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 200,000 input tokens and 2,000 output tokens:
- Input Cost: $0.000000
- Output Cost: $0.000000
- Unit Cost: $0.100000
- Total Cost: $0.100000
- Cost per 1K tokens: $0.000495
- Tokens per dollar: 2,020,000 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: 11 minutes, 13.51 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: $0.001875
Output: $0.001875
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 200,000 input tokens and 2,000 output tokens:
- Input Cost: $0.047175 (rounded ~ $0.05)
- Output Cost: $0.001875
- Total Cost: $0.027821 (rounded ~ $0.03)
- Cost per 1K tokens: $0.000110
- Tokens per dollar: 9,115,335 tokens
- Context Window: 1048576 tokens
Speed & Performance Analysis
With a processing speed of 340 tokens per second and 105ms time to first token:
- Processing Time: 12 minutes, 40.98 seconds
- Latency: 105 milliseconds to first token
- Base Throughput: 340 tokens/second
- Effective Throughput: 333 tokens/second (temperature-adjusted)
Best Use Cases
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This calculator shows the math for Gemini 3.8 Flash. 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 Gemini 3.8 Flash |
|---|---|---|---|---|
| 🏆 |
GPT-6 Luna
OpenAI
|
$0.007419 (rounded ~ $0.01) Best Value | ↓ 92.6% cheaper | ↓ 73.3% cheaper |
| 🥈 |
GPT-5.6 Luna
OpenAI
|
$0.007519 (rounded ~ $0.01) | ↓ 92.5% cheaper | ↓ 73% cheaper |
| 🥉 |
Gemini 3.1 Flash Lite
Google
|
$0.009399 | ↓ 90.6% cheaper | ↓ 66.2% cheaper |
| #4 |
Gemini 3.5 Flash-Lite
Google
|
$0.011629 (rounded ~ $0.01) | ↓ 88.4% cheaper | ↓ 58.2% cheaper |
| #5 |
Gemini 2.5 Flash
Google
|
$0.011629 (rounded ~ $0.01) | ↓ 88.4% cheaper | ↓ 58.2% cheaper |
| #6 |
Mistral Large 3
Mistral AI
|
$0.018298 (rounded ~ $0.02) | ↓ 81.7% cheaper | ↓ 34.2% cheaper |
| #7 |
Gemini 3.8 Flash
Google
|
$0.027821 (rounded ~ $0.03) | ↓ 72.2% cheaper | Same price |
| #8 |
Gemini 3.6 Flash
Google
|
$0.027821 (rounded ~ $0.03) | ↓ 72.2% cheaper | Same price |
| #9 |
GPT-5.4 mini
OpenAI
|
$0.028196 (rounded ~ $0.03) | ↓ 71.8% cheaper | ↑ 1.3% more |
| #10 |
Claude Haiku 5.5
Anthropic
|
$0.037095 (rounded ~ $0.04) | ↓ 62.9% cheaper | ↑ 33.3% more |
| #11 |
Claude Haiku 4.5
Anthropic
|
$0.037095 (rounded ~ $0.04) | ↓ 62.9% cheaper | ↑ 33.3% more |
| #12 |
Mistral Large 4
Mistral AI
|
$0.049819 | ↓ 50.2% cheaper | ↑ 79.1% more |
| #13 |
Claude Sonnet 5.5
Anthropic
|
$0.071045 (rounded ~ $0.07) | ↓ 29% cheaper | ↑ 155.4% more |
| #14 |
Claude Sonnet 5
Anthropic
|
$0.074190 (rounded ~ $0.07) | ↓ 25.8% cheaper | ↑ 166.7% more |
| #15 |
Gemini 4 Argon
Google
|
$0.074190 (rounded ~ $0.07) | ↓ 25.8% cheaper | ↑ 166.7% more |
| #16 |
Gemini 3.1 Flash
Google
|
$0.075190 (rounded ~ $0.08) | ↓ 24.8% cheaper | ↑ 170.3% more |
| #17 |
GPT-5.6 Terra
OpenAI
|
$0.075190 (rounded ~ $0.08) | ↓ 24.8% cheaper | ↑ 170.3% more |
| #18 |
Claude Sonnet 4.6
Anthropic
|
$0.111285 (rounded ~ $0.11) | ↑ 11.3% more | ↑ 300% more |
| #19 |
Claude Opus 5.5
Anthropic
|
$0.142090 (rounded ~ $0.14) | ↑ 42.1% more | ↑ 410.7% more |
| #20 |
GPT-6.1 Sol
OpenAI
|
$0.148380 (rounded ~ $0.15) | ↑ 48.4% more | ↑ 433.3% more |
| #21 |
GPT-6 Sol
OpenAI
|
$0.148380 (rounded ~ $0.15) | ↑ 48.4% more | ↑ 433.3% more |
| #22 |
GPT-5.6 Sol
OpenAI
|
$0.148380 (rounded ~ $0.15) | ↑ 48.4% more | ↑ 433.3% more |
| #23 |
Claude Opus 4.7
Anthropic
|
$0.185475 (rounded ~ $0.19) | ↑ 85.5% more | ↑ 566.7% more |
| #24 |
Claude Opus 5
Anthropic
|
$0.185475 (rounded ~ $0.19) | ↑ 85.5% more | ↑ 566.7% more |
| #25 |
Claude Opus 4.8
Anthropic
|
$0.185475 (rounded ~ $0.19) | ↑ 85.5% more | ↑ 566.7% more |
| #26 |
Claude Opus 4.6
