GPT-5.4 mini OpenAI
$0.025365 (rounded ~ $0.03)
Total Cost
Vision/Images
✓ Available
Audio Processing
✗ Not Available
Video Analysis
✗ Not Available
Tool Usage
✓ Available
OCR Support
✗ Not Available
Batch API
✓ Available
Caching
✓ Available
90% savings
💰 Total Cost Calculation (from Plugin)
Base Cost (No Optimizations)
$0.030563
Input: $0.028875 (rounded ~ $0.03)
Output: $0.001688
Output: $0.001688
Optimized Cost
$0.025365 (rounded ~ $0.03)
Input: $0.028875 (rounded ~ $0.03)
Output: $0.001688
Unit: $0.000000
Fees: $0.000000
Output: $0.001688
Unit: $0.000000
Fees: $0.000000
Total Savings
$0.005197 (rounded ~ $0.01)
17.0% discount
Advanced Cost Breakdown (from Plugin)
🖼️ Multimodal Input
$0.000000
129,000 tokens
📊 Batch API
50.0% off
Asynchronous processing discount
Multimodal Input Details
🖼️ Images
Count: 250
Resolution: Medium
Tokens: 129,000
Cost: $0.000000
Resolution: Medium
Tokens: 129,000
Cost: $0.000000
Detailed Cost Analysis (from Plugin)
For 25,000 input tokens and 1,500 output tokens:
- Input Cost: $0.028875 (rounded ~ $0.03)
- Output Cost: $0.001688
- Total Cost: $0.025365 (rounded ~ $0.03)
- Cost per 1K tokens: $0.000163
- Tokens per dollar: 6,130,495 tokens
- Context Window: 400000 tokens
Speed & Performance Analysis
With a processing speed of 500 tokens per second and 180ms time to first token:
- Processing Time: 5 minutes, 32.95 seconds
- Latency: 180 milliseconds to first token
- Base Throughput: 500 tokens/second
- Effective Throughput: 467 tokens/second (temperature-adjusted)
Best Use Cases
Comparing lightweight vision models for high-speed archival captioning and metadata generation.
Want this applied to YOUR actual stack?
This calculator shows the math for GPT-5.4 mini. Your decision needs more — current infrastructure, compliance requirements, actual workload patterns, volume tiers — that change which model is right for you.
Get a $39 personalized AI Architecture Audit. PDF tailored to your stack, delivered in under 60 seconds. 7-day no-questions-asked refund.
Get my instant AI audit — $39 →Gemini 2.5 Flash Google 1000000
$0.010409
Total Cost
Vision/Images
✓ Available
Audio Processing
✓ Available
Video Analysis
✓ Available
Tool Usage
✓ Available
OCR Support
✗ Not Available
Batch API
✓ Available
Caching
✓ Available
90% savings
💰 Total Cost Calculation (from Plugin)
Base Cost (No Optimizations)
$0.012488 (rounded ~ $0.01)
Input: $0.011550 (rounded ~ $0.01)
Output: $0.000938
Output: $0.000938
Optimized Cost
$0.010409
Input: $0.011550 (rounded ~ $0.01)
Output: $0.000938
Unit: $0.000000
Fees: $0.000000
Output: $0.000938
Unit: $0.000000
Fees: $0.000000
Total Savings
$0.002079
16.6% discount
Advanced Cost Breakdown (from Plugin)
🖼️ Multimodal Input
$0.000000
129,000 tokens
📊 Batch API
50.0% off
Asynchronous processing discount
Multimodal Input Details
🖼️ Images
Count: 250
Resolution: Medium
Tokens: 129,000
Cost: $0.000000
Resolution: Medium
Tokens: 129,000
Cost: $0.000000
Detailed Cost Analysis (from Plugin)
For 25,000 input tokens and 1,500 output tokens:
- Input Cost: $0.011550 (rounded ~ $0.01)
- Output Cost: $0.000938
- Total Cost: $0.010409
- Cost per 1K tokens: $0.000067
- Tokens per dollar: 14,939,713 tokens
- Context Window: 1000000 tokens
Speed & Performance Analysis
With a processing speed of 600 tokens per second and 120ms time to first token:
- Processing Time: 4 minutes, 37.49 seconds
- Latency: 120 milliseconds to first token
- Base Throughput: 600 tokens/second
- Effective Throughput: 561 tokens/second (temperature-adjusted)
Best Use Cases
Comparing lightweight vision models for high-speed archival captioning and metadata generation.
Want this applied to YOUR actual stack?
This calculator shows the math for Gemini 2.5 Flash. Your decision needs more — current infrastructure, compliance requirements, actual workload patterns, volume tiers — that change which model is right for you.
Get a $39 personalized AI Architecture Audit. PDF tailored to your stack, delivered in under 60 seconds. 7-day no-questions-asked refund.
