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Models

Nex-N2.5-Pro (free)

By Nex AGI. 396.8 billion parameters, a context window of 262,144 tokens and the licence apache-2.0.

Facts

Released
2026-09-08 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
396.8 billion counted from the safetensors weight files Hugging Face, read
Active parameters
17.8 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
  • Yes OpenRouter lists reasoning controls, with the efforts high, medium, none OpenRouter, read
Inputs and outputs
text in, text out Hugging Face, read
Good for
  • Reasoning: OpenRouter lists reasoning controls for it OpenRouter, read
  • Vision: OpenRouter lists images among its inputs OpenRouter, read

Prices

No source lists a price for this model. It may only run on your own hardware.

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_S81.8 GiB86.7 GiB87.4 GiB
IQ1_M91.3 GiB96.6 GiB97.3 GiB
IQ2_XXS107 GiB113 GiB114 GiB
IQ2_XS113 GiB119 GiB120 GiB
IQ2_S119 GiB126 GiB126 GiB
IQ2_M133 GiB140 GiB141 GiB
Q2_K140 GiB148 GiB149 GiB
IQ3_XXS158 GiB167 GiB167 GiB
IQ3_XS166 GiB175 GiB176 GiB
Q3_K_S168 GiB177 GiB177 GiB
Q3_K_M177 GiB186 GiB187 GiB
Q3_K_L186 GiB197 GiB197 GiB
IQ3_M195 GiB206 GiB206 GiB
IQ4_XS204 GiB215 GiB216 GiB
Q4_0210 GiB221 GiB222 GiB
Q4_K_S217 GiB229 GiB230 GiB
Q4_1232 GiB244 GiB245 GiB
IQ4_NL232 GiB245 GiB245 GiB
Q4_K_M234 GiB246 GiB247 GiB
Q5_K_S263 GiB277 GiB278 GiB
Q5_K_M285 GiB300 GiB300 GiB
Q6_K_S310 GiB327 GiB327 GiB
Q6_K326 GiB343 GiB344 GiB
Q8_0393 GiB413 GiB414 GiB

Start it with a local runtime

  • Ollama
    ollama run hf.co/bartowski/Nex-N2.5-Pro-GGUF:Q4_0
  • LM Studio
    lms get bartowski/Nex-N2.5-Pro-GGUF
    lms server start
  • llama.cpp server
    llama-server -hf bartowski/Nex-N2.5-Pro-GGUF:Q4_0 --jinja
  • vLLM
    vllm serve nex-agi/Nex-N2.5-Pro
  • SGLang
    sglang serve --model-path nex-agi/Nex-N2.5-Pro --port 30000

Use it from your harness

Set up for Ollama with the model hf.co/bartowski/Nex-N2.5-Pro-GGUF:Q4_0. 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": {
    "ollama": {
      "npm": "@ai-sdk/openai-compatible",
      "name": "Ollama",
      "options": {
        "baseURL": "http://localhost:11434/v1"
      },
      "models": {
        "hf.co/bartowski/Nex-N2.5-Pro-GGUF:Q4_0": {
          "name": "Nex-N2.5-Pro (free)",
          "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": {
    "ollama": {
      "baseUrl": "http://localhost:11434/v1",
      "api": "openai-completions",
      "apiKey": "ollama",
      "models": [
        {
          "id": "hf.co/bartowski/Nex-N2.5-Pro-GGUF:Q4_0"
        }
      ]
    }
  }
}
  • The apiKey field can name an environment variable as $NAME.

From Pi documentation, read .

Codex

Put this in a terminal:

codex --oss --local-provider ollama -m hf.co/bartowski/Nex-N2.5-Pro-GGUF:Q4_0
  • 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

Put this in ~/.claude/settings.json, or variables in your shell:

export ANTHROPIC_BASE_URL="http://localhost:11434"
export ANTHROPIC_AUTH_TOKEN="ollama"
export ANTHROPIC_MODEL="hf.co/bartowski/Nex-N2.5-Pro-GGUF:Q4_0"
claude
  • 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 .

Published results

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