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 500,000 input tokens and 1,000 output tokens:
- Input Cost: $0.375000 (rounded ~ $0.38)
- Output Cost: $0.003750
- Total Cost: $0.176250 (rounded ~ $0.18)
- Cost per 1K tokens: $0.000352
- Tokens per dollar: 2,842,553 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: 19 minutes, 6.91 seconds
- Latency: 200 milliseconds to first token
- Base Throughput: 450 tokens/second
- Effective Throughput: 437 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.
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Get my instant AI audit — $39 →DeepSeek V4 Flash DeepSeek 1000000
💰 Total Cost Calculation (from Plugin)
Output: $0.000280
Output: $0.000280
Unit: $0.000000
Fees: $0.000000
Detailed Cost Analysis (from Plugin)
For 500,000 input tokens and 1,000 output tokens:
- Input Cost: $0.070000
- Output Cost: $0.000280
- Total Cost: $0.029120
- Cost per 1K tokens: $0.000058
- Tokens per dollar: 17,204,670 tokens
- Context Window: 1000000 tokens
Speed & Performance Analysis
With a processing speed of 650 tokens per second and 95ms time to first token:
- Processing Time: 13 minutes, 14.07 seconds
- Latency: 95 milliseconds to first token
- Base Throughput: 650 tokens/second
- Effective Throughput: 631 tokens/second (temperature-adjusted)
Best Use Cases
Want this applied to YOUR actual stack?
This calculator shows the math for DeepSeek V4 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 Claude Sonnet 4.6| Rank | AI Model & Provider | Total Cost | vs Claude Sonnet 4.6 | vs DeepSeek V4 Flash |
|---|---|---|---|---|
| 🏆 |
Gemini 3.1 Flash Lite
Google
|
$0.014750 (rounded ~ $0.01) Best Value | ↓ 91.6% cheaper | ↓ 49.3% cheaper |
| 🥈 |
Gemini 3.5 Flash-Lite
Google
|
$0.017875 (rounded ~ $0.02) | ↓ 89.9% cheaper | ↓ 38.6% cheaper |
| 🥉 |
Gemini 2.5 Flash
Google
|
$0.017875 (rounded ~ $0.02) | ↓ 89.9% cheaper | ↓ 38.6% cheaper |
| #4 |
Gemini 3.8 Flash
Google
|
$0.044063 (rounded ~ $0.04) | ↓ 75% cheaper | ↑ 51.3% more |
| #5 |
GPT-5.6 Luna
OpenAI
|
$0.059000 | ↓ 66.5% cheaper | ↑ 102.6% more |
| #6 |
Gemini 3.6 Flash
Google
|
$0.088125 (rounded ~ $0.09) | ↓ 50% cheaper | ↑ 202.6% more |
| #7 |
Gemini 3.5 Flash
Google
|
$0.088500 (rounded ~ $0.09) | ↓ 49.8% cheaper | ↑ 203.9% more |
| #8 |
Claude Sonnet 5
Anthropic
|
$0.117500 (rounded ~ $0.12) | ↓ 33.3% cheaper | ↑ 303.5% more |
| #9 |
Gemini 3.1 Flash
Google
|
$0.118000 (rounded ~ $0.12) | ↓ 33% cheaper | ↑ 305.2% more |
| #10 |
GPT-5.6 Terra
OpenAI
|
$0.147500 (rounded ~ $0.15) | ↓ 16.3% cheaper | ↑ 406.5% more |
| #11 |
Claude Opus 4.7
Anthropic
|
$0.293750 (rounded ~ $0.29) | ↑ 66.7% more | ↑ 908.8% more |
| #12 |
Claude Opus 5
Anthropic
|
$0.293750 (rounded ~ $0.29) | ↑ 66.7% more | ↑ 908.8% more |
| #13 |
Claude Opus 4.8
Anthropic
|
$0.293750 (rounded ~ $0.29) | ↑ 66.7% more | ↑ 908.8% more |
| #14 |
Claude Opus 4.6
Anthropic
|
$0.293750 (rounded ~ $0.29) | ↑ 66.7% more | ↑ 908.8% more |
| #15 |
Gemini 2.5 Pro
Google
|
$0.295000 (rounded ~ $0.30) | ↑ 67.4% more | ↑ 913% more |
| #16 |
GPT-5.6 Sol
OpenAI
|
$0.295000 (rounded ~ $0.30) | ↑ 67.4% more | ↑ 913% more |
| #17 |
Grok 4.3
xAI
|
$0.464000 (rounded ~ $0.46) | ↑ 163.3% more | ↑ 1493.4% more |
| #18 |
Grok 4.20 Beta
xAI
|
$0.464000 (rounded ~ $0.46) | ↑ 163.3% more | ↑ 1493.4% more |
