Live market

qwen3-vl-32b-instruct

Qwen: Qwen3 VL 32B Instruct

Of list price: 100%
Output / 1M: 0.416 USDT
Sellers online: 50
Calls / min: 0

Calling this model

POST /chat/completions — the same request OpenAI's SDKs already send. Point the base URL at asale and change nothing else.

billed per token

INPUT

The conversation so far, oldest first.

Ceiling on the answer's length.

Higher is more varied; 0 is deterministic.

Nucleus sampling: consider only the most likely tokens summing to this.

Penalise tokens that appeared at all, pushing to new topics.

Repeat a previous result exactly.

Send the answer as it is produced.

Output

Run it to see the answer here.

Or call it from your own code

curl https://gw.asale.ai/v1/chat/completions \
  -H "Authorization: Bearer $ASALE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "qwen3-vl-32b-instruct",
    "messages": [
      {
        "role": "user",
        "content": "Say hello in one short sentence."
      }
    ]
  }'

import os, requests

r = requests.post(
    "https://gw.asale.ai/v1/chat/completions",
    headers={"Authorization": f"Bearer {os.environ['ASALE_API_KEY']}"},
    json={
      "model": "qwen3-vl-32b-instruct",
      "messages": [
        {
          "role": "user",
          "content": "Say hello in one short sentence."
        }
      ]
    },
)
r.raise_for_status()
print(r.json())

const r = await fetch("https://gw.asale.ai/v1/chat/completions", {
  method: "POST",
  headers: {
    Authorization: `Bearer ${process.env.ASALE_API_KEY}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
    "model": "qwen3-vl-32b-instruct",
    "messages": [
      {
        "role": "user",
        "content": "Say hello in one short sentence."
      }
    ]
  }),
});
if (!r.ok) throw new Error(await r.text());
console.log(await r.json());

Request fields

Field	Type	Accepts	Meaning
modelrequired	string	—	Which model serves the request.
messagesrequired	text	—	The conversation so far, oldest first.
max_tokens	int	— … 32768	Ceiling on the answer's length.
temperature	number	0 … 2	Higher is more varied; 0 is deterministic.
top_p	number	0 … 1	Nucleus sampling: consider only the most likely tokens summing to this.
presence_penalty	number	-2 … 2	Penalise tokens that appeared at all, pushing to new topics.
seed	int	—	Repeat a previous result exactly.
stream	boolean	—	Send the answer as it is produced.

Response

{
  "id": "chatcmpl-…",
  "object": "chat.completion",
  "model": "qwen3-vl-32b-instruct",
  "choices": [
    {
      "index": 0,
      "message": {
        "role": "assistant",
        "content": "…"
      },
      "finish_reason": "stop"
    }
  ],
  "usage": {
    "prompt_tokens": 24,
    "completion_tokens": 12,
    "total_tokens": 36
  }
}

Token type	List / 1M	Market / 1M	Of list price
Input	0.104	0.104	100%
Output	0.416	0.416	100%
Cache read	0.104	0.104	100%
Cache write	0.104	0.104	100%

Channel quality

What has been measured about the supply behind this price. Readings, not promises — and aggregate, because which seller failed is nobody's business but theirs and ours.

Online lanes: 50
Verified lanes: 1/1; Proved they serve this model
First byte (p50): —
Success rate: —; No turns settled in the window
Sellable capacity: 100.0M; Tokens offered right now

Latency and verification are measured over the last day; the success rate comes from settled traffic. See the status page

Price trend

Currently selling at 100% of the vendor's list price. More sellers online push it down; more buyers push it back up to list.

Of list price: 100%
Sellers online: 50
Calls / min: 0

Market depth

Price / 1MSellers

0.416