Claude Opus 4.7 Anthropic 1000000
💰 Total Cost Calculation (from Plugin)
Output: $0.012500 (rounded ~ $0.01)
Output: $0.012500 (rounded ~ $0.01)
Unit: $0.000000
Fees: $0.000000
Advanced Cost Breakdown (from Plugin)
Detailed Cost Analysis (from Plugin)
For 50,000 input tokens and 2,000 output tokens:
- Input Cost: $0.062500 (rounded ~ $0.06)
- Output Cost: $0.012500 (rounded ~ $0.01)
- Total Cost: $0.046875 (rounded ~ $0.05)
- Cost per 1K tokens: $0.000901
- Tokens per dollar: 1,109,333 tokens
- Context Window: 1000000 tokens
Speed & Performance Analysis
With a processing speed of 260 tokens per second and 400ms time to first token:
- Processing Time: 3 minutes, 24.18 seconds
- Latency: 400 milliseconds to first token
- Base Throughput: 260 tokens/second
- Effective Throughput: 255 tokens/second (temperature-adjusted)
Best Use Cases
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This calculator shows the math for Claude Opus 4.7. 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: $0.012000 (rounded ~ $0.01)
Output: $0.012000 (rounded ~ $0.01)
Unit: $0.000000
Fees: $0.000000
Advanced Cost Breakdown (from Plugin)
Detailed Cost Analysis (from Plugin)
For 50,000 input tokens and 2,000 output tokens:
- Input Cost: $0.050000
- Output Cost: $0.012000 (rounded ~ $0.01)
- Total Cost: $0.039500
- Cost per 1K tokens: $0.000760
- Tokens per dollar: 1,316,456 tokens
- Context Window: 1000000 tokens
Speed & Performance Analysis
With a processing speed of 400 tokens per second and 220ms time to first token:
- Processing Time: 2 minutes, 12.78 seconds
- Latency: 220 milliseconds to first token
- Base Throughput: 400 tokens/second
- Effective Throughput: 392 tokens/second (temperature-adjusted)
Best Use Cases
Want this applied to YOUR actual stack?
This calculator shows the math for Gemini 3.1 Pro. 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 Opus 4.7| Rank | AI Model & Provider | Total Cost | vs Claude Opus 4.7 | vs Gemini 3.1 Pro |
|---|---|---|---|---|
| 🏆 |
Mistral Small 3
Mistral AI
|
$0.000838 Best Value | ↓ 98.2% cheaper | ↓ 97.9% cheaper |
| 🥈 |
Devstral Small 2
Mistral AI
|
$0.000838 | ↓ 98.2% cheaper | ↓ 97.9% cheaper |
| 🥉 |
Ministral 3 (14B)
Mistral AI
|
$0.001475 | ↓ 96.9% cheaper | ↓ 96.3% cheaper |
| #4 |
Gemini 3.1 Flash Lite
Google
|
$0.002469 | ↓ 94.7% cheaper | ↓ 93.8% cheaper |
| #5 |
Nemotron 3 Super
NVIDIA
|
$0.002473 | ↓ 94.7% cheaper | ↓ 93.7% cheaper |
| #6 |
Devstral 2
Mistral AI
|
$0.003200 | ↓ 93.2% cheaper | ↓ 91.9% cheaper |
| #7 |
Gemini 3.5 Flash-Lite
Google
|
$0.003313 | ↓ 92.9% cheaper | ↓ 91.6% cheaper |
| #8 |
Gemini 2.5 Flash
Google
|
$0.003313 | ↓ 92.9% cheaper | ↓ 91.6% cheaper |
| #9 |
Mistral Large 3
Mistral AI
|
$0.004188 | ↓ 91.1% cheaper | ↓ 89.4% cheaper |
| #10 |
Gemini 3.8 Flash
Google
|
$0.007031 (rounded ~ $0.01) | ↓ 85% cheaper | ↓ 82.2% cheaper |
| #11 |
GPT-5.4 mini
OpenAI
|
$0.007406 (rounded ~ $0.01) | ↓ 84.2% cheaper | ↓ 81.3% cheaper |
| #12 |
o4-mini Deep Research
OpenAI
|
$0.008875 (rounded ~ $0.01) | ↓ 81.1% cheaper | ↓ 77.5% cheaper |
| #13 |
Claude Haiku 4.5
Anthropic
|
$0.009375 | ↓ 80% cheaper | ↓ 76.3% cheaper |
| #14 |
o4-mini
OpenAI
|
$0.009763 | ↓ 79.2% cheaper | ↓ 75.3% cheaper |
| #15 |
Gemini 3.1 Flash
Google
|
$0.009875 | ↓ 78.9% cheaper | ↓ 75% cheaper |
| #16 |
GPT-5.6 Luna
OpenAI
|
$0.009875 | ↓ 78.9% cheaper | ↓ 75% cheaper |
| #17 |
Gemini 3.6 Flash
Google
|
$0.014063 (rounded ~ $0.01) | ↓ 70% cheaper | ↓ 64.4% cheaper |
| #18 |
Gemini 3.5 Flash
Google
|
$0.014813 (rounded ~ $0.01) | ↓ 68.4% cheaper | ↓ 62.5% cheaper |
| #19 |
Magistral Medium
Mistral AI
|
$0.016250 (rounded ~ $0.02) | ↓ 65.3% cheaper | ↓ 58.9% cheaper |
| #20 |
Claude Sonnet 5
Anthropic
|
$0.018750 (rounded ~ $0.02) | ↓ 60% cheaper | ↓ 52.5% cheaper |
| #21 |
GPT-5.3 Codex Spark
OpenAI
|
$0.019031 | ↓ 59.4% cheaper | ↓ 51.8% cheaper |
| #22 |
GPT-5.3 Instant
OpenAI
|
$0.019031 | ↓ 59.4% cheaper | ↓ 51.8% cheaper |
| #23 |
GPT-5.6 Terra
OpenAI
|
$0.024688 (rounded ~ $0.02) | ↓ 47.3% cheaper | ↓ 37.5% cheaper |
| #24 |
Gemini 2.5 Pro
Google
|
