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Models

Qwen3 Coder Next

By Qwen. 79.7 billion parameters, a context window of 262,144 tokens and the licence apache-2.0.

Facts

Released
2026-01-30 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
79.7 billion counted from the safetensors weight files Hugging Face, read
Active parameters
3.9 billion estimate estimated from the expert counts and sizes in the configuration model configuration, read
Knowledge cutoff
Unknown
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
Unknown
Inputs and outputs
text in, text out Hugging Face, read
Good for
  • Coding: the maker's name for the model marks it for code Hugging Face, read

Prices

Prices in US dollars per million tokens, as each source lists them
ProviderInputOutputContextAs ofSource
OpenRouter direct0.120 USD0.800 USD262,144 older than 30 days; check the providermodels.dev, read
Parasail through OpenRouter0.120 USD0.800 USD262,144OpenRouter endpoints, read
Merge Gateway direct0.150 USD0.800 USD262,144 older than 30 days; check the providermodels.dev, read
StreamLake through OpenRouter0.180 USD0.900 USD256,000OpenRouter endpoints, read
Hugging Face direct0.200 USD1.50 USD262,144 older than 30 days; check the providermodels.dev, read
Jiekou.AI direct0.200 USD1.50 USD262,144models.dev, read
NanoGPT direct0.200 USD1.50 USD262,144 older than 30 days; check the providermodels.dev, read
Novita through OpenRouter0.200 USD1.50 USD262,144OpenRouter endpoints, read
NovitaAI direct0.200 USD1.50 USD262,144 older than 30 days; check the providermodels.dev, read
Ofox direct0.200 USD1.50 USD256,000 older than 30 days; check the providermodels.dev, read
Alibaba through OpenRouter0.300 USD1.50 USD262,144OpenRouter endpoints, read
Eden AI direct0.300 USD1.50 USD262,144 older than 30 days; check the providermodels.dev, read
Kilo Gateway direct0.300 USD1.50 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
UD-TQ1_017.6 GiB19.8 GiB22.0 GiB
UD-IQ1_S20.0 GiB22.3 GiB24.5 GiB
UD-IQ1_M20.2 GiB22.5 GiB24.7 GiB
UD-IQ2_XXS21.7 GiB24.0 GiB26.3 GiB
UD-IQ2_M23.2 GiB25.7 GiB27.9 GiB
UD-Q2_K_XL24.9 GiB27.4 GiB29.7 GiB
Q2_K27.2 GiB29.8 GiB32.1 GiB
Q2_K_L27.3 GiB29.9 GiB32.1 GiB
UD-IQ3_S27.7 GiB30.3 GiB32.5 GiB
UD-Q3_K_S31.0 GiB33.8 GiB36.1 GiB
Q3_K_S32.2 GiB35.1 GiB37.3 GiB
UD-Q3_K_M33.5 GiB36.4 GiB38.6 GiB
UD-Q3_K_XL33.8 GiB36.7 GiB39.0 GiB
Q3_K_M35.7 GiB38.7 GiB41.0 GiB
UD-IQ4_NL36.5 GiB39.6 GiB41.9 GiB
IQ4_XS39.7 GiB43.0 GiB45.2 GiB
IQ4_NL42.0 GiB45.4 GiB47.6 GiB
Q4_042.2 GiB45.6 GiB47.8 GiB
Q4_K_S42.4 GiB45.8 GiB48.0 GiB
UD-Q4_K_S42.9 GiB46.3 GiB48.6 GiB
MXFP4_MOE44.7 GiB48.2 GiB50.5 GiB
Q4_K_M45.2 GiB48.7 GiB51.0 GiB
UD-Q4_K_M45.9 GiB49.5 GiB51.7 GiB
UD-Q4_K_XL46.2 GiB49.8 GiB52.0 GiB
Q4_146.6 GiB50.2 GiB52.5 GiB
Q5_K_S51.3 GiB55.1 GiB57.3 GiB
UD-Q5_K_S52.0 GiB55.8 GiB58.1 GiB
Q5_K_M52.9 GiB56.8 GiB59.1 GiB
UD-Q5_K_M55.2 GiB59.2 GiB61.4 GiB
UD-Q5_K_XL55.5 GiB59.5 GiB61.7 GiB
Q6_K61.1 GiB65.4 GiB67.7 GiB
UD-Q6_K61.3 GiB65.6 GiB67.8 GiB
UD-Q6_K_XL68.1 GiB72.8 GiB75.0 GiB
Q8_079.0 GiB84.2 GiB86.4 GiB
UD-Q8_K_XL80.4 GiB85.7 GiB87.9 GiB
BF16149 GiB157 GiB159 GiB

Start it with a local runtime

  • Ollama
    ollama run hf.co/unsloth/Qwen3-Coder-Next-GGUF:Q4_0
  • LM Studio
    lms get unsloth/Qwen3-Coder-Next-GGUF
    lms server start
  • llama.cpp server
    llama-server -hf unsloth/Qwen3-Coder-Next-GGUF:Q4_0 --jinja
  • vLLM
    vllm serve Qwen/Qwen3-Coder-Next
  • SGLang
    sglang serve --model-path Qwen/Qwen3-Coder-Next --port 30000

Use it from your harness

Set up for Eden AI with the model qwen/qwen3-coder-next. 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-coder-next": {
          "name": "Qwen3 Coder Next",
          "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-coder-next"
        }
      ]
    }
  }
}
  • 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

Published results

These are results other people published. Baltor did not run them and does not rank models by them.