DeepSeek V4 Pro DeepSeek 1000000
💰 Total Cost Calculation (from Plugin)
Output: $0.001740
Output: $0.001740
Unit: $0.000000
Fees: $0.000000
Detailed Cost Analysis (from Plugin)
For 100,000 input tokens and 2,000 output tokens:
- Input Cost: $0.043500 (rounded ~ $0.04)
- Output Cost: $0.001740
- Total Cost: $0.040977
- Cost per 1K tokens: $0.000402
- Tokens per dollar: 2,489,201 tokens
- Context Window: 1000000 tokens
Speed & Performance Analysis
With a processing speed of 300 tokens per second and 180ms time to first token:
- Processing Time: 6 minutes, 3.98 seconds
- Latency: 180 milliseconds to first token
- Base Throughput: 300 tokens/second
- Effective Throughput: 280 tokens/second (temperature-adjusted)
Best Use Cases
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← Back to DeepSeek V4 Pro| Rank | AI Model & Provider | Total Cost | vs DeepSeek V4 Pro |
|---|---|---|---|
| 🏆 |
Mistral Small 3
Mistral AI
|
$0.002425 Best Value | ↓ 94.1% cheaper |
| 🥈 |
Gemini 3.1 Flash Lite
Google
|
$0.006438 (rounded ~ $0.01) | ↓ 84.3% cheaper |
| 🥉 |
Gemini 3.5 Flash-Lite
Google
|
$0.008075 (rounded ~ $0.01) | ↓ 80.3% cheaper |
| #4 |
Gemini 2.5 Flash
Google
|
$0.008075 (rounded ~ $0.01) | ↓ 80.3% cheaper |
| #5 |
Mistral Large 3
Mistral AI
|
$0.012125 (rounded ~ $0.01) | ↓ 70.4% cheaper |
| #6 |
Gemini 3.8 Flash
Google
|
$0.018938 (rounded ~ $0.02) | ↓ 53.8% cheaper |
| #7 |
GPT-5.4 mini
OpenAI
|
$0.019313 | ↓ 52.9% cheaper |
| #8 |
o4-mini Deep Research
OpenAI
|
$0.024750 (rounded ~ $0.02) | ↓ 39.6% cheaper |
| #9 |
Claude Haiku 4.5
Anthropic
|
$0.025250 (rounded ~ $0.03) | ↓ 38.4% cheaper |
| #10 |
Gemini 3.1 Flash
Google
|
$0.025750 (rounded ~ $0.03) | ↓ 37.2% cheaper |
| #11 |
GPT-5.6 Luna
OpenAI
|
$0.025750 (rounded ~ $0.03) | ↓ 37.2% cheaper |
| #12 |
o4-mini
OpenAI
|
$0.027225 (rounded ~ $0.03) | ↓ 33.6% cheaper |
| #13 |
Gemini 3.6 Flash
Google
|
$0.037875 (rounded ~ $0.04) | ↓ 7.6% cheaper |
| #14 |
Gemini 3.5 Flash
Google
|
$0.038625 (rounded ~ $0.04) | ↓ 5.7% cheaper |
| #15 |
GPT-5.3 Codex Spark
OpenAI
|
$0.046813 (rounded ~ $0.05) | ↑ 14.2% more |
| #16 |
GPT-5.3 Instant
OpenAI
|
$0.046813 (rounded ~ $0.05) | ↑ 14.2% more |
| #17 |
Claude Sonnet 5
Anthropic
|
$0.050500 | ↑ 23.2% more |
| #18 |
GPT-5.6 Terra
OpenAI
|
$0.064375 (rounded ~ $0.06) | ↑ 57.1% more |
| #19 |
Gemini 2.5 Pro
Google
|
$0.066875 (rounded ~ $0.07) | ↑ 63.2% more |
| #20 |
Claude Sonnet 4.6
Anthropic
|
$0.075750 (rounded ~ $0.08) | ↑ 84.9% more |
| #21 |
Grok 4.3
xAI
|
$0.095000 (rounded ~ $0.10) | ↑ 131.8% more |
| #22 |
Grok 4.20 Beta
xAI
|
$0.095000 (rounded ~ $0.10) | ↑ 131.8% more |
| #23 |
Gemini 3.1 Pro
Google
|
$0.103000 (rounded ~ $0.10) | ↑ 151.4% more |