| #19 |
Gemini 3.1 Pro
Google
|
$0.469000 | ↑ 166.1% more | ↑ 1510.6% more |
| #20 |
Claude Fable 5.1
Anthropic
|
$0.531250 (rounded ~ $0.53) | ↑ 201.4% more | ↑ 1724.3% more |
| #21 |
Claude Mythos 5.1
Anthropic
|
$0.531250 (rounded ~ $0.53) | ↑ 201.4% more | ↑ 1724.3% more |
| #22 |
GPT-5.4
OpenAI
|
$0.586250 (rounded ~ $0.59) | ↑ 232.6% more | ↑ 1913.2% more |
| #23 |
GPT-5.4 Thinking
OpenAI
|
$0.586250 (rounded ~ $0.59) | ↑ 232.6% more | ↑ 1913.2% more |
| #24 |
Claude Fable 5
Anthropic
|
$0.587500 (rounded ~ $0.59) | ↑ 233.3% more | ↑ 1917.5% more |
| #25 |
Claude Mythos 5
Anthropic
|
$0.587500 (rounded ~ $0.59) | ↑ 233.3% more | ↑ 1917.5% more |
| #26 |
GPT-5.5
OpenAI
|
$1.172500 (rounded ~ $1.17) | ↑ 565.2% more | ↑ 3926.4% more |
| #27 |
GPT-6 Astra
OpenAI
|
$2.350000 | ↑ 1233.3% more | ↑ 7970.1% more |
| #28 |
GPT-6 Astra
OpenAI
|
$2.350000 | ↑ 1233.3% more | ↑ 7970.1% more |
Gemini 3.1 Flash Lite Google
Gemini 3.5 Flash-Lite Google
Gemini 2.5 Flash Google
Gemini 3.8 Flash Google
GPT-5.6 Luna OpenAI
Gemini 3.6 Flash Google
Gemini 3.5 Flash Google
Claude Sonnet 5 Anthropic
Gemini 3.1 Flash Google
GPT-5.6 Terra OpenAI
Claude Opus 4.7 Anthropic
Claude Opus 5 Anthropic
Claude Opus 4.8 Anthropic
Claude Opus 4.6 Anthropic
Gemini 2.5 Pro Google
GPT-5.6 Sol OpenAI
Grok 4.3 xAI
Grok 4.20 Beta xAI
Gemini 3.1 Pro Google
Claude Fable 5.1 Anthropic
Claude Mythos 5.1 Anthropic
GPT-5.4 OpenAI
GPT-5.4 Thinking OpenAI
Claude Fable 5 Anthropic
Claude Mythos 5 Anthropic
GPT-5.5 OpenAI
GPT-6 Astra OpenAI
GPT-6 Astra OpenAI
Choosing the Right Model for Large-Context Coding
Selecting the backbone for an AI-powered code generation IDE requires a trade-off between absolute reasoning depth and inference efficiency. This comparison focuses on two of the most capable models for handling 500,000-token context windows, which are essential when indexing entire repositories for context-aware suggestions.
Claude Sonnet 4.6 is widely recognized for its superior instruction-following and nuanced reasoning. It excels in complex multi-file refactoring and architectural planning, where the model must understand the global impact of a localized change. For developers who prioritize code correctness and safety in their agentic workflows, Sonnet 4.6 provides a level of reliability that is unmatched in mid-tier models. Its ability to navigate large codebases with minimal hallucination makes it an excellent choice for the ‘review’ or ‘planning’ stages of a coding agent’s logic.
Conversely, DeepSeek V4 Flash is optimized for raw speed and throughput. It utilizes a sparse architecture that allows it to maintain high performance while significantly reducing the computational overhead. For solo founders optimizing for scale, this model provides an exceptionally high return on investment. While it may occasionally require more explicit prompt engineering to achieve the same level of architectural coherence as Sonnet, its latency advantages make it a formidable contender for real-time, interactive IDE features where responsiveness is the make-or-break metric for user retention.
Ultimately, the choice depends on your feature set: use Sonnet for agents that perform high-stakes refactoring, and Flash for autocomplete systems where the cost-per-suggest must stay low.