Access DeepSeek, Qwen, Kimi, GLM, MiniMax, and 20+ more models
through a single OpenAI-compatible API. $2 free credit β no card required.
| FlintAPI | Direct Provider | OpenRouter | |
|---|---|---|---|
| 25+ Chinese LLMs | β One API key | β Per-provider account | β |
| Self-hosted PPU Qwen | β Lower cost | β Cloud pricing | β |
| OpenAI-compatible | β Drop-in replacement | β | |
| Free credit | β $2, no card | β | |
| No middleman markup | β Self-hosted | β | β Markup |
| Referral bonus | β $1 each | β | β |
Go to flintapi.ai/register β you get $2 free credit instantly, no credit card required.
Find it in your Dashboard β Settings β Create Key. Copy it β it's shown only once!
cURL:
curl https://flintapi.ai/v1/chat/completions \
-H "Authorization: Bearer YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "flint-smart",
"messages": [{"role": "user", "content": "Explain quantum computing in one sentence."}]
}'Python (with pip install openai):
from openai import OpenAI
client = OpenAI(
base_url="https://flintapi.ai/v1",
api_key="YOUR_API_KEY"
)
response = client.chat.completions.create(
model="flint-smart",
messages=[{"role": "user", "content": "Hello!"}]
)
print(response.choices[0].message.content)Node.js (npm install openai):
import OpenAI from 'openai';
const client = new OpenAI({
baseURL: 'https://flintapi.ai/v1',
apiKey: 'YOUR_API_KEY',
});
const completion = await client.chat.completions.create({
model: 'qwen3.7-max',
messages: [{ role: 'user', content: 'Say hello in Chinese' }],
});
console.log(completion.choices[0].message.content);Go (go get github.com/sashabaranov/go-openai):
import "github.com/sashabaranov/go-openai"
client := openai.NewClient("YOUR_API_KEY")
client.BaseURL = "https://flintapi.ai/v1"
resp, _ := client.CreateChatCompletion(ctx, openai.ChatCompletionRequest{
Model: "glm-5.1",
Messages: []openai.ChatCompletionMessage{
{Role: "user", Content: "Hello!"},
},
})
fmt.Println(resp.Choices[0].Message.Content)Don't know which model to pick? Use "model": "flint-smart" and our router auto-selects the best Chinese LLM for your prompt:
| Prompt Type | Routed To | Why |
|---|---|---|
| Code / programming | deepseek-v4-pro |
Best coding LLM |
| Reasoning / analysis | deepseek-v4-pro |
Strong logic |
| Chinese / bilingual | deepseek-v4-pro |
Native Chinese |
| General / default | deepseek-v4-flash |
Fast & cheap |
| Model | Provider | Context | Best For |
|---|---|---|---|
deepseek-v4-pro |
DeepSeek | 128K | Reasoning & code |
deepseek-v4-flash |
DeepSeek | 128K | Fast, cost-effective |
qwen3.7-max |
Qwen | 128K | Flagship all-rounder |
qwen3.7-plus |
Qwen | 128K | Balanced Chinese-English |
qwen3.5-plus |
Qwen | 128K | Solid general-purpose |
qwen3.5-flash |
Qwen | 128K | Lowest latency |
kimi-k2.6 |
Kimi | 256K | Long context |
kimi-k2.5 |
Kimi | 128K | Long context |
glm-5.1 |
GLM | 32K | Bilingual expert |
MiniMax-M2.7 |
MiniMax | 512K | Creative writing |
Full list & pricing: flintapi.ai/pricing
For an even simpler experience:
pip install flintapifrom flintapi import Flint
flint = Flint(api_key="YOUR_API_KEY")
# Simple chat
reply = flint.chat("Explain quantum computing in one sentence.")
print(reply)
# With model selection
reply = flint.chat("Write a Python quicksort", model="flint-smart")
print(reply)
# Streaming
for chunk in flint.chat_stream("Tell me a story"):
print(chunk, end="")- API Docs β Full API reference with code examples
- Playground β Try models in your browser
- Pricing β Per-token pricing for all models
- Compare β FlintAPI vs alternatives
- Status β Real-time model health
- Dashboard β Usage, billing, API keys
- One API key for 25+ Chinese LLMs
- OpenAI-compatible β change
base_urland keep existing code - flint-smart router β auto-select best model per request
- $2 free credit β instant, no card required
- Real-time billing β per-token pricing, usage dashboard
- 4 language SDKs β cURL, Python, Node.js, Go
- PPU self-hosted Qwen β competitive pricing on custom silicon
- Referral program β both you and your friend get $1
- Email: support@flintapi.ai
- GitHub Issues: github.com/moozechen/flintapi/issues
- Website: flintapi.ai
A community resource tracking the Chinese LLM ecosystem. Not promotional β just what's out there, what each model does best, and how to try them.
| Model | Organization | Open Weights | Best For | How to Try |
|---|---|---|---|---|
| DeepSeek-V4-Pro | DeepSeek | β | Reasoning, math, code | api-docs.deepseek.com |
| Qwen3.7-Max | Alibaba | β | All-rounder, bilingual | qwen.ai |
| Kimi-K2.6 | Moonshot AI | β API only | Long context (256K) | kimi.moonshot.cn |
| GLM-5.1 | Zhipu AI | β | Bilingual enterprise | zhipuai.cn |
| MiniMax-M2.7 | MiniMax | β API only | Creative writing, 512K ctx | minimaxi.com |
| Doubao-1.5-pro | ByteDance | β API only | Chinese content, fast | volcengine.com |
| Baichuan-M1 | Baichuan | β | Healthcare, finance | baichuan-ai.com |
| Yi-Lightning | 01.AI | β | Efficient, low-latency | 01.ai |
- DeepSeek-V4 scored #1 on Aider's polyglot coding benchmark, beating GPT-5 and Claude
- Qwen3.6-35B-A3B (MoE) delivers near-70B performance at 35B params β 1274 points on HN
- Qwen3.6-27B runs on a single RTX 3090 (Q4 quant) at 50-70 tok/s β HN front page
- Kimi-K2.6 handles 256K context windows, competitive with Gemini for long-document tasks
- MiniMax-M2.7 has 512K context β among the longest available worldwide
| Benchmark | Top Chinese Model | Score vs GPT-5 |
|---|---|---|
| Aider Polyglot (coding) | DeepSeek-V4-Pro | +5.2% |
| LiveCodeBench | Qwen3.7-Max | -2.1% |
| MMLU-Pro | DeepSeek-V4-Pro | -1.8% |
| C-Eval (Chinese NLP) | Qwen3.7-Max | +8.3% |
Benchmarks from official model cards and public leaderboards. Last updated: June 2026.
- Via API: Most providers offer OpenAI-compatible endpoints β sign up, get a key, swap
base_url - Run locally: Qwen3.6-27B fits on a 3090; DeepSeek-V4 needs ~140GB VRAM (run on cloud or multiple GPUs)
- Registration tip: Some platforms require Chinese phone numbers β use Alibaba Cloud's international portal for Qwen without Chinese ID
Community-maintained resource. Spotted outdated info? Open an issue.