Get my instant AI audit — $39 →✨ Market Recommendations AI Model Registry
← Back to GPT-5.4 mini
📋 Active Input Parameters
Input Tokens:
25,000
Output Tokens:
1,500
Batch API:
Enabled (50% discount)
Cached Tokens:
20%
Images:
250 (Medium Resolution)
| Rank | AI Model & Provider | Total Cost | vs GPT-5.4 mini | vs Gemini 2.5 Flash |
|---|---|---|---|---|
| 🏆 |
Mistral Small 3
Mistral AI
|
$0.003270 Best Value | ↓ 87.1% cheaper | ↓ 68.6% cheaper |
| 🥈 |
Ministral 3 (14B)
Mistral AI
|
$0.006489 (rounded ~ $0.01) | ↓ 74.4% cheaper | ↓ 37.7% cheaper |
| 🥉 |
Gemini 3.1 Flash Lite
Google
|
$0.008455 (rounded ~ $0.01) | ↓ 66.7% cheaper | ↓ 18.8% cheaper |
| #4 |
Gemini 2.5 Flash
Google
|
$0.010409 | ↓ 59% cheaper | Same price |
| #5 |
Mistral Large 3
Mistral AI
|
$0.016598 (rounded ~ $0.02) | ↓ 34.6% cheaper | ↑ 59.5% more |
| #6 |
o4-mini Deep Research
OpenAI
|
$0.033070 (rounded ~ $0.03) | ↑ 30.4% more | ↑ 217.7% more |
| #7 |
Claude Haiku 4.5
Anthropic
|
$0.033445 (rounded ~ $0.03) | ↑ 31.9% more | ↑ 221.3% more |
| #8 |
Gemini 3.1 Flash
Google
|
$0.033820 (rounded ~ $0.03) | ↑ 33.3% more | ↑ 224.9% more |
| #9 |
o4-mini
OpenAI
|
$0.036377 (rounded ~ $0.04) | ↑ 43.4% more | ↑ 249.5% more |
| #10 |
Grok 4.3
xAI
|
$0.040400 | ↑ 59.3% more | ↑ 288.1% more |
| #11 |
Gemini 3.5 Flash
Google
|
$0.050730 | ↑ 100% more | ↑ 387.4% more |
| #12 |
GPT-5.3 Codex Spark
OpenAI
|
$0.060498 | ↑ 138.5% more | ↑ 481.2% more |
| #13 |
GPT-5.3 Instant
OpenAI
|
$0.060498 | ↑ 138.5% more | ↑ 481.2% more |
| #14 |
Gemini 2.5 Pro
Google
|
$0.086425 (rounded ~ $0.09) | ↑ 240.7% more | ↑ 730.3% more |
| #15 |
Claude Sonnet 4.6
Anthropic
|
$0.100335 | ↑ 295.6% more | ↑ 864% more |
| #16 |
Gemini 3.1 Pro
Google
|
$0.135280 (rounded ~ $0.14) | ↑ 433.3% more | ↑ 1199.7% more |
| #17 |
Claude Opus 4.7
Anthropic
|
$0.167225 (rounded ~ $0.17) | ↑ 559.3% more | ↑ 1506.6% more |
| #18 |
Claude Opus 4.8
Anthropic
|
$0.167225 (rounded ~ $0.17) | ↑ 559.3% more | ↑ 1506.6% more |
| #19 |
Claude Opus 4.6
Anthropic
|
$0.167225 (rounded ~ $0.17) | ↑ 559.3% more | ↑ 1506.6% more |
| #20 |
GPT-5.4
OpenAI
|
$0.169100 | ↑ 566.7% more | ↑ 1524.6% more |
| #21 |
GPT-5.4 Thinking
OpenAI
|
$0.169100 | ↑ 566.7% more | ↑ 1524.6% more |
| #22 |
GPT-5.5 Instant
OpenAI
|
$0.169100 | ↑ 566.7% more | ↑ 1524.6% more |
| #23 |
o3 Deep Research
OpenAI
|
$0.330700 | ↑ 1203.8% more | ↑ 3077.2% more |
| #24 |
GPT-5.5
OpenAI
|
$0.338200 (rounded ~ $0.34) | ↑ 1233.3% more | ↑ 3149.3% more |
| #25 |
o3 Pro
OpenAI
|
$0.661400 (rounded ~ $0.66) | ↑ 2507.5% more | ↑ 6254.4% more |
| #26 |
GPT-5.2 Pro
OpenAI
|
$0.725970 (rounded ~ $0.73) | ↑ 2762.1% more | ↑ 6874.8% more |
| #27 |
GPT-5.2 Pro
OpenAI
|
$0.725970 (rounded ~ $0.73) | ↑ 2762.1% more | ↑ 6874.8% more |
🏆
Mistral Small 3
Mistral Small 3 Mistral AI
$0.003270
vs GPT-5.4 mini:
↓ 87.1%
vs Gemini 2.5 Flash:
↓ 68.6%
🥈
Ministral 3 (14B)
Ministral 3 (14B) Mistral AI
$0.006489 (rounded ~ $0.01)
vs GPT-5.4 mini:
↓ 74.4%
vs Gemini 2.5 Flash:
↓ 37.7%
🥉
Gemini 3.1 Flash Lite
Gemini 3.1 Flash Lite Google
$0.008455 (rounded ~ $0.01)
vs GPT-5.4 mini:
↓ 66.7%
vs Gemini 2.5 Flash:
↓ 18.8%
#4
Gemini 2.5 Flash
Gemini 2.5 Flash Google
$0.010409
vs GPT-5.4 mini:
↓ 59%
vs Gemini 2.5 Flash:
Same
#5
Mistral Large 3
Mistral Large 3 Mistral AI
$0.016598 (rounded ~ $0.02)
