| Feature | DeepSeek V4 Best Overall | DeepSeek V3 | DeepSeek R1 | Qwen3 Flash Budget |
|---|---|---|---|---|
| Input Price | $0.28/M tokens | $0.14/M tokens | $0.55/M tokens | $0.07/M tokens |
| Output Price | $0.42/M tokens | $0.28/M tokens | $2.19/M tokens | $0.07/M tokens |
| Context Window | 128K | 128K | 128K | 32K |
| Reasoning | ⭐⭐⭐⭐⭐ | ⭐⭐⭐⭐ | ⭐⭐⭐⭐⭐+ | ⭐⭐⭐ |
| Coding | ⭐⭐⭐⭐⭐ | ⭐⭐⭐⭐ | ⭐⭐⭐⭐⭐ | ⭐⭐⭐⭐ |
| Speed | Fast | Faster | Slow (CoT) | Fastest |
| Best For | General purpose, agents | Balanced tasks | Math, logic, hard reasoning | High volume, simple tasks |
Choose this when you need the best balance of quality and cost for general-purpose tasks. It excels at coding, instruction following, and multi-turn conversations. Ideal for AI agents, chatbots, and production systems.
Use cases: Customer support bots, code assistants, content generation, API backends
Half the price of V4 with still-strong performance. Perfect when you need good quality but want to minimize costs at scale.
Use cases: Batch processing, data extraction, summarization, non-critical workflows
Uses chain-of-thought reasoning to solve complex problems. Slower and more expensive per output token, but delivers superior results on math, logic puzzles, and multi-step reasoning tasks.
Use cases: Mathematical proofs, complex debugging, strategic analysis, research tasks
At $0.07/M tokens, these are perfect for high-throughput scenarios where you need fast responses and can tolerate slightly lower quality.
Use cases: Autocomplete, real-time chat, classification, simple Q&A, prototyping
Assuming average 500 input + 200 output tokens per request:
| Model | Cost per 1M requests | vs OpenAI GPT-4o |
|---|---|---|
| DeepSeek V4 | $224 | 91% cheaper |
| DeepSeek V3 | $126 | 95% cheaper |
| DeepSeek R1 | $493 | 80% cheaper |
| Qwen3 Flash / DS Flash | $35 | 98.6% cheaper |
| OpenAI GPT-4o (reference) | $2,500 | — |
All models are available through the same OpenAI-compatible API. Just change the model parameter:
from openai import OpenAI
client = OpenAI(
base_url="https://eaf9553505eeb8f5-115-190-107-107.serveousercontent.com/v1",
api_key="your-api-key"
)
# Switch models by changing one line
response = client.chat.completions.create(
model="deepseek-v4", # or deepseek-v3, deepseek-r1, qwen3.6-flash, deepseek-v4-flash
messages=[{"role": "user", "content": "Hello!"}]
)All models are available 24/7 through our API with 99.9% uptime SLA. Flash models have the lowest latency (~200ms TTFT), while R1 may take 2-5 seconds for complex reasoning.