Get GPT-4 level performance at 70% lower cost. Same API format. Same code. Way less money.
If you're building an AI-powered product, OpenAI's API costs can eat your margins alive. GPT-4o costs $2.50 per million input tokens and $10.00 per million output tokens. At scale, that adds up fast.
TokenEase gives you access to DeepSeek V4, GLM-5, Qwen-Plus, and more through an OpenAI-compatible API. You literally change 2 lines of code and start saving.
$2.50/M input
$10.00/M output
128K context
+ Rate limits
+ US-only priority
+ No Chinese models
$0.50/M input
$2.00/M output
128K context
+ 6 models available
+ Global access
+ $1 free credit
| Monthly Volume | OpenAI GPT-4o | TokenEase (DeepSeek V4) | You Save |
|---|---|---|---|
| 10M tokens | $42.50 | $12.50 | $30.00 (71%) |
| 100M tokens | $425 | $125 | $300 (71%) |
| 1B tokens | $4,250 | $1,250 | $3,000 (71%) |
| 10B tokens | $42,500 | $12,500 | $30,000 (71%) |
71% savings — same quality, fraction of the cost.
# Before (OpenAI)
from openai import OpenAI
client = OpenAI(api_key="sk-your-openai-key")
# After (TokenEase) — change 2 lines
client = OpenAI(
base_url="https://tokenease.io/v1",
api_key="sk-your-tokenease-key"
)
# Everything else stays exactly the same!
response = client.chat.completions.create(
model="deepseek", # just change model name
messages=[{"role":"user","content":"Hello!"}]
)
| Model | Input $/M | Output $/M | Best For |
|---|---|---|---|
| DeepSeek V4 | $0.50 | $2.00 | General + Code |
| Qwen-Plus | $0.40 | $1.20 | Multilingual + Agents |
| Doubao Pro | $0.20 | $0.80 | Creative + Chat |
| GLM-5.1 | $1.00 | $4.00 | Chinese Enterprise |
| Kimi | $2.00 | $8.00 | Long Documents (200K) |
On major benchmarks (MMLU, HumanEval, MATH, GSM8K), DeepSeek V4 scores within 5% of GPT-4o. For coding tasks specifically, it often outperforms GPT-4o. And it costs 80% less.
Yes. TokenEase uses the exact same API format as OpenAI. If you use the OpenAI Python/Node.js SDK, you only need to change the base_url and api_key. No other code changes needed.
Absolutely. Many users route different requests to different models — GPT-4o for the most critical tasks, DeepSeek for everything else. This hybrid approach can cut costs by 50%+.