Claude Sonnet 4.6 Anthropic 1000000
💰 Total Cost Calculation (from Plugin)
Output: $0.003750
Output: $0.003750
Unit: $0.000000
Fees: $0.000000
Advanced Cost Breakdown (from Plugin)
Detailed Cost Analysis (from Plugin)
For 100,000 input tokens and 1,000 output tokens:
- Input Cost: $0.075000 (rounded ~ $0.08)
- Output Cost: $0.003750
- Total Cost: $0.045000 (rounded ~ $0.05)
- Cost per 1K tokens: $0.000446
- Tokens per dollar: 2,244,444 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: 3 minutes, 49.11 seconds
- Latency: 200 milliseconds to first token
- Base Throughput: 450 tokens/second
- Effective Throughput: 441 tokens/second (temperature-adjusted)
Best Use Cases
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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.
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💰 Total Cost Calculation (from Plugin)
Output: $0.001100
Output: $0.001100
Unit: $0.000000
Fees: $0.000000
Advanced Cost Breakdown (from Plugin)
Detailed Cost Analysis (from Plugin)
For 100,000 input tokens and 1,000 output tokens:
- Input Cost: $0.027500 (rounded ~ $0.03)
- Output Cost: $0.001100
- Total Cost: $0.016225 (rounded ~ $0.02)
- Cost per 1K tokens: $0.000161
- Tokens per dollar: 6,224,961 tokens
- Context Window: 200000 tokens
Speed & Performance Analysis
With a processing speed of 180 tokens per second and 280ms time to first token:
- Processing Time: 9 minutes, 32.51 seconds
- Latency: 280 milliseconds to first token
- Base Throughput: 180 tokens/second
- Effective Throughput: 176 tokens/second (temperature-adjusted)
Best Use Cases
Want this applied to YOUR actual stack?
This calculator shows the math for o4-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 →✨ Market Recommendations AI Model Registry
← Back to Claude Sonnet 4.6| Rank | AI Model & Provider | Total Cost | vs Claude Sonnet 4.6 | vs o4-mini |
|---|---|---|---|---|
| 🏆 |
Mistral Small 3
Mistral AI
|
$0.001450 Best Value | ↓ 96.8% cheaper | ↓ 91.1% cheaper |
| 🥈 |
Gemini 3.1 Flash Lite
Google
|
$0.003813 | ↓ 91.5% cheaper | ↓ 76.5% cheaper |
| 🥉 |
Gemini 3.5 Flash-Lite
Google
|
$0.004750 | ↓ 89.4% cheaper | ↓ 70.7% cheaper |
| #4 |
Gemini 2.5 Flash
Google
|
$0.004750 | ↓ 89.4% cheaper | ↓ 70.7% cheaper |
| #5 |
Mistral Large 3
Mistral AI
|
$0.007250 (rounded ~ $0.01) | ↓ 83.9% cheaper | ↓ 55.3% cheaper |
| #6 |
Gemini 3.8 Flash
Google
|
$0.011250 (rounded ~ $0.01) | ↓ 75% cheaper | ↓ 30.7% cheaper |
| #7 |
GPT-5.4 mini
OpenAI
|
$0.011438 (rounded ~ $0.01) | ↓ 74.6% cheaper | ↓ 29.5% cheaper |
| #8 |
o4-mini Deep Research
OpenAI
|
$0.014750 (rounded ~ $0.01) | ↓ 67.2% cheaper | ↓ 9.1% cheaper |
| #9 |
Claude Haiku 4.5
Anthropic
|
$0.015000 (rounded ~ $0.02) | ↓ 66.7% cheaper | ↓ 7.6% cheaper |
| #10 |
Gemini 3.1 Flash
Google
|
$0.015250 (rounded ~ $0.02) | ↓ 66.1% cheaper | ↓ 6% cheaper |
| #11 |
GPT-5.6 Luna
OpenAI
|
$0.015250 (rounded ~ $0.02) | ↓ 66.1% cheaper | ↓ 6% cheaper |
| #12 |
o4-mini
OpenAI
|
$0.016225 (rounded ~ $0.02) | ↓ 63.9% cheaper | Same price |
| #13 |
Gemini 3.6 Flash
Google
|
$0.022500 (rounded ~ $0.02) | ↓ 50% cheaper | ↑ 38.7% more |
| #14 |
Gemini 3.5 Flash
Google
|
$0.022875 (rounded ~ $0.02) | ↓ 49.2% cheaper | ↑ 41% more |
| #15 |
GPT-5.3 Codex Spark
OpenAI
|
$0.027563 (rounded ~ $0.03) | ↓ 38.8% cheaper | ↑ 69.9% more |
| #16 |
GPT-5.3 Instant
OpenAI
|
$0.027563 (rounded ~ $0.03) | ↓ 38.8% cheaper | ↑ 69.9% more |
| #17 |
Claude Sonnet 5
Anthropic
|
$0.030000 | ↓ 33.3% cheaper | ↑ 84.9% more |
| #18 |
GPT-5.6 Terra
OpenAI
|
$0.038125 (rounded ~ $0.04) | ↓ 15.3% cheaper | ↑ 135% more |
| #19 |
Gemini 2.5 Pro
Google
|
$0.039375 | ↓ 12.5% cheaper | ↑ 142.7% more |
| #20 |
Grok 4.3
xAI
|
$0.057000 (rounded ~ $0.06) | ↑ 26.7% more | ↑ 251.3% more |
| #21 |
Grok 4.20 Beta
xAI
|
$0.057000 (rounded ~ $0.06) | ↑ 26.7% more | ↑ 251.3% more |
| #22 |
Gemini 3.1 Pro
Google
|
$0.061000 (rounded ~ $0.06) | ↑ 35.6% more | ↑ 276% more |
