GPT-5.4 Mini OpenAI
💰 Total Cost Calculation (from Plugin)
Output: $0.009000
Output: $0.009000
Unit: $0.000000
Fees: $0.000000
Advanced Cost Breakdown (from Plugin)
Detailed Cost Analysis (from Plugin)
For 128,000 input tokens and 8,000 output tokens:
- Input Cost: $0.024000 (rounded ~ $0.02)
- Output Cost: $0.009000
- Total Cost: $0.028680 (rounded ~ $0.03)
- Cost per 1K tokens: $0.000211
- Tokens per dollar: 4,741,980 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: 4 minutes, 51.22 seconds
- Latency: 180 milliseconds to first token
- Base Throughput: 500 tokens/second
- Effective Throughput: 467 tokens/second (temperature-adjusted)
Best Use Cases
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.
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Get my instant AI audit — $39 →Claude Sonnet 4.6 Anthropic 1000000
💰 Total Cost Calculation (from Plugin)
Output: $0.030000
Output: $0.030000
Unit: $0.000000
Fees: $0.000000
Advanced Cost Breakdown (from Plugin)
Detailed Cost Analysis (from Plugin)
For 128,000 input tokens and 8,000 output tokens:
- Input Cost: $0.096000 (rounded ~ $0.10)
- Output Cost: $0.030000
- Total Cost: $0.108720 (rounded ~ $0.11)
- Cost per 1K tokens: $0.000799
- Tokens per dollar: 1,250,920 tokens
- Context Window: 1000000 tokens
Speed & Performance Analysis
With a processing speed of 450 tokens per second and 200ms time to first token:
- Processing Time: 5 minutes, 23.56 seconds
- Latency: 200 milliseconds to first token
- Base Throughput: 450 tokens/second
- Effective Throughput: 421 tokens/second (temperature-adjusted)
Best Use Cases
Want this applied to YOUR actual stack?
This calculator shows the math for Claude Sonnet 4.6. 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| Rank | AI Model & Provider | Total Cost | vs GPT-5.4 Mini | vs Claude Sonnet 4.6 |
|---|---|---|---|---|
| 🏆 |
Gemini 3.1 Flash Lite
Google
|
$0.009560 Best Value | ↓ 66.7% cheaper | ↓ 91.2% cheaper |
| 🥈 |
Gemini 3.5 Flash-Lite
Google
|
$0.012872 (rounded ~ $0.01) | ↓ 55.1% cheaper | ↓ 88.2% cheaper |
| 🥉 |
Gemini 2.5 Flash
Google
|
$0.012872 (rounded ~ $0.01) | ↓ 55.1% cheaper | ↓ 88.2% cheaper |
| #4 |
Mistral Large 3
Mistral AI
|
$0.016120 (rounded ~ $0.02) | ↓ 43.8% cheaper | ↓ 85.2% cheaper |
| #5 |
Gemini 3.8 Flash
Google
|
$0.027180 (rounded ~ $0.03) | ↓ 5.2% cheaper | ↓ 75% cheaper |
| #6 |
Claude Haiku 4.5
Anthropic
|
$0.036240 (rounded ~ $0.04) | ↑ 26.4% more | ↓ 66.7% cheaper |
| #7 |
o4-mini
OpenAI
|
$0.037664 (rounded ~ $0.04) | ↑ 31.3% more | ↓ 65.4% cheaper |
| #8 |
Gemini 3.1 Flash
Google
|
$0.038240 (rounded ~ $0.04) | ↑ 33.3% more | ↓ 64.8% cheaper |
| #9 |
GPT-5.6 Luna
OpenAI
|
$0.038240 (rounded ~ $0.04) | ↑ 33.3% more | ↓ 64.8% cheaper |
| #10 |
Gemini 3.6 Flash
Google
|
$0.054360 (rounded ~ $0.05) | ↑ 89.5% more | ↓ 50% cheaper |
| #11 |
Gemini 3.5 Flash
Google
|
$0.057360 (rounded ~ $0.06) | ↑ 100% more | ↓ 47.2% cheaper |
| #12 |
Claude Sonnet 5
Anthropic
|
$0.072480 (rounded ~ $0.07) | ↑ 152.7% more | ↓ 33.3% cheaper |
| #13 |
GPT-5.3 Codex Spark
OpenAI
|
$0.073920 (rounded ~ $0.07) | ↑ 157.7% more | ↓ 32% cheaper |
| #14 |
GPT-5.6 Terra
OpenAI
|
$0.095600 (rounded ~ $0.10) | ↑ 233.3% more | ↓ 12.1% cheaper |
| #15 |
Gemini 2.5 Pro
Google
|
$0.105600 (rounded ~ $0.11) | ↑ 268.2% more | ↓ 2.9% cheaper |
| #16 |
Claude Sonnet 4.6
Anthropic
|
$0.108720 (rounded ~ $0.11) | ↑ 279.1% more | Same price |
| #17 |
Grok 4.3
xAI
|
$0.120960 | ↑ 321.8% more | ↑ 11.3% more |
| #18 |
Grok 4.20 Beta
xAI
|
$0.120960 | ↑ 321.8% more | ↑ 11.3% more |
| #19 |
Gemini 3.1 Pro
Google
|
$0.152960 (rounded ~ $0.15) | ↑ 433.3% more | ↑ 40.7% more |
| #20 |
Claude Opus 4.7
Anthropic
|
