Qwen3 Next 80B A3B Thinking
By Qwen. 81.3 billion parameters, a context window of 262,144 tokens and the licence apache-2.0.
Facts
- Released
- 2025-09-09 the day the repository was first published on Hugging Face Hugging Face, read
- Licence
- apache-2.0 the licence the model card declares Hugging Face, read
- Open weights
- Yes the weights are published in this Hugging Face repository Hugging Face, read
- Parameters
- 81.3 billion counted from the safetensors weight files Hugging Face, read
- Active parameters
- 5.5 billion estimate estimated from the expert counts and sizes in the configuration model configuration, read
- Knowledge cutoff
- 2025-09-30 the knowledge cutoff OpenRouter lists OpenRouter, read
- Context window
- 262,144 tokens the maximum position embeddings in the model configuration model configuration, read
- 262,144 tokens the context length OpenRouter lists OpenRouter, read
- Longest output
- 235,929 tokens the largest output OpenRouter's first provider allows OpenRouter, read
- Tool calling
- Yes the chat template in the tokenizer configuration accepts tool definitions Hugging Face, read
- Yes OpenRouter lists tools among the supported parameters OpenRouter, read
- Structured output
- Yes OpenRouter lists structured outputs among the supported parameters OpenRouter, read
- Reasoning controls
- Yes OpenRouter lists reasoning controls OpenRouter, read
- Inputs and outputs
- text in, text out Hugging Face, read
- Good for
- Reasoning: OpenRouter lists reasoning controls for it OpenRouter, read
Prices
| Provider | Input | Output | Context | As of | Source |
|---|---|---|---|---|---|
| NanoGPT direct | 0.150 USD | 0.650 USD | 256,000 | models.dev, read | |
| Alibaba through OpenRouter | 0.150 USD | 1.20 USD | 131,072 | OpenRouter endpoints, read | |
| Eden AI direct | 0.150 USD | 1.20 USD | 131,072 | models.dev, read | |
| Google through OpenRouter | 0.150 USD | 1.20 USD | 262,144 | OpenRouter endpoints, read | |
| Kilo Gateway direct | 0.150 USD | 1.20 USD | 262,144 | models.dev, read | |
| Merge Gateway direct | 0.150 USD | 1.20 USD | 131,072 | models.dev, read | |
| OpenRouter direct | 0.150 USD | 1.20 USD | 262,144 | models.dev, read | |
| Jiekou.AI direct | 0.150 USD | 1.50 USD | 65,536 | models.dev, read | |
| NovitaAI direct | 0.150 USD | 1.50 USD | 131,072 | older than 30 days; check the provider | models.dev, read |
| Hugging Face direct | 0.300 USD | 2.00 USD | 262,144 | older than 30 days; check the provider | models.dev, read |
Run it on your own hardware
Weights are the sizes of the files a source lists, or an estimate from the parameter count where none does. Memory is an estimate: weights plus KV cache plus 512 MiB and 5 percent of the weights for runtime buffers. Check it against your hardware.
| Quantization | Weights | Memory at 8,192 tokens | Memory at 32,768 tokens |
|---|---|---|---|
| IQ1_S | 15.4 GiB | 17.5 GiB | 19.7 GiB |
| IQ1_M | 16.1 GiB | 18.2 GiB | 20.4 GiB |
| IQ2_XS | 20.7 GiB | 23.0 GiB | 25.2 GiB |
| IQ2_S | 21.8 GiB | 24.1 GiB | 26.4 GiB |
| IQ2_M | 24.3 GiB | 26.8 GiB | 29.0 GiB |
| Q2_K | 26.2 GiB | 28.8 GiB | 31.0 GiB |
| Q2_K_L | 26.5 GiB | 29.1 GiB | 31.3 GiB |
| IQ3_XXS | 29.5 GiB | 32.3 GiB | 34.5 GiB |
| IQ3_XS | 30.8 GiB | 33.6 GiB | 35.8 GiB |
| Q3_K_S | 32.5 GiB | 35.3 GiB | 37.6 GiB |
| IQ3_M | 34.1 GiB | 37.1 GiB | 39.3 GiB |
| Q3_K_M | 34.1 GiB | 37.1 GiB | 39.3 GiB |
| Q3_K_L | 35.6 GiB | 38.6 GiB | 40.9 GiB |
| Q3_K_XL | 35.9 GiB | 38.9 GiB | 41.1 GiB |
| IQ4_XS | 39.9 GiB | 43.2 GiB | 45.4 GiB |
| IQ4_NL | 42.2 GiB | 45.6 GiB | 47.8 GiB |
| Q4_0 | 42.9 GiB | 46.3 GiB | 48.6 GiB |
| Q4_K_S | 43.7 GiB | 47.1 GiB | 49.4 GiB |
| Q4_K_M | 45.4 GiB | 48.9 GiB | 51.2 GiB |
| Q4_K_L | 45.6 GiB | 49.1 GiB | 51.4 GiB |
| Q4_1 | 46.8 GiB | 50.4 GiB | 52.6 GiB |
