Specs & substance

Developed by: Alibaba
Model family: Qwen
Use case: Coding
Modality: Text
Context window: 256K tokens
Architecture: MoE
Version: Coder-Next
License: Apache 2.0
Pricing: $0.12 in · $0.80 out · $0.07 cache read
Released: May 2026
Endpoint: parasail-qwen3-coder-next

Code-specialized model with strong fill-in-the-middle and agentic coding support.

Qwen3-Coder-Next is part of the Qwen family by Alibaba, and sits in the coding category. It supports a 256K tokens context window and is built on a MoE architecture.

Key strengths: coding, efficient. Parasail serves Qwen3-Coder-Next on a global fleet of current-gen GPUs behind a single OpenAI-compatible endpoint — with per-token pricing, no minimums, and dedicated capacity options when you need guaranteed throughput.

Integrate

Drop-in via the OpenAI SDK

Point any OpenAI-compatible client at Parasail and change the model name. That's it.

python parasail · Qwen3-Coder-Next

from openai import OpenAI

client = OpenAI(
    api_key="YOUR_API_KEY",
    base_url="https://api.parasail.io/v1"
)

response = client.chat.completions.create(
    model="parasail-qwen3-coder-next",
    messages=[
        {"role": "user", "content": "Hello, what can you do?"}
    ],
    stream=True,
    max_tokens=1000
)

for chunk in response:
    if chunk.choices and chunk.choices[0].delta.content is not None:
        print(chunk.choices[0].delta.content, end="", flush=True)

bash parasail · Qwen3-Coder-Next

curl https://api.parasail.io/v1/chat/completions \
  -H "Authorization: Bearer $PARASAIL_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "parasail-qwen3-coder-next",
    "messages": [{"role": "user", "content": "Hello, what can you do?"}],
    "stream": true,
    "max_tokens": 1000
  }'

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