |
| Maverick size | 17B active / 400B total (128 experts) | - |
| OlmOCRBench | - | 85.20 |
| OmniDocBench | - | 93.07 |
| Human preference (head-to-head) | - | 72% win rate |
| Human evaluation (blind) | - | 72% |
| Human Evaluation (Blind Test) | - | 72% win rate |
Scores sourced from official provider release posts and independent benchmark aggregators.
Which should you choose?
Choose Llama 4 if...
- →You need extremely long context in an open model (Scout's 10M window)
- →Self-hosted or on-prem multimodal deployment
- →You want an efficient MoE that activates few parameters per token
- →Fine-tuning or full control over the model
Choose Mistral OCR 4 if...
- →You need to convert PDFs, scans, or office docs into structured text/Markdown
- →You require high-accuracy multilingual document parsing at low cost
- →You need tables, equations, and layout preserved with confidence scores
- →You must keep documents in-house (self-hosted deployment)