| Q5_K_S | 51.4 GiB | 55.2 GiB | 57.5 GiB |
| Q5_K_M | 53.1 GiB | 57.0 GiB | 59.2 GiB |
| Q5_K_L | 53.2 GiB | 57.2 GiB | 59.4 GiB |
| Q6_K | 61.3 GiB | 65.6 GiB | 67.8 GiB |
| Q6_K_L | 61.4 GiB | 65.7 GiB | 68.0 GiB |
| Q8_0 | 79.0 GiB | 84.2 GiB | 86.4 GiB |
Start it with a local runtime
- Ollama
ollama run hf.co/bartowski/Qwen_Qwen3-Next-80B-A3B-Thinking-GGUF:Q4_0 - LM Studio
lms get bartowski/Qwen_Qwen3-Next-80B-A3B-Thinking-GGUF lms server start - llama.cpp server
llama-server -hf bartowski/Qwen_Qwen3-Next-80B-A3B-Thinking-GGUF:Q4_0 --jinja - vLLM
vllm serve Qwen/Qwen3-Next-80B-A3B-Thinking - SGLang
sglang serve --model-path Qwen/Qwen3-Next-80B-A3B-Thinking --port 30000
Use it from your harness
Set up for Eden AI with the model qwen/qwen3-next-80b-a3b-thinking. Each endpoint page has the same setup for its own address.
OpenCode
Put this in opencode.json in your project folder:
{
"$schema": "https://opencode.ai/config.json",
"provider": {
"edenai": {
"npm": "@ai-sdk/openai-compatible",
"name": "Eden AI",
"options": {
"baseURL": "https://api.edenai.run/v3",
"apiKey": "{env:EDENAI_API_KEY}"
},
"models": {
"qwen/qwen3-next-80b-a3b-thinking": {
"name": "Qwen3 Next 80B A3B Thinking",
"limit": {
"context": 262144,
"output": 235929
}
}
}
}
}
}- OpenCode reads any OpenAI-compatible address through the @ai-sdk/openai-compatible package, and an address that speaks the Responses API through @ai-sdk/openai.
From OpenCode documentation, read .
Pi
Put this in ~/.pi/agent/models.json:
{
"providers": {
"edenai": {
"baseUrl": "https://api.edenai.run/v3",
"api": "openai-completions",
"apiKey": "$EDENAI_API_KEY",
"models": [
{
"id": "qwen/qwen3-next-80b-a3b-thinking"
}
]
}
}
}- The apiKey field can name an environment variable as $NAME.
From Pi documentation, read .
Codex
Codex speaks only the Responses API, and Eden AI documents no Responses address. A gateway that offers one can sit in between.
- Codex speaks the Responses API only: responses is the one supported wire API of a custom provider. Ollama and LM Studio are built in and start with --oss.
From Codex documentation, read .
Claude Code
Claude Code sends Anthropic Messages requests, and Eden AI documents no such address. A gateway that translates to that API can sit in between.
- Claude Code sends Anthropic Messages requests to ANTHROPIC_BASE_URL. Anthropic says it does not support routing Claude Code to models other than Claude through any gateway, so some features may not work with another model.
From Claude Code documentation, read .
Other ways to reach it
- Hugging Face, model
Qwen/Qwen3-Next-80B-A3B-Thinking - Jiekou.AI, model
qwen/qwen3-next-80b-a3b-thinking - Kilo Gateway, model
qwen/qwen3-next-80b-a3b-thinking - NanoGPT, model
qwen/qwen3-next-80b-a3b-thinking - NovitaAI, model
qwen/qwen3-next-80b-a3b-thinking - OpenRouter, model
qwen/qwen3-next-80b-a3b-thinking - Ollama, model
hf.co/bartowski/Qwen_Qwen3-Next-80B-A3B-Thinking-GGUF:Q4_0
Published results
These are results other people published. Baltor did not run them and does not rank models by them.
- Results the maker published on the model card published by Qwen Hugging Face, read
- Artificial Analysis Coding Index: 17.4 published by Artificial Analysis OpenRouter, read
Sources of this page
- huggingface.co/api/models/Qwen/Qwen3-Next-80B-A3B-Thinking, read
- huggingface.co/Qwen/Qwen3-Next-80B-A3B-Thinking/raw/main/config.json, read
- huggingface.co/api/models/bartowski/Qwen_Qwen3-Next-80B-A3B-Thinking-GGUF/tree/main, read
- openrouter.ai/api/v1/models/qwen/qwen3-next-80b-a3b-thinking-2509/endpoints, read
- openrouter.ai/api/v1/models, read
- models.dev/api.json, read
Paid links
No link in this directory is a paid link or an ad, and no listing is paid for. The order and the contents of every list come from the sources named on this page.