Anthropic
|
$0.185475 (rounded ~ $0.19) | ↑ 85.5% more | ↑ 566.7% more |
| #27 |
GPT-5.4
OpenAI
|
$0.187975 (rounded ~ $0.19) | ↑ 88% more | ↑ 575.7% more |
| #28 |
GPT-5.4 Thinking
OpenAI
|
$0.187975 (rounded ~ $0.19) | ↑ 88% more | ↑ 575.7% more |
| #29 |
Gemini 2.5 Pro
Google
|
$0.187975 (rounded ~ $0.19) | ↑ 88% more | ↑ 575.7% more |
| #30 |
GPT-5.5 Instant
OpenAI
|
$0.187975 (rounded ~ $0.19) | ↑ 88% more | ↑ 575.7% more |
| #31 |
Grok 4.3
xAI
|
$0.284760 (rounded ~ $0.28) | ↑ 184.8% more | ↑ 923.5% more |
| #32 |
Gemini 3.1 Pro
Google
|
$0.294760 (rounded ~ $0.29) | ↑ 194.8% more | ↑ 959.5% more |
| #33 |
Claude Fable 5.1
Anthropic
|
$0.347363 (rounded ~ $0.35) | ↑ 247.4% more | ↑ 1148.6% more |
| #34 |
Claude Mythos 5.1
Anthropic
|
$0.347363 (rounded ~ $0.35) | ↑ 247.4% more | ↑ 1148.6% more |
| #35 |
Claude Fable 5
Anthropic
|
$0.370950 | ↑ 271% more | ↑ 1233.3% more |
| #36 |
Claude Mythos 5
Anthropic
|
$0.370950 | ↑ 271% more | ↑ 1233.3% more |
| #37 |
GPT-5.5
OpenAI
|
$0.375950 (rounded ~ $0.38) | ↑ 276% more | ↑ 1251.3% more |
| #38 |
GPT-6 Astra
OpenAI
|
$0.741900 (rounded ~ $0.74) | ↑ 641.9% more | ↑ 2566.7% more |
| #39 |
GPT-6 Astra
OpenAI
|
$0.741900 (rounded ~ $0.74) | ↑ 641.9% more | ↑ 2566.7% more |
GPT-6 Luna OpenAI
GPT-5.6 Luna OpenAI
Gemini 3.1 Flash Lite Google
Gemini 3.5 Flash-Lite Google
Gemini 2.5 Flash Google
Mistral Large 3 Mistral AI
Gemini 3.8 Flash Google
Gemini 3.6 Flash Google
GPT-5.4 mini OpenAI
Claude Haiku 5.5 Anthropic
Claude Haiku 4.5 Anthropic
Mistral Large 4 Mistral AI
Claude Sonnet 5.5 Anthropic
Claude Sonnet 5 Anthropic
Gemini 4 Argon Google
Gemini 3.1 Flash Google
GPT-5.6 Terra OpenAI
Claude Sonnet 4.6 Anthropic
Claude Opus 5.5 Anthropic
GPT-6.1 Sol OpenAI
GPT-6 Sol OpenAI
GPT-5.6 Sol OpenAI
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
Gemini 2.5 Pro Google
GPT-5.5 Instant OpenAI
Grok 4.3 xAI
Gemini 3.1 Pro Google
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-6 Astra OpenAI
Choosing the Right OCR Strategy for Financial Documents
For healthcare administrators managing invoice reconciliation, the choice between a specialized OCR model and a general-purpose vision model is critical. Mistral OCR 3 is purpose-built for document-heavy workflows, offering high fidelity when extracting text from scanned invoices, receipts, and clinical forms. Its architecture is optimized for dense document layouts, which is often a challenge for standard models.
In contrast, Gemini 3.8 Flash offers a broader multimodal capability. While primarily known for its efficiency in text and video analysis, its vision capabilities are robust enough to handle structured data extraction from PDFs. For teams that need not just extraction, but also summarization or audit-trail generation based on the invoice content, Gemini 3.8 Flash provides a more integrated environment for follow-on reasoning.
Decision Factors Beyond Extraction
When processing 100 invoice PDFs, the primary differentiator is the balance between extraction precision and downstream utility. If your pipeline requires strict adherence to financial schemas and minimal hallucination on tabular data, the specialized approach of Mistral OCR 3 is often superior. However, if your workflow involves complex logic—such as cross-referencing invoice line items with patient records or prior authorization codes—the reasoning capabilities of Gemini 3.8 Flash provide an edge. Consider your existing infrastructure; if you are already utilizing Google Cloud, the integration path for Gemini is likely more efficient, whereas Mistral provides a clean, focused toolset for specific document-parsing tasks.