OpenLuxGemini 3.1 Pro (preview) vs DeepSeek V4
Gemini 3.1 Pro (preview) and DeepSeek V4 both run on OpenLux behind one OpenAI-compatible endpoint. Gemini 3.1 Pro (preview) is metered at $0.1471 per 1M tokens (-92% vs official rates); DeepSeek V4 at $0.0613 per 1M tokens (-90% vs official rates). DeepSeek V4 is the lower-cost option per unit — about 58% cheaper on the same OpenLux endpoint. This page compares their rates, strengths and best-fit workloads so you can route each request to the right model.
The short version
In practice the two models are complements, not substitutes: Gemini 3.1 Pro (preview) suits workloads that need multimodal questions that benefit from extended thinking, production chat and assistant workloads. DeepSeek V4 is the better fit when you need step-by-step reasoning, analysis and planning, Chinese-language products and bilingual apps. Both are called with the same OpenLux key, so switching between them is a one-field change to the model name.
Choose Gemini 3.1 Pro (preview) when
- You need multimodal questions that benefit from extended thinking.
- You need production chat and assistant workloads.
Choose DeepSeek V4 when
- You need step-by-step reasoning, analysis and planning.
- You need Chinese-language products and bilingual apps.
- Unit cost is the deciding factor for this workload.
Rates on OpenLux
| Model | Provider | Rate | Discount |
|---|---|---|---|
| Gemini 3.1 Pro (preview) | $0.1471 per 1M tokens | -92% | |
| DeepSeek V4 | DeepSeek | $0.0613 per 1M tokens | -90% |
Rates follow official provider pricing and are billed in USD. See the full catalogue and pricing plans for credit allowances.
One snippet, two models
Gemini 3.1 Pro (preview) and DeepSeek V4 share the same OpenAI-compatible request shape. Run the same code against both and compare the answers on your own workload.
from openai import OpenAI
client = OpenAI(
api_key="sk-openlux-...",
base_url="https://openlux.lol/v1",
)
for model in ["gemini-3.1-pro-preview", "deepseek-v4"]:
resp = client.chat.completions.create(
model=model,
messages=[{"role": "user", "content": "Summarise this release note for me."}],
)
print(model, "->", resp.choices[0].message.content)Any OpenAI SDK works the same way — see the docs for streaming, tools and error codes.
Gemini 3.1 Pro (preview) vs DeepSeek V4 questions
How much do Gemini 3.1 Pro (preview) and DeepSeek V4 cost on OpenLux?
Gemini 3.1 Pro (preview) is metered pay as you go at $0.1471 per 1M tokens, a -92% discount on official list pricing. DeepSeek V4 is metered at $0.0613 per 1M tokens, a -90% discount. There is no subscription requirement: usage is billed in USD and every request is visible in the console.
Can I call Gemini 3.1 Pro (preview) and DeepSeek V4 with the same API key?
Yes. Both models sit behind the same OpenAI-compatible endpoint at https://openlux.lol/v1. Keep the same key and change only the "model" field to switch between gemini-3.1-pro-preview and deepseek-v4 — request and response shapes stay identical.
Which is cheaper, Gemini 3.1 Pro (preview) or DeepSeek V4?
DeepSeek V4 costs less per unit: $0.0613 per 1M tokens versus $0.1471 per 1M tokens, about 58% lower for the same volume. Over a month of production traffic the difference compounds, and the console shows cost per request in real time.
When should I pick Gemini 3.1 Pro (preview) over DeepSeek V4?
In practice the two models are complements, not substitutes: Gemini 3.1 Pro (preview) suits workloads that need multimodal questions that benefit from extended thinking, production chat and assistant workloads. DeepSeek V4 is the better fit when you need step-by-step reasoning, analysis and planning, Chinese-language products and bilingual apps. Both are called with the same OpenLux key, so switching between them is a one-field change to the model name.
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Route every request to the right model
OpenLux keeps Gemini 3.1 Pro (preview), DeepSeek V4 and every other model behind one key, one endpoint and one bill. Start with free trial credit and switch models without touching your code.