vs GPT-5.4 mini:
↓ 34.6%
vs Gemini 2.5 Flash:
↑ 59.5%
#6
o4-mini Deep Research
o4-mini Deep Research OpenAI
$0.033070 (rounded ~ $0.03)
vs GPT-5.4 mini:
↑ 30.4%
vs Gemini 2.5 Flash:
↑ 217.7%
#7
Claude Haiku 4.5
Claude Haiku 4.5 Anthropic
$0.033445 (rounded ~ $0.03)
vs GPT-5.4 mini:
↑ 31.9%
vs Gemini 2.5 Flash:
↑ 221.3%
#8
Gemini 3.1 Flash
Gemini 3.1 Flash Google
$0.033820 (rounded ~ $0.03)
vs GPT-5.4 mini:
↑ 33.3%
vs Gemini 2.5 Flash:
↑ 224.9%
#9
o4-mini
o4-mini OpenAI
$0.036377 (rounded ~ $0.04)
vs GPT-5.4 mini:
↑ 43.4%
vs Gemini 2.5 Flash:
↑ 249.5%
#10
Grok 4.3
Grok 4.3 xAI
$0.040400
vs GPT-5.4 mini:
↑ 59.3%
vs Gemini 2.5 Flash:
↑ 288.1%
#11
Gemini 3.5 Flash
Gemini 3.5 Flash Google
$0.050730
vs GPT-5.4 mini:
↑ 100%
vs Gemini 2.5 Flash:
↑ 387.4%
#12
GPT-5.3 Codex Spark
GPT-5.3 Codex Spark OpenAI
$0.060498
vs GPT-5.4 mini:
↑ 138.5%
vs Gemini 2.5 Flash:
↑ 481.2%
#13
GPT-5.3 Instant
GPT-5.3 Instant OpenAI
$0.060498
vs GPT-5.4 mini:
↑ 138.5%
vs Gemini 2.5 Flash:
↑ 481.2%
#14
Gemini 2.5 Pro
Gemini 2.5 Pro Google
$0.086425 (rounded ~ $0.09)
vs GPT-5.4 mini:
↑ 240.7%
vs Gemini 2.5 Flash:
↑ 730.3%
#15
Claude Sonnet 4.6
Claude Sonnet 4.6 Anthropic
$0.100335
vs GPT-5.4 mini:
↑ 295.6%
vs Gemini 2.5 Flash:
↑ 864%
#16
Gemini 3.1 Pro
Gemini 3.1 Pro Google
$0.135280 (rounded ~ $0.14)
vs GPT-5.4 mini:
↑ 433.3%
vs Gemini 2.5 Flash:
↑ 1199.7%
#17
Claude Opus 4.7
Claude Opus 4.7 Anthropic
$0.167225 (rounded ~ $0.17)
vs GPT-5.4 mini:
↑ 559.3%
vs Gemini 2.5 Flash:
↑ 1506.6%
#18
Claude Opus 4.8
Claude Opus 4.8 Anthropic
$0.167225 (rounded ~ $0.17)
vs GPT-5.4 mini:
↑ 559.3%
vs Gemini 2.5 Flash:
↑ 1506.6%
#19
Claude Opus 4.6
Claude Opus 4.6 Anthropic
$0.167225 (rounded ~ $0.17)
vs GPT-5.4 mini:
↑ 559.3%
vs Gemini 2.5 Flash:
↑ 1506.6%
#20
GPT-5.4
GPT-5.4 OpenAI
$0.169100
vs GPT-5.4 mini:
↑ 566.7%
vs Gemini 2.5 Flash:
↑ 1524.6%
#21
GPT-5.4 Thinking
GPT-5.4 Thinking OpenAI
$0.169100
vs GPT-5.4 mini:
↑ 566.7%
vs Gemini 2.5 Flash:
↑ 1524.6%
#22
GPT-5.5 Instant
GPT-5.5 Instant OpenAI
$0.169100
vs GPT-5.4 mini:
↑ 566.7%
vs Gemini 2.5 Flash:
↑ 1524.6%
#23
o3 Deep Research
o3 Deep Research OpenAI
$0.330700
vs GPT-5.4 mini:
↑ 1203.8%
vs Gemini 2.5 Flash:
↑ 3077.2%
#24
GPT-5.5
GPT-5.5 OpenAI
$0.338200 (rounded ~ $0.34)
vs GPT-5.4 mini:
↑ 1233.3%
vs Gemini 2.5 Flash:
↑ 3149.3%
#25
o3 Pro
o3 Pro OpenAI
$0.661400 (rounded ~ $0.66)
vs GPT-5.4 mini:
↑ 2507.5%
vs Gemini 2.5 Flash:
↑ 6254.4%
#26
GPT-5.2 Pro
GPT-5.2 Pro OpenAI
$0.725970 (rounded ~ $0.73)
vs GPT-5.4 mini:
↑ 2762.1%
vs Gemini 2.5 Flash:
↑ 6874.8%
#27
GPT-5.2 Pro
GPT-5.2 Pro OpenAI
$0.725970 (rounded ~ $0.73)
vs GPT-5.4 mini:
↑ 2762.1%
vs Gemini 2.5 Flash:
↑ 6874.8%
✨ How recommendations work (v8.6.0): We scan all active models in the registry and only include those that support ALL your current inputs. For token-based models, we check if they can handle your token counts. For special pricing models (OCR, video, audio), we verify they have the correct pricing structure. Features marked requested were in your inputs but not supported by that model. Now using official provider pricing without reseller markups.
Balancing Vision Accuracy and Cost