| #24 |
Claude Opus 4.7
Anthropic
|
$0.126250 (rounded ~ $0.13) | ↑ 208.1% more |
| #25 |
Claude Opus 5
Anthropic
|
$0.126250 (rounded ~ $0.13) | ↑ 208.1% more |
| #26 |
Claude Opus 4.8
Anthropic
|
$0.126250 (rounded ~ $0.13) | ↑ 208.1% more |
| #27 |
Claude Opus 4.6
Anthropic
|
$0.126250 (rounded ~ $0.13) | ↑ 208.1% more |
| #28 |
GPT-5.4
OpenAI
|
$0.128750 (rounded ~ $0.13) | ↑ 214.2% more |
| #29 |
GPT-5.4 Thinking
OpenAI
|
$0.128750 (rounded ~ $0.13) | ↑ 214.2% more |
| #30 |
GPT-5.5 Instant
OpenAI
|
$0.128750 (rounded ~ $0.13) | ↑ 214.2% more |
| #31 |
GPT-5.6 Sol
OpenAI
|
$0.128750 (rounded ~ $0.13) | ↑ 214.2% more |
| #32 |
o3 Deep Research
OpenAI
|
$0.247500 (rounded ~ $0.25) | ↑ 504% more |
| #33 |
Claude Fable 5.1
Anthropic
|
$0.250625 | ↑ 511.6% more |
| #34 |
Claude Mythos 5.1
Anthropic
|
$0.250625 | ↑ 511.6% more |
| #35 |
Claude Fable 5
Anthropic
|
$0.252500 (rounded ~ $0.25) | ↑ 516.2% more |
| #36 |
Claude Mythos 5
Anthropic
|
$0.252500 (rounded ~ $0.25) | ↑ 516.2% more |
| #37 |
GPT-5.5
OpenAI
|
$0.257500 (rounded ~ $0.26) | ↑ 528.4% more |
| #38 |
o3 Pro
OpenAI
|
$0.495000 (rounded ~ $0.50) | ↑ 1108% more |
| #39 |
GPT-6 Astra
OpenAI
|
$0.505000 (rounded ~ $0.51) | ↑ 1132.4% more |
| #40 |
GPT-5.2 Pro
OpenAI
|
$0.561750 (rounded ~ $0.56) | ↑ 1270.9% more |
| #41 |
GPT-5.2 Pro
OpenAI
|
$0.561750 (rounded ~ $0.56) | ↑ 1270.9% 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
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-5.2 Pro OpenAI
GPT-5.2 Pro OpenAI
Optimizing Worker Agent Costs
For translation agencies implementing multi-agent systems, efficiently managing the operational costs of individual worker agents is crucial for scalability. DeepSeek V4 Pro presents a compelling choice for these roles, offering a strong blend of reasoning capabilities and competitive pricing. Worker agents often handle specific, recurring tasks within a larger orchestration flow, such as segment translation, terminology extraction, or quality checks. DeepSeek V4 Pro’s ability to follow instructions accurately and its substantial 1 million token context window ensure it can handle moderately complex sub-tasks effectively. Its attractive cost structure per 100,000 tokens makes it an ideal candidate for scaling out worker agent fleets, allowing agencies to deploy more agents or process larger volumes of data per agent without a proportional increase in expenditure. When an orchestrator delegates work, the efficiency and cost-effectiveness of each worker agent directly impacts the overall profitability and throughput of the AI-assisted translation service. DeepSeek V4 Pro empowers this by providing reliable performance at an accessible price point.