The open-weight model punching way above its price tag.
No signup required — try it as a guest. 30,000 free tokens every day once you sign up.
DeepSeek V3 is a 671B-parameter mixture-of-experts model from the Hangzhou lab that made headlines for reaching GPT-4o-level quality on most public benchmarks at roughly 1/30th the cost. Open weights, strong at code and reasoning.
Frontier-quality reasoning at budget prices
Excellent at code — benchmarks near Claude 3.5 Sonnet
Open weights (self-host if you want)
64k context
Often under 1,000 tokens per message. Some of the best quality-per-credit on the platform.
OpenAI-compatible. Same Faceb.ai tokens cover chat and API. Drop-in replacement for the OpenAI SDK.
curl https://api.faceb.ai/v1/chat/completions \
-H "Authorization: Bearer sk-faceb-YOUR_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "deepseek/deepseek-chat",
"messages": [{"role": "user", "content": "Hello!"}],
"stream": true
}'from openai import OpenAI
client = OpenAI(
base_url="https://api.faceb.ai/v1",
api_key="sk-faceb-YOUR_KEY",
)
stream = client.chat.completions.create(
model="deepseek/deepseek-chat",
messages=[{"role": "user", "content": "Hello!"}],
stream=True,
)
for chunk in stream:
print(chunk.choices[0].delta.content or "", end="", flush=True)import OpenAI from "openai";
const client = new OpenAI({
baseURL: "https://api.faceb.ai/v1",
apiKey: "sk-faceb-YOUR_KEY",
});
const stream = await client.chat.completions.create({
model: "deepseek/deepseek-chat",
messages: [{ role: "user", content: "Hello!" }],
stream: true,
});
for await (const chunk of stream) {
process.stdout.write(chunk.choices[0]?.delta?.content || "");
}
Also works for image generation (image-output model slugs return image_url content parts) and web search (add "web_search": true to the payload). Same endpoint, same wallet.
DeepSeek V3 is a 671-billion-parameter mixture-of-experts model from DeepSeek (a Hangzhou-based lab). Released December 2024, it benchmarks close to GPT-4o and Claude 3.5 Sonnet at roughly 1/30th the training cost.
On most public benchmarks, yes — it's within a few percentage points on code, math, and reasoning. On creative writing and some edge cases, GPT-4o is still ahead. Try both on the same prompt.
Yes — DeepSeek V3's weights are on HuggingFace under a custom licence that allows commercial use with attribution. You can self-host if you have the compute.
Often under 1,000 tokens per message (compare GPT-4o at 3,750–9,200). Some of the best quality-per-credit on the platform.
We route through upstream hosts, not DeepSeek directly. Check the specific host's terms in the model details — some US-based hosts explicitly prohibit cross-border training.
64,000 tokens. Smaller than Claude (200k) or Gemini (1M), but still comfortable for most tasks.
No — text-only. DeepSeek has separate vision models; our picker lists them if you need image input.
R1 is the reasoning-focused variant with visible chain-of-thought, optimised for math/logic. V3 is the general-purpose chat variant. Both are in our picker.
Yes. Model slug: deepseek/deepseek-chat. OpenAI-compatible SDK works with base_url=https://api.faceb.ai/v1.
Mixture-of-experts architecture activates only a subset of the 671B parameters per token (~37B active), plus aggressive training optimisations. Both factors drop inference cost.
Yes — it was trained on a substantial multilingual corpus. English output quality is comparable to the big Western labs.
As soon as our upstream aggregator adds it, yes — automatically.
Your Faceb.ai tokens work for every model — switch per message, no extra subscriptions.
Anthropic's best balance of quality and cost — a coder favourite.
Chat with Claude 3.5 Sonnet →Meta's best open-weight model — runs on community hosts.
Chat with Llama 3.3 70B →OpenAI's flagship multimodal model — text, vision, and code.
Chat with GPT-4o →One subscription covers every frontier model — switch between them per message. No extra API keys, no extra bills.