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 4
Mistral AI
|
$0.002025 Best Value | ↓ 98% cheaper |
| 🥈 |
Ministral 3 (14B)
Mistral AI
|
$0.002550 | ↓ 97.5% cheaper |
| 🥉 |
Claude Haiku 5.5
Anthropic
|
$0.002750 | ↓ 97.3% cheaper |
| #4 |
GPT-6 Luna
OpenAI
|
$0.002750 | ↓ 97.3% cheaper |
| #5 |
GPT-5.6 Luna
OpenAI
|
$0.002800 | ↓ 97.2% cheaper |
| #6 |
Gemini 3.1 Flash Lite
Google
|
$0.003500 | ↓ 96.5% cheaper |
| #7 |
Nemotron 3 Super
NVIDIA
|
$0.003955 | ↓ 96% cheaper |
| #8 |
Llama 4 Scout
Meta AI
|
$0.004300 | ↓ 95.7% cheaper |
| #9 |
Gemini 3.5 Flash-Lite
Google
|
$0.004375 | ↓ 95.6% cheaper |
| #10 |
Gemini 2.5 Flash
Google
|
$0.004375 | ↓ 95.6% cheaper |
| #11 |
Mistral Large 3
Mistral AI
|
$0.006625 (rounded ~ $0.01) | ↓ 93.4% cheaper |
| #12 |
Llama 4 Maverick (400B)
Meta AI
|
$0.008100 (rounded ~ $0.01) | ↓ 91.9% cheaper |
| #13 |
Gemini 3.8 Flash
Google
|
$0.010313 | ↓ 89.7% cheaper |
| #14 |
Gemini 3.6 Flash
Google
|
$0.010313 | ↓ 89.7% cheaper |
| #15 |
GPT-5.4 mini
OpenAI
|
$0.010500 | ↓ 89.5% cheaper |
| #16 |
Claude Haiku 4.5
Anthropic
|
$0.013750 (rounded ~ $0.01) | ↓ 86.3% cheaper |
| #17 |
Gemini 3.1 Flash
Google
|
$0.014000 (rounded ~ $0.01) | ↓ 86% cheaper |
| #18 |
Mistral Large 4
Mistral AI
|
$0.018045 (rounded ~ $0.02) | ↓ 82% cheaper |
| #19 |
Mistral Medium 3.5
Mistral AI
|
$0.020625 | ↓ 79.4% cheaper |
| #20 |
GPT-5.3 Codex Spark
OpenAI
|
$0.025375 (rounded ~ $0.03) | ↓ 74.6% cheaper |
| #21 |
GPT-5.3 Instant
OpenAI
|
$0.025375 (rounded ~ $0.03) | ↓ 74.6% cheaper |
| #22 |
Claude Sonnet 5.5
Anthropic
|
$0.027500 (rounded ~ $0.03) | ↓ 72.5% cheaper |
| #23 |
Claude Sonnet 5
Anthropic
|
$0.027500 (rounded ~ $0.03) | ↓ 72.5% cheaper |
| #24 |
Gemini 4 Argon
Google
|
$0.027500 (rounded ~ $0.03) | ↓ 72.5% cheaper |
| #25 |
GPT-5.6 Terra
OpenAI
|
$0.028000 (rounded ~ $0.03) | ↓ 72% cheaper |
| #26 |
Llama 3.3 70B
Meta AI
|
$0.031200 (rounded ~ $0.03) | ↓ 68.8% 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 |
Claude Opus 5.5
Anthropic
|
$0.055000 (rounded ~ $0.06) | ↓ 45% cheaper |
| #32 |
GPT-6.1 Sol
OpenAI
|
$0.055000 (rounded ~ $0.06) | ↓ 45% cheaper |
| #33 |
GPT-6 Sol
OpenAI
|
$0.055000 (rounded ~ $0.06) | ↓ 45% cheaper |
| #34 |
GPT-5.6 Sol
OpenAI
|
$0.055000 (rounded ~ $0.06) | ↓ 45% cheaper |
| #35 |
Gemini 3.1 Pro
Google
|
$0.056000 (rounded ~ $0.06) | ↓ 44% cheaper |
| #36 |
Claude Opus 4.7
Anthropic
|
$0.068750 (rounded ~ $0.07) | ↓ 31.3% cheaper |
| #37 |
Claude Opus 5
Anthropic
|
$0.068750 (rounded ~ $0.07) | ↓ 31.3% cheaper |
| #38 |
Claude Opus 4.8
Anthropic
|
$0.068750 (rounded ~ $0.07) | ↓ 31.3% cheaper |
| #39 |
Claude Opus 4.6
Anthropic
|
$0.068750 (rounded ~ $0.07) | ↓ 31.3% cheaper |
| #40 |
GPT-5.4
OpenAI
|
$0.070000 | ↓ 30% cheaper |
| #41 |
GPT-5.4 Thinking
OpenAI
|
$0.070000 | ↓ 30% cheaper |
| #42 |
GPT-5.5 Instant
OpenAI
|
$0.070000 | ↓ 30% cheaper |
| #43 |
Claude Fable 5.1
Anthropic
|
$0.137500 (rounded ~ $0.14) | ↑ 37.5% more |
| #44 |
Claude Mythos 5.1
Anthropic
|
$0.137500 (rounded ~ $0.14) | ↑ 37.5% more |
| #45 |
Claude Fable 5
Anthropic
|
$0.137500 (rounded ~ $0.14) | ↑ 37.5% more |
| #46 |
Claude Mythos 5
Anthropic
|
$0.137500 (rounded ~ $0.14) | ↑ 37.5% more |
| #47 |
GPT-5.5
OpenAI
|
$0.140000 | ↑ 40% more |
| #48 |
GPT-6 Astra
OpenAI
|
$0.275000 (rounded ~ $0.28) | ↑ 175% more |
| #49 |
GPT-5.2 Pro
OpenAI
|
$0.304500 (rounded ~ $0.30) | ↑ 204.5% more |
| #50 |
GPT-5.5 Pro
OpenAI
|
$0.420000 | ↑ 320% more |
| #51 |
GPT-5.5 Pro
OpenAI
|
$0.420000 | ↑ 320% more |
Mistral Small 4 Mistral AI
Ministral 3 (14B) Mistral AI
Claude Haiku 5.5 Anthropic
GPT-6 Luna OpenAI
GPT-5.6 Luna OpenAI
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
Mistral Large 3 Mistral AI
Llama 4 Maverick (400B) Meta AI
Gemini 3.8 Flash Google
Gemini 3.6 Flash Google
GPT-5.4 mini OpenAI
Claude Haiku 4.5 Anthropic
Gemini 3.1 Flash Google
Mistral Large 4 Mistral AI
Mistral Medium 3.5 Mistral AI
GPT-5.3 Codex Spark OpenAI
GPT-5.3 Instant OpenAI
Claude Sonnet 5.5 Anthropic
Claude Sonnet 5 Anthropic
Gemini 4 Argon Google
GPT-5.6 Terra OpenAI
Llama 3.3 70B Meta AI
Gemini 2.5 Pro Google
Claude Sonnet 4.6 Anthropic
Grok 4.3 xAI
Grok 4.20 Beta xAI
Claude Opus 5.5 Anthropic
GPT-6.1 Sol OpenAI
GPT-6 Sol OpenAI
GPT-5.6 Sol OpenAI
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
Claude Fable 5.1 Anthropic
Claude Mythos 5.1 Anthropic
Claude Fable 5 Anthropic
Claude Mythos 5 Anthropic
GPT-5.5 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.