OpenLuxDeepSeek V4 vs Qwen3 Max
DeepSeek V4 and Qwen3 Max both run on OpenLux behind one OpenAI-compatible endpoint. DeepSeek V4 is metered at $0.0613 per 1M tokens (-90% vs official rates); Qwen3 Max at $0.0784 per 1M tokens (-88% vs official rates). DeepSeek V4 is the lower-cost option per unit — about 22% 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: DeepSeek V4 suits workloads that need step-by-step reasoning, analysis and planning, Chinese-language products and bilingual apps. Qwen3 Max is the better fit when you need agents and apps that call tools or functions, 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 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.
Choose Qwen3 Max when
- You need agents and apps that call tools or functions.
- You need Chinese-language products and bilingual apps.
Rates on OpenLux
| Model | Provider | Rate | Discount |
|---|---|---|---|
| DeepSeek V4 | DeepSeek | $0.0613 per 1M tokens | -90% |
| Qwen3 Max | Qwen | $0.0784 per 1M tokens | -88% |
Rates follow official provider pricing and are billed in USD. See the full catalogue and pricing plans for credit allowances.
One snippet, two models
DeepSeek V4 and Qwen3 Max 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 ["deepseek-v4", "qwen3-max"]:
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.
DeepSeek V4 vs Qwen3 Max questions
How much do DeepSeek V4 and Qwen3 Max cost on OpenLux?
DeepSeek V4 is metered pay as you go at $0.0613 per 1M tokens, a -90% discount on official list pricing. Qwen3 Max is metered at $0.0784 per 1M tokens, a -88% discount. There is no subscription requirement: usage is billed in USD and every request is visible in the console.
Can I call DeepSeek V4 and Qwen3 Max 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 deepseek-v4 and qwen3-max — request and response shapes stay identical.
Which is cheaper, DeepSeek V4 or Qwen3 Max?
DeepSeek V4 costs less per unit: $0.0613 per 1M tokens versus $0.0784 per 1M tokens, about 22% 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 DeepSeek V4 over Qwen3 Max?
In practice the two models are complements, not substitutes: DeepSeek V4 suits workloads that need step-by-step reasoning, analysis and planning, Chinese-language products and bilingual apps. Qwen3 Max is the better fit when you need agents and apps that call tools or functions, 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 DeepSeek V4, Qwen3 Max and every other model behind one key, one endpoint and one bill. Start with free trial credit and switch models without touching your code.