DeepSeek V4 Flash DeepSeek 1000000
💰 Total Cost Calculation (from Plugin)
Output: $0.000560
Output: $0.000560
Unit: $0.000000
Fees: $0.000000
Detailed Cost Analysis (from Plugin)
For 100,000 input tokens and 2,000 output tokens:
- Input Cost: $0.014000 (rounded ~ $0.01)
- Output Cost: $0.000560
- Total Cost: $0.007700 (rounded ~ $0.01)
- Cost per 1K tokens: $0.000075
- Tokens per dollar: 13,246,753 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: 2 minutes, 49.66 seconds
- Latency: 95 milliseconds to first token
- Base Throughput: 650 tokens/second
- Effective Throughput: 602 tokens/second (temperature-adjusted)
Best Use Cases
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← Back to DeepSeek V4 Flash| Rank | AI Model & Provider | Total Cost | vs DeepSeek V4 Flash |
|---|---|---|---|
| 🏆 |
Mistral Small 3
Mistral AI
|
$0.001525 Best Value | ↓ 80.2% cheaper |
| 🥈 |
Devstral Small 2
Mistral AI
|
$0.001525 | ↓ 80.2% cheaper |
| 🥉 |
Gemini 3.1 Flash Lite
Google
|
$0.004188 | ↓ 45.6% cheaper |
| #4 |
Nemotron 3 Super
NVIDIA
|
$0.004535 | ↓ 41.1% cheaper |
| #5 |
Gemini 3.5 Flash-Lite
Google
|
$0.005375 (rounded ~ $0.01) | ↓ 30.2% cheaper |
| #6 |
Gemini 2.5 Flash
Google
|
$0.005375 (rounded ~ $0.01) | ↓ 30.2% cheaper |
| #7 |
Devstral 2
Mistral AI
|
$0.005950 (rounded ~ $0.01) | ↓ 22.7% cheaper |
| #8 |
Mistral Large 3
Mistral AI
|
$0.007625 (rounded ~ $0.01) | ↓ 1% cheaper |
| #9 |
Gemini 3.8 Flash
Google
|
$0.012188 (rounded ~ $0.01) | ↑ 58.3% more |
| #10 |
GPT-5.4 mini
OpenAI
|
$0.012563 (rounded ~ $0.01) | ↑ 63.1% more |
| #11 |
o4-mini Deep Research
OpenAI
|
$0.015750 (rounded ~ $0.02) | ↑ 104.5% more |
| #12 |
Claude Haiku 4.5
Anthropic
|
$0.016250 (rounded ~ $0.02) | ↑ 111% more |
| #13 |
Gemini 3.1 Flash
Google
|
$0.016750 (rounded ~ $0.02) | ↑ 117.5% more |
| #14 |
GPT-5.6 Luna
OpenAI
|
$0.016750 (rounded ~ $0.02) | ↑ 117.5% more |
| #15 |
o4-mini
OpenAI
|
$0.017325 (rounded ~ $0.02) | ↑ 125% more |
| #16 |
Gemini 3.6 Flash
Google
|
$0.024375 (rounded ~ $0.02) | ↑ 216.6% more |
| #17 |
Gemini 3.5 Flash
Google
|
$0.025125 (rounded ~ $0.03) | ↑ 226.3% more |
| #18 |
Magistral Medium
Mistral AI
|
$0.030000 | ↑ 289.6% more |
| #19 |
GPT-5.3 Codex Spark
OpenAI
|
$0.031063 (rounded ~ $0.03) | ↑ 303.4% more |
| #20 |
GPT-5.3 Instant
OpenAI
|
$0.031063 (rounded ~ $0.03) | ↑ 303.4% more |
| #21 |
Claude Sonnet 5
Anthropic
|
$0.032500 (rounded ~ $0.03) | ↑ 322.1% more |
| #22 |
GPT-5.6 Terra
OpenAI
|
$0.041875 (rounded ~ $0.04) | ↑ 443.8% more |
| #23 |
Gemini 2.5 Pro
Google
|
$0.044375 (rounded ~ $0.04) | ↑ 476.3% more |
| #24 |
Claude Sonnet 4.6
Anthropic
|
$0.048750 (rounded ~ $0.05) | ↑ 533.1% more |
| #25 |
Grok 4.3
xAI
|
$0.059000 (rounded ~ $0.06) | ↑ 666.2% more |
| #26 |
Grok 4.20 Beta
xAI
|
$0.059000 (rounded ~ $0.06) | ↑ 666.2% more |
| #27 |
Gemini 3.1 Pro
Google
|
$0.067000 (rounded ~ $0.07) | ↑ 770.1% more |
| #28 |
Claude Opus 4.7
Anthropic
|
$0.081250 (rounded ~ $0.08) | ↑ 955.2% more |
| #29 |
Claude Opus 5
Anthropic
|
$0.081250 (rounded ~ $0.08) | ↑ 955.2% more |
| #30 |
Claude Opus 4.8
Anthropic
|
$0.081250 (rounded ~ $0.08) | ↑ 955.2% more |
| #31 |
Claude Opus 4.6
