Mistral OCR 3 Mistral AI
💰 Total Cost Calculation (from Plugin)
Output: $0.000000
Output: $0.000000
Unit: $0.100000
Fees: $0.000000
Advanced Cost Breakdown (from Plugin)
Detailed Cost Analysis (from Plugin)
For 50,000 input tokens and 1,000 output tokens:
- Input Cost: $0.000000
- Output Cost: $0.000000
- Unit Cost: $0.100000
- Total Cost: $0.100000
- Cost per 1K tokens: $0.001961
- Tokens per dollar: 510,000 tokens
- Context Window: 65536 tokens
- Thinking Source: (0 tokens)
Speed & Performance Analysis
With a processing speed of 300 tokens per second and 200ms time to first token:
- Processing Time: 2 minutes, 50.18 seconds
- Latency: 200 milliseconds to first token
- Base Throughput: 300 tokens/second
Best Use Cases
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← Back to Mistral OCR 3| Rank | AI Model & Provider | Total Cost | vs Mistral OCR 3 |
|---|---|---|---|
| 🏆 |
Mistral Small 3
Mistral AI
|
$0.001325 Best Value | ↓ 98.7% cheaper |
| 🥈 |
Devstral Small 2
Mistral AI
|
$0.001325 | ↓ 98.7% cheaper |
| 🥉 |
Ministral 3 (14B)
Mistral AI
|
$0.002550 | ↓ 97.5% cheaper |
| #4 |
Gemini 3.1 Flash Lite
Google
|
$0.003500 | ↓ 96.5% cheaper |
| #5 |
Nemotron 3 Super
NVIDIA
|
$0.003955 | ↓ 96% cheaper |
| #6 |
Llama 4 Scout
Meta AI
|
$0.004300 | ↓ 95.7% cheaper |
| #7 |
Gemini 3.5 Flash-Lite
Google
|
$0.004375 | ↓ 95.6% cheaper |
| #8 |
Gemini 2.5 Flash
Google
|
$0.004375 | ↓ 95.6% cheaper |
| #9 |
Devstral 2
Mistral AI
|
$0.005225 (rounded ~ $0.01) | ↓ 94.8% cheaper |
| #10 |
Mistral Large 3
Mistral AI
|
$0.006625 (rounded ~ $0.01) | ↓ 93.4% cheaper |
| #11 |
Llama 4 Maverick (400B)
Meta AI
|
$0.008100 (rounded ~ $0.01) | ↓ 91.9% cheaper |
| #12 |
Gemini 3.8 Flash
Google
|
$0.010313 | ↓ 89.7% cheaper |
| #13 |
GPT-5.4 mini
OpenAI
|
$0.010500 | ↓ 89.5% cheaper |
| #14 |
o4-mini Deep Research
OpenAI
|
$0.013500 (rounded ~ $0.01) | ↓ 86.5% cheaper |
| #15 |
Claude Haiku 4.5
Anthropic
|
$0.013750 (rounded ~ $0.01) | ↓ 86.3% cheaper |
| #16 |
Gemini 3.1 Flash
Google
|
$0.014000 (rounded ~ $0.01) | ↓ 86% cheaper |
| #17 |
GPT-5.6 Luna
OpenAI
|
$0.014000 (rounded ~ $0.01) | ↓ 86% cheaper |
| #18 |
o4-mini
OpenAI
|
$0.014850 (rounded ~ $0.01) | ↓ 85.2% cheaper |
| #19 |
Gemini 3.6 Flash
Google
|
$0.020625 | ↓ 79.4% cheaper |
| #20 |
Gemini 3.5 Flash
Google
|
$0.021000 (rounded ~ $0.02) | ↓ 79% cheaper |
| #21 |
GPT-5.3 Codex Spark
OpenAI
|
$0.025375 (rounded ~ $0.03) | ↓ 74.6% cheaper |
| #22 |
GPT-5.3 Instant
OpenAI
|
$0.025375 (rounded ~ $0.03) | ↓ 74.6% cheaper |
| #23 |
Magistral Medium
Mistral AI
|
$0.026250 (rounded ~ $0.03) | ↓ 73.8% cheaper |
| #24 |
Claude Sonnet 5
Anthropic
|
$0.027500 (rounded ~ $0.03) | ↓ 72.5% cheaper |
| #25 |
Llama 3.3 70B
Meta AI
|
$0.031200 (rounded ~ $0.03) | ↓ 68.8% cheaper |
| #26 |
GPT-5.6 Terra
OpenAI
|
$0.035000 (rounded ~ $0.04) | ↓ 65% cheaper |
| #27 |
Gemini 2.5 Pro
Google
|
$0.036250 (rounded ~ $0.04) | ↓ 63.8% cheaper |
| #28 |
Claude Sonnet 4.6
Anthropic
|
$0.041250 (rounded ~ $0.04) | ↓ 58.8% cheaper |
| #29 |
Grok 4.3
xAI
|
$0.052000 (rounded ~ $0.05) | ↓ 48% cheaper |
| #30 |
Grok 4.20 Beta
xAI
|
$0.052000 (rounded ~ $0.05) | ↓ 48% cheaper |
| #31 |
Gemini 3.1 Pro
Google
|
$0.056000 (rounded ~ $0.06) | ↓ 44% cheaper |
| #32 |
Claude Opus 4.7
Anthropic
|
$0.068750 (rounded ~ $0.07) | ↓ 31.3% cheaper |
| #33 |
Claude Opus 5
Anthropic
|
$0.068750 (rounded ~ $0.07) | ↓ 31.3% cheaper |
| #34 |
Claude Opus 4.8
Anthropic
|
$0.068750 (rounded ~ $0.07) | ↓ 31.3% cheaper |
| #35 |
Claude Opus 4.6
Anthropic
|
$0.068750 (rounded ~ $0.07) | ↓ 31.3% cheaper |
| #36 |
GPT-5.4
OpenAI
|
$0.070000 | ↓ 30% cheaper |
| #37 |
GPT-5.4 Thinking
OpenAI
|
$0.070000 | ↓ 30% cheaper |
