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 5,000 output tokens:
- Input Cost: $0.000000
- Output Cost: $0.000000
- Unit Cost: $0.100000
- Total Cost: $0.100000
- Cost per 1K tokens: $0.001818
- Tokens per dollar: 550,000 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: 3 minutes, 3.51 seconds
- Latency: 200 milliseconds to first token
- Base Throughput: 300 tokens/second
Best Use Cases
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This calculator shows the math for Mistral OCR 3. Your decision needs more — current infrastructure, compliance requirements, actual workload patterns, volume tiers — that change which model is right for you.
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💰 Total Cost Calculation (from Plugin)
Output: $0.003125
Output: $0.003125
Unit: $0.000000
Fees: $0.000000
Advanced Cost Breakdown (from Plugin)
Multimodal Input Details
Resolution: Medium
Tokens: 51,600
Cost: $0.000000
Detailed Cost Analysis (from Plugin)
For 50,000 input tokens and 5,000 output tokens:
- Input Cost: $0.031750 (rounded ~ $0.03)
- Output Cost: $0.003125
- Total Cost: $0.023445 (rounded ~ $0.02)
- Cost per 1K tokens: $0.000220
- Tokens per dollar: 4,546,812 tokens
- Context Window: 1000000 tokens
Speed & Performance Analysis
With a processing speed of 550 tokens per second and 200ms time to first token:
- Processing Time: 3 minutes, 27.57 seconds
- Latency: 200 milliseconds to first token
- Base Throughput: 550 tokens/second
- Effective Throughput: 514 tokens/second (temperature-adjusted)
Best Use Cases
Want this applied to YOUR actual stack?
This calculator shows the math for Grok 4.1. Your decision needs more — current infrastructure, compliance requirements, actual workload patterns, volume tiers — that change which model is right for you.
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Get my instant AI audit — $39 →✨ Market Recommendations AI Model Registry
← Back to Mistral OCR 3| Rank | AI Model & Provider | Total Cost | vs Mistral OCR 3 | vs Grok 4.1 |
|---|---|---|---|---|
| 🏆 |
Mistral Small 3
Mistral AI
|
$0.002001 Best Value | ↓ 98% cheaper | ↓ 91.5% cheaper |
| 🥈 |
Ministral 3 (14B)
Mistral AI
|
$0.003601 | ↓ 96.4% cheaper | ↓ 84.6% cheaper |
| 🥉 |
Gemini 3.1 Flash Lite
Google
|
$0.005939 (rounded ~ $0.01) | ↓ 94.1% cheaper | ↓ 74.7% cheaper |
| #4 |
Gemini 2.5 Flash
Google
|
$0.008002 (rounded ~ $0.01) | ↓ 92% cheaper | ↓ 65.9% cheaper |
| #5 |
Mistral Large 3
Mistral AI
|
$0.010253 | ↓ 89.7% cheaper | ↓ 56.3% cheaper |
| #6 |
GPT-5.4 mini
OpenAI
|
$0.017817 (rounded ~ $0.02) | ↓ 82.2% cheaper | ↓ 24% cheaper |
| #7 |
o4-mini Deep Research
OpenAI
|
$0.021256 (rounded ~ $0.02) | ↓ 78.7% cheaper | ↓ 9.3% cheaper |
| #8 |
Claude Haiku 4.5
Anthropic
|
$0.022506 (rounded ~ $0.02) | ↓ 77.5% cheaper | ↓ 4% cheaper |
| #9 |
o4-mini
OpenAI
|
$0.023382 (rounded ~ $0.02) | ↓ 76.6% cheaper | ↓ 0.3% cheaper |
| #10 |
Grok 4.3
xAI
|
$0.023445 (rounded ~ $0.02) | ↓ 76.6% cheaper | Same price |
| #11 |
Gemini 3.1 Flash
Google
|
$0.023756 (rounded ~ $0.02) | ↓ 76.2% cheaper | ↑ 1.3% more |
| #12 |
Gemini 3.5 Flash
Google
