Qwen3 8B

Apache 2.0

qwen/qwen3-8b

Dense 8B instruct model from Alibaba. Strong general reasoning and multilingual performance for its size, with a hybrid thinking mode. A good default for agent loops and classification where an 8B is enough and latency matters.

Get an API key

Endpoints

Each row is one provider serving these weights at one precision. Prices are per million tokens.

Provider	Quantisation	Hardware	Context	Max out	Input	Output	Cached in
Infersiafree	AWQ int4	RTX 3090mock — no GPU yet	8K	2K	Free	Free	—
Infersia	AWQ int4	RTX 3090mock — no GPU yet	32K	8K	$0.05	$0.15	$0.01

Prefix caching is enabled and the discount is passed through. If your agent replays the same system prompt each iteration, the repeated portion bills at the cached rate.

What AWQ int4 means

Activation-aware 4-bit weight quantisation. Small, measurable quality cost.

We serve this on vllm 0.9.1, and the quantisation is returned on every request in the x-infersia-quantization response header — so you can assert on it in your own tests rather than trusting this page.

Call it

curlbash

curl https://api.infersia.com/v1/chat/completions \
  -H "Authorization: Bearer $INFERSIA_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "qwen/qwen3-8b",
    "messages": [{"role": "user", "content": "Hello"}],
    "stream": true
  }'

Pin a provider with qwen/qwen3-8b@infersia, or take the cheapest with the bare id. Add :free for the rate-limited free tier where one exists.