| #38 |
GPT-5.5 Instant
OpenAI
|
$0.070000 | ↓ 30% cheaper |
| #39 |
GPT-5.6 Sol
OpenAI
|
$0.070000 | ↓ 30% cheaper |
| #40 |
o3 Deep Research
OpenAI
|
$0.135000 (rounded ~ $0.14) | ↑ 35% more |
| #41 |
Claude Fable 5.1
Anthropic
|
$0.137500 (rounded ~ $0.14) | ↑ 37.5% more |
| #42 |
Claude Mythos 5.1
Anthropic
|
$0.137500 (rounded ~ $0.14) | ↑ 37.5% more |
| #43 |
Claude Fable 5
Anthropic
|
$0.137500 (rounded ~ $0.14) | ↑ 37.5% more |
| #44 |
Claude Mythos 5
Anthropic
|
$0.137500 (rounded ~ $0.14) | ↑ 37.5% more |
| #45 |
GPT-5.5
OpenAI
|
$0.140000 | ↑ 40% more |
| #46 |
o3 Pro
OpenAI
|
$0.270000 | ↑ 170% more |
| #47 |
GPT-6 Astra
OpenAI
|
$0.275000 (rounded ~ $0.28) | ↑ 175% more |
| #48 |
GPT-5.2 Pro
OpenAI
|
$0.304500 (rounded ~ $0.30) | ↑ 204.5% more |
| #49 |
GPT-5.5 Pro
OpenAI
|
$0.420000 | ↑ 320% more |
| #50 |
GPT-5.5 Pro
OpenAI
|
$0.420000 | ↑ 320% more |
Mistral Small 3 Mistral AI
Devstral Small 2 Mistral AI
Ministral 3 (14B) Mistral AI
Gemini 3.1 Flash Lite Google
Nemotron 3 Super NVIDIA
Llama 4 Scout Meta AI
Gemini 3.5 Flash-Lite Google
Gemini 2.5 Flash Google
Devstral 2 Mistral AI
Mistral Large 3 Mistral AI
Llama 4 Maverick (400B) Meta AI
Gemini 3.8 Flash Google
GPT-5.4 mini OpenAI
o4-mini Deep Research OpenAI
Claude Haiku 4.5 Anthropic
Gemini 3.1 Flash Google
GPT-5.6 Luna OpenAI
o4-mini OpenAI
Gemini 3.6 Flash Google
Gemini 3.5 Flash Google
GPT-5.3 Codex Spark OpenAI
GPT-5.3 Instant OpenAI
Magistral Medium Mistral AI
Claude Sonnet 5 Anthropic
Llama 3.3 70B Meta AI
GPT-5.6 Terra OpenAI
Gemini 2.5 Pro Google
Claude Sonnet 4.6 Anthropic
Grok 4.3 xAI
Grok 4.20 Beta xAI
Gemini 3.1 Pro Google
Claude Opus 4.7 Anthropic
Claude Opus 5 Anthropic
Claude Opus 4.8 Anthropic
Claude Opus 4.6 Anthropic
GPT-5.4 OpenAI
GPT-5.4 Thinking OpenAI
GPT-5.5 Instant OpenAI
GPT-5.6 Sol OpenAI
o3 Deep Research OpenAI
Claude Fable 5.1 Anthropic
Claude Mythos 5.1 Anthropic
Claude Fable 5 Anthropic
Claude Mythos 5 Anthropic
GPT-5.5 OpenAI
o3 Pro OpenAI
GPT-6 Astra OpenAI
GPT-5.2 Pro OpenAI
GPT-5.5 Pro OpenAI
GPT-5.5 Pro OpenAI
Scaling document processing to 1 million PDFs per month requires more than just high-speed text extraction; it necessitates a document-intelligence layer that understands layout, structure, and hierarchy. Mistral OCR 3 has emerged as a specialized solution for this scale, moving beyond simple character recognition to provide structured data outputs that are ready for immediate downstream consumption in RAG and automation workflows.
The core strength of this model lies in its ability to output structured formats like Markdown or JSON, which effectively preserve the semantic relationship between elements. For enterprise teams, this means that headers, tables, and lists remain intact, reducing the need for costly post-processing or manual cleaning. Its architecture is optimized for heavy batch processing, which is a critical requirement when you are ingesting huge volumes of historical or incoming business documents.
Unlike traditional OCR pipelines that rely on fragile, rule-based heuristics to parse layout, Mistral OCR 3 utilizes a deep understanding of document structure. This reduces the error rate significantly when dealing with complex, real-world documents such as invoices, financial reports, or dense technical schematics. By integrating directly into your data pipeline, this model allows for cleaner, more reliable data ingestion, which directly improves the performance of any retrieval-augmented generation system feeding off these documents. For enterprises focusing on quality at scale, it provides a stable foundation for transforming document archives into queryable assets.