|
$0.035634 (rounded ~ $0.04) | ↓ 64.4% cheaper | ↑ 52% more |
| #13 |
GPT-5.3 Codex Spark
OpenAI
|
$0.045948 (rounded ~ $0.05) | ↓ 54.1% cheaper | ↑ 96% more |
| #14 |
GPT-5.3 Instant
OpenAI
|
$0.045948 (rounded ~ $0.05) | ↓ 54.1% cheaper | ↑ 96% more |
| #15 |
Gemini 2.5 Pro
Google
|
$0.065640 (rounded ~ $0.07) | ↓ 34.4% cheaper | ↑ 180% more |
| #16 |
Claude Sonnet 4.6
Anthropic
|
$0.067518 (rounded ~ $0.07) | ↓ 32.5% cheaper | ↑ 188% more |
| #17 |
Gemini 3.1 Pro
Google
|
$0.095024 (rounded ~ $0.10) | ↓ 5% cheaper | ↑ 305.3% more |
| #18 |
Claude Opus 4.7
Anthropic
|
$0.112530 (rounded ~ $0.11) | ↑ 12.5% more | ↑ 380% more |
| #19 |
Claude Opus 4.8
Anthropic
|
$0.112530 (rounded ~ $0.11) | ↑ 12.5% more | ↑ 380% more |
| #20 |
Claude Opus 4.6
Anthropic
|
$0.112530 (rounded ~ $0.11) | ↑ 12.5% more | ↑ 380% more |
| #21 |
GPT-5.4
OpenAI
|
$0.118780 (rounded ~ $0.12) | ↑ 18.8% more | ↑ 406.6% more |
| #22 |
GPT-5.4 Thinking
OpenAI
|
$0.118780 (rounded ~ $0.12) | ↑ 18.8% more | ↑ 406.6% more |
| #23 |
GPT-5.5 Instant
OpenAI
|
$0.118780 (rounded ~ $0.12) | ↑ 18.8% more | ↑ 406.6% more |
| #24 |
o3 Deep Research
OpenAI
|
$0.212560 (rounded ~ $0.21) | ↑ 112.6% more | ↑ 806.6% more |
| #25 |
GPT-5.5
OpenAI
|
$0.237560 (rounded ~ $0.24) | ↑ 137.6% more | ↑ 913.3% more |
| #26 |
o3 Pro
OpenAI
|
$0.425120 (rounded ~ $0.43) | ↑ 325.1% more | ↑ 1713.3% more |
| #27 |
GPT-5.2 Pro
OpenAI
|
$0.551376 (rounded ~ $0.55) | ↑ 451.4% more | ↑ 2251.8% more |
| #28 |
GPT-5.2 Pro
OpenAI
|
$0.551376 (rounded ~ $0.55) | ↑ 451.4% more | ↑ 2251.8% more |
Mistral Small 3 Mistral AI
Ministral 3 (14B) Mistral AI
Gemini 3.1 Flash Lite Google
Gemini 2.5 Flash Google
Mistral Large 3 Mistral AI
GPT-5.4 mini OpenAI
o4-mini Deep Research OpenAI
Claude Haiku 4.5 Anthropic
o4-mini OpenAI
Grok 4.3 xAI
Gemini 3.1 Flash Google
Gemini 3.5 Flash Google
GPT-5.3 Codex Spark OpenAI
GPT-5.3 Instant OpenAI
Gemini 2.5 Pro Google
Claude Sonnet 4.6 Anthropic
Gemini 3.1 Pro Google
Claude Opus 4.7 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
o3 Deep Research OpenAI
GPT-5.5 OpenAI
o3 Pro OpenAI
GPT-5.2 Pro OpenAI
GPT-5.2 Pro OpenAI
When digitizing legacy archives, selecting the right OCR tool can significantly impact accuracy and efficiency. Mistral OCR 3 stands out as a dedicated OCR model, designed to interpret text, tables, and even handwriting with notable accuracy, aiming for around 90% on clear documents. Its focus is on robust text extraction, making it a strong contender for straightforward digitization tasks. On the other hand, Grok 4.1 offers broader multimodal capabilities, including OCR, which can be advantageous if your archival research involves analyzing documents with complex visual elements or requiring deeper contextual understanding beyond simple text extraction. For researchers working with limited sets of documents, comparing these two offers a choice between a specialized OCR solution and a more generalist model with OCR integrated. The decision may hinge on whether the primary need is pure text extraction accuracy or a more holistic document analysis capability.