$0.181200 (rounded ~ $0.18) | ↑ 531.8% more | ↑ 66.7% more |
| #21 |
Claude Opus 5
Anthropic
|
$0.181200 (rounded ~ $0.18) | ↑ 531.8% more | ↑ 66.7% more |
| #22 |
Claude Opus 4.8
Anthropic
|
$0.181200 (rounded ~ $0.18) | ↑ 531.8% more | ↑ 66.7% more |
| #23 |
Claude Opus 4.6
Anthropic
|
$0.181200 (rounded ~ $0.18) | ↑ 531.8% more | ↑ 66.7% more |
| #24 |
GPT-5.4
OpenAI
|
$0.191200 (rounded ~ $0.19) | ↑ 566.7% more | ↑ 75.9% more |
| #25 |
GPT-5.4 Thinking
OpenAI
|
$0.191200 (rounded ~ $0.19) | ↑ 566.7% more | ↑ 75.9% more |
| #26 |
GPT-5.5 Instant
OpenAI
|
$0.191200 (rounded ~ $0.19) | ↑ 566.7% more | ↑ 75.9% more |
| #27 |
GPT-5.6 Sol
OpenAI
|
$0.191200 (rounded ~ $0.19) | ↑ 566.7% more | ↑ 75.9% more |
| #28 |
o3 Deep Research
OpenAI
|
$0.342400 (rounded ~ $0.34) | ↑ 1093.9% more | ↑ 214.9% more |
| #29 |
Claude Fable 5.1
Anthropic
|
$0.357600 (rounded ~ $0.36) | ↑ 1146.9% more | ↑ 228.9% more |
| #30 |
Claude Mythos 5.1
Anthropic
|
$0.357600 (rounded ~ $0.36) | ↑ 1146.9% more | ↑ 228.9% more |
| #31 |
Claude Fable 5
Anthropic
|
$0.362400 (rounded ~ $0.36) | ↑ 1163.6% more | ↑ 233.3% more |
| #32 |
Claude Mythos 5
Anthropic
|
$0.362400 (rounded ~ $0.36) | ↑ 1163.6% more | ↑ 233.3% more |
| #33 |
GPT-5.5
OpenAI
|
$0.382400 (rounded ~ $0.38) | ↑ 1233.3% more | ↑ 251.7% more |
| #34 |
o3 Pro
OpenAI
|
$0.684800 (rounded ~ $0.68) | ↑ 2287.7% more | ↑ 529.9% more |
| #35 |
GPT-6 Astra
OpenAI
|
$0.724800 (rounded ~ $0.72) | ↑ 2427.2% more | ↑ 566.7% more |
| #36 |
GPT-6 Astra
OpenAI
|
$0.724800 (rounded ~ $0.72) | ↑ 2427.2% more | ↑ 566.7% more |
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
Claude Haiku 4.5 Anthropic
o4-mini OpenAI
Gemini 3.1 Flash Google
GPT-5.6 Luna OpenAI
Gemini 3.6 Flash Google
Gemini 3.5 Flash Google
Claude Sonnet 5 Anthropic
GPT-5.3 Codex Spark OpenAI
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-6 Astra OpenAI
Choosing the Right Engine for Healthcare Script Production
For healthcare administrators producing high volumes of video scripts—such as patient education, clinical training, or regulatory updates—selecting the correct AI model involves balancing nuanced communication against production efficiency. When managing a pipeline of 128,000 tokens per month, the choice between GPT-5.4 Mini and Claude Sonnet 4.6 often comes down to the specific nature of your content.
Claude Sonnet 4.6 has gained a reputation in creative and professional domains for its ability to maintain a sophisticated, empathetic, and structured tone. In healthcare environments where the script must convey complex clinical information while remaining accessible and patient-friendly, Claude often requires fewer iterative prompts to hit the right balance of warmth and accuracy. Its reasoning capabilities make it highly effective for longer, more complex scripts that require deep logical flow and adherence to strict messaging guidelines.
GPT-5.4 Mini, by contrast, is a powerhouse for operational scalability. If your video production strategy relies on templates, rapid-fire generation of procedural training scripts, or high-volume administrative messaging, this model provides the necessary speed and consistency. It is particularly well-suited for pipelines where you need to integrate scripts into larger, automated workflows that prioritize throughput. While it may require slightly more detailed prompting to achieve the same stylistic polish as Claude for highly sensitive patient communication, its performance across general administrative tasks is reliable. For administrators, the decision hinges on whether your priority is the ‘human’ touch required for patient engagement or the raw scalability required for internal operational content.