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Models

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

Prices in US dollars per million tokens, as each source lists them
ProviderInputOutputContextAs ofSource
NanoGPT direct0.150 USD0.650 USD256,000models.dev, read
Alibaba through OpenRouter0.150 USD1.20 USD131,072OpenRouter endpoints, read
Eden AI direct0.150 USD1.20 USD131,072models.dev, read
Google through OpenRouter0.150 USD1.20 USD262,144OpenRouter endpoints, read
Kilo Gateway direct0.150 USD1.20 USD262,144models.dev, read
Merge Gateway direct0.150 USD1.20 USD131,072models.dev, read
OpenRouter direct0.150 USD1.20 USD262,144models.dev, read
Jiekou.AI direct0.150 USD1.50 USD65,536models.dev, read
NovitaAI direct0.150 USD1.50 USD131,072 older than 30 days; check the providermodels.dev, read
Hugging Face direct0.300 USD2.00 USD262,144 older than 30 days; check the providermodels.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.

QuantizationWeightsMemory at 8,192 tokensMemory at 32,768 tokens
IQ1_S15.4 GiB17.5 GiB19.7 GiB
IQ1_M16.1 GiB18.2 GiB20.4 GiB
IQ2_XS20.7 GiB23.0 GiB25.2 GiB
IQ2_S21.8 GiB24.1 GiB26.4 GiB
IQ2_M24.3 GiB26.8 GiB29.0 GiB
Q2_K26.2 GiB28.8 GiB31.0 GiB
Q2_K_L26.5 GiB29.1 GiB31.3 GiB
IQ3_XXS29.5 GiB32.3 GiB34.5 GiB
IQ3_XS30.8 GiB33.6 GiB35.8 GiB
Q3_K_S32.5 GiB35.3 GiB37.6 GiB
IQ3_M34.1 GiB37.1 GiB39.3 GiB
Q3_K_M34.1 GiB37.1 GiB39.3 GiB
Q3_K_L35.6 GiB38.6 GiB40.9 GiB
Q3_K_XL35.9 GiB38.9 GiB41.1 GiB
IQ4_XS39.9 GiB43.2 GiB45.4 GiB
IQ4_NL42.2 GiB45.6 GiB47.8 GiB
Q4_042.9 GiB46.3 GiB48.6 GiB
Q4_K_S43.7 GiB47.1 GiB49.4 GiB
Q4_K_M45.4 GiB48.9 GiB51.2 GiB
Q4_K_L45.6 GiB49.1 GiB51.4 GiB
Q4_146.8 GiB50.4 GiB52.6 GiB
Q5_K_S51.4 GiB55.2 GiB57.5 GiB
Q5_K_M53.1 GiB57.0 GiB59.2 GiB
Q5_K_L53.2 GiB57.2 GiB59.4 GiB
Q6_K61.3 GiB65.6 GiB67.8 GiB
Q6_K_L61.4 GiB65.7 GiB68.0 GiB
Q8_079.0 GiB84.2 GiB86.4 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.