$0.027188 (rounded ~ $0.03) | ↓ 42% cheaper | ↓ 31.2% cheaper |
| #25 |
Claude Sonnet 4.6
Anthropic
|
$0.028125 (rounded ~ $0.03) | ↓ 40% cheaper | ↓ 28.8% cheaper |
| #26 |
Grok 4.3
xAI
|
$0.031500 (rounded ~ $0.03) | ↓ 32.8% cheaper | ↓ 20.3% cheaper |
| #27 |
Grok 4.20 Beta
xAI
|
$0.031500 (rounded ~ $0.03) | ↓ 32.8% cheaper | ↓ 20.3% cheaper |
| #28 |
Gemini 3.1 Pro
Google
|
$0.039500 | ↓ 15.7% cheaper | Same price |
| #29 |
Claude Opus 5
Anthropic
|
$0.046875 (rounded ~ $0.05) | Same price | ↑ 18.7% more |
| #30 |
Claude Opus 4.8
Anthropic
|
$0.046875 (rounded ~ $0.05) | Same price | ↑ 18.7% more |
| #31 |
Claude Opus 4.6
Anthropic
|
$0.046875 (rounded ~ $0.05) | Same price | ↑ 18.7% more |
| #32 |
GPT-5.4
OpenAI
|
$0.049375 | ↑ 5.3% more | ↑ 25% more |
| #33 |
GPT-5.4 Thinking
OpenAI
|
$0.049375 | ↑ 5.3% more | ↑ 25% more |
| #34 |
GPT-5.5 Instant
OpenAI
|
$0.049375 | ↑ 5.3% more | ↑ 25% more |
| #35 |
GPT-5.6 Sol
OpenAI
|
$0.049375 | ↑ 5.3% more | ↑ 25% more |
| #36 |
o3 Deep Research
OpenAI
|
$0.088750 (rounded ~ $0.09) | ↑ 89.3% more | ↑ 124.7% more |
| #37 |
Claude Fable 5.1
Anthropic
|
$0.089063 | ↑ 90% more | ↑ 125.5% more |
| #38 |
Claude Mythos 5.1
Anthropic
|
$0.089063 | ↑ 90% more | ↑ 125.5% more |
| #39 |
Claude Fable 5
Anthropic
|
$0.093750 (rounded ~ $0.09) | ↑ 100% more | ↑ 137.3% more |
| #40 |
Claude Mythos 5
Anthropic
|
$0.093750 (rounded ~ $0.09) | ↑ 100% more | ↑ 137.3% more |
| #41 |
GPT-5.5
OpenAI
|
$0.098750 (rounded ~ $0.10) | ↑ 110.7% more | ↑ 150% more |
| #42 |
o3 Pro
OpenAI
|
$0.177500 (rounded ~ $0.18) | ↑ 278.7% more | ↑ 349.4% more |
| #43 |
GPT-6 Astra
OpenAI
|
$0.187500 (rounded ~ $0.19) | ↑ 300% more | ↑ 374.7% more |
| #44 |
GPT-5.2 Pro
OpenAI
|
$0.228375 (rounded ~ $0.23) | ↑ 387.2% more | ↑ 478.2% more |
| #45 |
GPT-5.2 Pro
OpenAI
|
$0.228375 (rounded ~ $0.23) | ↑ 387.2% more | ↑ 478.2% more |
Mistral Small 3 Mistral AI
Devstral Small 2 Mistral AI
Ministral 3 (14B) Mistral AI
Gemini 3.1 Flash Lite Google
Nemotron 3 Super NVIDIA
Devstral 2 Mistral AI
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
o4-mini OpenAI
Gemini 3.1 Flash Google
GPT-5.6 Luna OpenAI
Gemini 3.6 Flash Google
Gemini 3.5 Flash Google
Magistral Medium Mistral AI
Claude Sonnet 5 Anthropic
GPT-5.3 Codex Spark OpenAI
GPT-5.3 Instant 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 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-5.2 Pro OpenAI
GPT-5.2 Pro OpenAI
For a localization manager overseeing clinical note generation across 12 languages, the primary challenge is balancing nuanced medical terminology with consistent structural formatting. When processing 50K-token clinical notes at a scale of 100 million tokens monthly, the choice between these models often comes down to reasoning style and multimodal handling.
Claude Opus 4.7 is a powerhouse for structured, highly nuanced clinical reasoning. It excels at maintaining tone and idiomatic accuracy when translating complex medical narratives into secondary languages. Its strong adherence to instructions ensures that sensitive patient data remains formatted correctly, which is critical for compliance in a global healthcare environment. Localization teams often prefer Opus for its ability to handle long-form, complex documentation without losing the thread of the clinical encounter.
Gemini 3.1 Pro, conversely, offers distinct advantages in handling multimodal inputs, such as audio-heavy clinical dictations. If your notes are derived from raw audio transcription, Gemini’s native ability to process audio data can reduce the need for upstream transcription pipelines, streamlining the localization workflow. Its speed is also notable for high-volume pipelines. However, when comparing the two, consider that Opus often provides more stable, predictable reasoning for highly technical, specialized medical content, whereas Gemini offers significant efficiency for high-velocity, multimodal environments. Evaluate your team’s specific need for audio-input processing versus text-heavy clinical reasoning to decide which model architecture best supports your global documentation strategy.