Anthropic
|
$0.081250 (rounded ~ $0.08) | ↑ 955.2% more |
| #32 |
GPT-5.4
OpenAI
|
$0.083750 (rounded ~ $0.08) | ↑ 987.7% more |
| #33 |
GPT-5.4 Thinking
OpenAI
|
$0.083750 (rounded ~ $0.08) | ↑ 987.7% more |
| #34 |
GPT-5.5 Instant
OpenAI
|
$0.083750 (rounded ~ $0.08) | ↑ 987.7% more |
| #35 |
GPT-5.6 Sol
OpenAI
|
$0.083750 (rounded ~ $0.08) | ↑ 987.7% more |
| #36 |
Claude Fable 5.1
Anthropic
|
$0.153125 (rounded ~ $0.15) | ↑ 1888.6% more |
| #37 |
Claude Mythos 5.1
Anthropic
|
$0.153125 (rounded ~ $0.15) | ↑ 1888.6% more |
| #38 |
o3 Deep Research
OpenAI
|
$0.157500 (rounded ~ $0.16) | ↑ 1945.5% more |
| #39 |
Claude Fable 5
Anthropic
|
$0.162500 (rounded ~ $0.16) | ↑ 2010.4% more |
| #40 |
Claude Mythos 5
Anthropic
|
$0.162500 (rounded ~ $0.16) | ↑ 2010.4% more |
| #41 |
GPT-5.5
OpenAI
|
$0.167500 (rounded ~ $0.17) | ↑ 2075.3% more |
| #42 |
o3 Pro
OpenAI
|
$0.315000 (rounded ~ $0.32) | ↑ 3990.9% more |
| #43 |
GPT-6 Astra
OpenAI
|
$0.325000 (rounded ~ $0.33) | ↑ 4120.8% more |
| #44 |
GPT-5.2 Pro
OpenAI
|
$0.372750 (rounded ~ $0.37) | ↑ 4740.9% more |
| #45 |
GPT-5.2 Pro
OpenAI
|
$0.372750 (rounded ~ $0.37) | ↑ 4740.9% more |
Mistral Small 3 Mistral AI
Devstral Small 2 Mistral AI
Gemini 3.1 Flash Lite Google
Nemotron 3 Super NVIDIA
Gemini 3.5 Flash-Lite Google
Gemini 2.5 Flash Google
Devstral 2 Mistral AI
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
Magistral Medium Mistral AI
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
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
Managing the AI budget for small-scale marketing experiments often involves choosing models that deliver maximum performance for high-throughput, repetitive tasks. When running 100K-token loads for A/B testing campaign copy, DeepSeek V4 Flash has established itself as an efficiency-first option.
Unlike flagship models reserved for complex, multi-step agentic workflows, DeepSeek V4 Flash is purpose-built for high-throughput, routine tasks. For a social media manager producing 20 variations of ad copy, this model provides consistent performance without the premium cost associated with larger reasoning models. It handles the bulk generation of marketing content effectively, allowing teams to iterate on language angles and calls-to-action rapidly.
One of the primary benefits of DeepSeek V4 Flash for this specific use case is its architecture. It is a Mixture-of-Experts (MoE) model that offers high performance while maintaining cost-efficiency. For teams that need to run daily experiments without constant budget monitoring, this predictability is a major advantage.
However, it is important to note that while excellent for high-volume drafting and copy variants, this model is not designed for deep, multi-step logical reasoning. If your A/B testing requires the model to analyze complex performance data or synthesize competitor research alongside copy generation, you may find that it lacks the deep analysis capabilities of larger, more expensive models. For pure creative drafting and high-volume variation generation, it represents a highly efficient choice for cost-conscious solo practitioners and indie teams.