When prototyping an archive digitization pipeline, creators must balance the quality of vision processing against the operational overhead of generating descriptive metadata. GPT-5.4 mini and Gemini 2.5 Flash represent two of the most efficient pathways for creators looking to caption 250 images from an archival collection. Both models offer advanced vision capabilities, but they differ significantly in their qualitative approach to image understanding.
GPT-5.4 mini provides a highly refined vision-to-text bridge, excelling at capturing structured data from archival images and maintaining a coherent narrative tone. It is particularly effective when the goal is to generate metadata that aligns with specific educational standards. On the other hand, Gemini 2.5 Flash is built for speed and high-volume throughput. Its integration with the broader Google ecosystem makes it a strong contender for creators who already utilize Cloud Storage for their scanned archives. While both models are positioned for efficiency, the choice often hinges on the specific complexity of the images. GPT-5.4 mini tends to offer slightly more nuanced reasoning for dense visual information, whereas Gemini 2.5 Flash is the preferred choice for rapid, low-latency identification across large datasets.
Frequently Asked Questions
How accurate are these AI model cost calculations?
Our calculations are based on official pricing from each provider (Google, OpenAI, Anthropic, Meta, xAI, Perplexity, DeepSeek, Mistral) and are updated regularly.
We account for all factors including multimodal inputs, caching discounts, batch API pricing, tool usage multipliers, OCR processing, audio minutes, silence fees, and research mode pricing.
Note: Reseller markups and dedicated instance multipliers have been removed to reflect official provider pricing.
How are image tokens calculated?
Images are tokenized based on resolution: Low: 85 tokens, Medium: 170 tokens, High: 255 tokens, Full: 765 tokens per image. Some models (like Llama 4 Maverick) use tile-based encoding with 1,610 tokens/image (standard) or 8,050 tokens/image (high-res).
How does prompt caching work?
Caching discounts vary by provider: Google and OpenAI offer 90% discounts on cached input tokens. Anthropic uses write (1.25x) and read (0.10x) multipliers. Savings are applied to the token portion only, not unit-based fees.
How do Market Recommendations work (v8.6.0)?
Our recommendation engine scans the entire model registry and only includes models that support ALL your current input parameters (tokens, images, video, audio, OCR, tools, batch API, etc.). It calculates exact costs with your settings and sorts by price, showing you the best value options that can handle your complete workflow. Special pricing models (OCR, video, audio, image generation) are properly handled and only appear when their specific input types are requested. v8.6.0 removes reseller markups (20% buffer) and dedicated instance multipliers to reflect official provider pricing.
What is the YemHub AI Calculator Tool?
The YemHub AI Calculator is the most comprehensive tool for estimating costs and comparing performance metrics across 50+ AI models. It calculates token-based pricing, analyzes multimodal processing, accounts for state-dependent pricing (context cliffs, tiered tunnels), provides optimization recommendations, and now offers intelligent market matching to find the best alternatives for your specific needs.