Qwen: Qwen3 Coder Next✓ Catalog verified
Qwen3-Coder-Next is an open-weight causal language model optimized for coding agents and local development workflows. It uses a sparse MoE design with 80B total parameters and only 3B activated per...
Overview
Qwen3-Coder-Next is an open-weight causal language model optimized for coding agents and local development workflows. It uses a sparse MoE design with 80B total parameters and only 3B activated per...
Access: available through the official Qwen API. Context window: 262K.
Specifications
| API identifier | qwen/qwen3-coder-next |
| Provider | Qwen |
| Model type | Text LLM |
| Context window | 262K catalog |
| Input modalities | text |
| Output modalities | text |
| Released | Feb 4, 2026 |
| Tokenizer | Qwen |
| Moderated | No |
| Architecture modality | text->text |
API defaults
{
"top_p": 0.95,
"temperature": 1,
"frequency_penalty": null
}Pricing
Live pricing components for qwen/qwen3-coder-next as published in the catalog.
| Pricing component | Raw unit price | Normalized | Unit |
|---|---|---|---|
| Prompt tokens | $1.2e-7 | $0.12 / 1M | Per input token |
| Completion tokens | $8e-7 | $0.80 / 1M | Per output token |
| Request fee | N/A | N/A | Per request |
| Image fee | N/A | N/A | Per image unit |
| Web search fee | N/A | N/A | Per search request |
Cost calculator
Estimate monthly spend from your own token volumes.
Estimated Total Cost
$0.22Calculated from current list pricing in the ModelsAtlas catalog.Capabilities
| Capability | Status | What it means |
|---|---|---|
| Visual Understanding | Not advertised | Image and document analysis support |
| Audio Processing | Not advertised | Speech and voice aligned flows |
| Tool Calling | ✓ Supported | Supports tools / function calling |
| Self-Hosting | ✓ Supported | Deploy outside managed APIs |
Capability signals
Directional signals derived from model metadata and capability tags — not official benchmark submissions.
Quick start
Call Qwen: Qwen3 Coder Next through an OpenAI-compatible client.
from openai import OpenAI
client = OpenAI(
base_url="https://openrouter.ai/api/v1",
api_key="YOUR_API_KEY"
)
response = client.chat.completions.create(
model="qwen/qwen3-coder-next",
messages=[{"role": "user", "content": "Explain quantum physics."}]
)
print(response.choices[0].message.content)Alternatives
Closest models by context window from a different provider.
| Model | Provider | Context | Input /1M | Actions |
|---|---|---|---|---|
| Arcee AI: Trinity Large Thinking | Arcee Ai | 262K | $0.25 | View → |
| ByteDance Seed: Seed 1.6 | Bytedance Seed | 262K | $0.25 | View → |
Sources & attribution
Pricing and metadata are maintained in the ModelsAtlas catalog.
Frequently asked questions
How much does Qwen: Qwen3 Coder Next cost?
$0.12 per 1M input tokens and $0.80 per 1M output tokens on the official Qwen API.
What is the context window of Qwen: Qwen3 Coder Next?
Qwen: Qwen3 Coder Next supports up to 262K tokens of context.
Does Qwen: Qwen3 Coder Next support tool / function calling?
Yes, Qwen: Qwen3 Coder Next supports tool / function calling — you can register tools and the model will emit structured tool calls.
How do I access Qwen: Qwen3 Coder Next?
Use the official Qwen API with the model id `qwen/qwen3-coder-next`. See the Quick start section above for code examples.