| #23 |
Claude Opus 4.7
Anthropic
|
$0.075000 (rounded ~ $0.08) | ↑ 66.7% more | ↑ 362.2% more |
| #24 |
Claude Opus 5
Anthropic
|
$0.075000 (rounded ~ $0.08) | ↑ 66.7% more | ↑ 362.2% more |
| #25 |
Claude Opus 4.8
Anthropic
|
$0.075000 (rounded ~ $0.08) | ↑ 66.7% more | ↑ 362.2% more |
| #26 |
Claude Opus 4.6
Anthropic
|
$0.075000 (rounded ~ $0.08) | ↑ 66.7% more | ↑ 362.2% more |
| #27 |
GPT-5.4
OpenAI
|
$0.076250 (rounded ~ $0.08) | ↑ 69.4% more | ↑ 370% more |
| #28 |
GPT-5.4 Thinking
OpenAI
|
$0.076250 (rounded ~ $0.08) | ↑ 69.4% more | ↑ 370% more |
| #29 |
GPT-5.5 Instant
OpenAI
|
$0.076250 (rounded ~ $0.08) | ↑ 69.4% more | ↑ 370% more |
| #30 |
GPT-5.6 Sol
OpenAI
|
$0.076250 (rounded ~ $0.08) | ↑ 69.4% more | ↑ 370% more |
| #31 |
Claude Fable 5.1
Anthropic
|
$0.140625 | ↑ 212.5% more | ↑ 766.7% more |
| #32 |
Claude Mythos 5.1
Anthropic
|
$0.140625 | ↑ 212.5% more | ↑ 766.7% more |
| #33 |
o3 Deep Research
OpenAI
|
$0.147500 (rounded ~ $0.15) | ↑ 227.8% more | ↑ 809.1% more |
| #34 |
Claude Fable 5
Anthropic
|
$0.150000 | ↑ 233.3% more | ↑ 824.5% more |
| #35 |
Claude Mythos 5
Anthropic
|
$0.150000 | ↑ 233.3% more | ↑ 824.5% more |
| #36 |
GPT-5.5
OpenAI
|
$0.152500 (rounded ~ $0.15) | ↑ 238.9% more | ↑ 839.9% more |
| #37 |
o3 Pro
OpenAI
|
$0.295000 (rounded ~ $0.30) | ↑ 555.6% more | ↑ 1718.2% more |
| #38 |
GPT-6 Astra
OpenAI
|
$0.300000 | ↑ 566.7% more | ↑ 1749% more |
| #39 |
GPT-5.2 Pro
OpenAI
|
$0.330750 | ↑ 635% more | ↑ 1938.5% more |
| #40 |
GPT-5.2 Pro
OpenAI
|
$0.330750 | ↑ 635% more | ↑ 1938.5% more |
Mistral Small 3 Mistral AI
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
GPT-5.4 mini OpenAI
o4-mini Deep Research OpenAI
Claude Haiku 4.5 Anthropic
Gemini 3.1 Flash Google
GPT-5.6 Luna OpenAI
o4-mini OpenAI
Gemini 3.6 Flash Google
Gemini 3.5 Flash Google
GPT-5.3 Codex Spark OpenAI
GPT-5.3 Instant OpenAI
Claude Sonnet 5 Anthropic
GPT-5.6 Terra OpenAI
Gemini 2.5 Pro Google
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
Claude Fable 5.1 Anthropic
Claude Mythos 5.1 Anthropic
o3 Deep Research OpenAI
Claude Fable 5 Anthropic
Claude Mythos 5 Anthropic
GPT-5.5 OpenAI
o3 Pro OpenAI
GPT-6 Astra OpenAI
GPT-5.2 Pro OpenAI
GPT-5.2 Pro OpenAI
Clinical note generation requires balancing deep medical reasoning with operational efficiency. For engineering teams, the choice between Claude Sonnet 4.6 and o4-mini often comes down to the specific nature of your clinical pipeline—whether you prioritize complex multi-step synthesis or rapid, high-volume extraction. Claude Sonnet 4.6 excels when the workload involves nuanced clinical reasoning, such as synthesizing patient history across scattered records or drafting nuanced encounter summaries. Its adaptive thinking engine allows the model to scale its reasoning depth, which is particularly valuable when processing messy, unstructured medical logs where accuracy is paramount to clinician trust. The model’s large context window enables it to hold long-term patient records in memory, facilitating consistent documentation over time.
Conversely, o4-mini is optimized for high-speed, cost-efficient reasoning. It shines in pipelines where the structure of the clinical note is relatively consistent, such as standard progress notes or routine procedure documentation. Its ability to perform structured output generation makes it a strong candidate for backend automation where you need to parse large volumes of data into specific EHR fields. While it may lack the depth of Sonnet for highly complex, multi-modal clinical diagnostic reasoning, it significantly reduces latency in high-throughput environments. For teams scaling their medical documentation tools, we often recommend starting with o4-mini for routine templated tasks and reserving Claude Sonnet 4.6 for specialized encounters that demand sophisticated analytical depth and clinical precision.