> ## Documentation Index
> Fetch the complete documentation index at: https://docs.gourmand.dev/llms.txt
> Use this file to discover all available pages before exploring further.

# Model Setup for Agent Mode

> Learn how to set up models for Agent Mode in Gobi, including recommended models and configuration options for optimal performance

export const ModelRecommendations = ({role = "all"}) => {
  const parseMarkdownLinks = text => {
    const regex = /\[([^\]]+)\]\(([^)]+)\)/g;
    const parts = [];
    let lastIndex = 0;
    let match;
    let key = 0;
    while ((match = regex.exec(text)) !== null) {
      if (match.index > lastIndex) {
        const beforeText = text.slice(lastIndex, match.index);
        if (beforeText) {
          parts.push(<span key={key++}>{beforeText}</span>);
        }
      }
      const [, linkText, url] = match;
      parts.push(<a key={key++} href={url} target="_blank" rel="noopener noreferrer" style={{
        color: "#0066cc",
        textDecoration: "underline"
      }}>
          {linkText}
        </a>);
      lastIndex = regex.lastIndex;
    }
    if (lastIndex < text.length) {
      const remainingText = text.slice(lastIndex);
      if (remainingText) {
        parts.push(<span key={key++}>{remainingText}</span>);
      }
    }
    return parts.length > 0 ? parts : text;
  };
  const modelRecs = {
    agent_plan: {
      open: ["[Qwen3 Coder (480B)](https://hub.gourmand.dev/openrouter/qwen3-coder)", "[Qwen3 Coder (30B)](https://hub.gourmand.dev/ollama/qwen3-coder-30b)", "[Devstral (27B)](https://hub.gourmand.dev/ollama/devstral)", "[Kimi K2 (1T)](https://hub.gourmand.dev/openrouter/kimi-k2)", "[gpt-oss (120B)](https://hub.gourmand.dev/openrouter/gpt-oss-120b)", "[gpt-oss (20B)](https://hub.gourmand.dev/ollama/gpt-oss-20b)", "[GLM 4.5 (355B)](https://hub.gourmand.dev/openrouter/glm-4-5)", "[GLM 4.5 Air (106B)](https://hub.gourmand.dev/openrouter/glm-4-5-air)"],
      closed: ["[Claude Opus 4.1](https://hub.gourmand.dev/anthropic/claude-4-1-opus)", "[Claude Sonnet 4](https://hub.gourmand.dev/anthropic/claude-4-sonnet)", "[GPT-5](https://hub.gourmand.dev/openai/gpt-5)", "[Gemini 2.5 Pro](https://hub.gourmand.dev/google/gemini-2.5-pro)"],
      notes: "Closed models are slightly better than open models"
    },
    chat_edit: {
      open: ["[Qwen3 Coder (480B)](https://hub.gourmand.dev/openrouter/qwen3-coder)", "[Qwen3 Coder (30B)](https://hub.gourmand.dev/ollama/qwen3-coder-30b)", "[gpt-oss (120B)](https://hub.gourmand.dev/openrouter/gpt-oss-120b)", "[gpt-oss (20B)](https://hub.gourmand.dev/ollama/gpt-oss-20b)"],
      closed: ["[Claude Opus 4.1](https://hub.gourmand.dev/anthropic/claude-4-1-opus)", "[Claude Sonnet 4](https://hub.gourmand.dev/anthropic/claude-4-sonnet)", "[GPT-5](https://hub.gourmand.dev/openai/gpt-5)", "[Gemini 2.5 Pro](https://hub.gourmand.dev/google/gemini-2.5-pro)"],
      notes: "Closed and open models have pretty similar performance"
    },
    autocomplete: {
      open: ["[QwenCoder2.5 (1.5B)](https://hub.gourmand.dev/ollama/qwen2.5-coder-1.5b)", "[QwenCoder2.5 (7B)](https://hub.gourmand.dev/ollama/qwen2.5-coder-7b)"],
      closed: ["[Codestral](https://hub.gourmand.dev/mistral/codestral)", "[Mercury Coder](https://hub.gourmand.dev/inception/mercury-coder)"],
      notes: "Closed models are slightly better than open models"
    },
    apply: {
      open: ["N/A"],
      closed: ["[Relace Instant Apply](https://hub.gourmand.dev/relace/instant-apply)", "[Morph Fast Apply](https://hub.gourmand.dev/morphllm/morph-v2)"],
      notes: "Open models are not good enough for this model role"
    },
    embed: {
      open: ["[Nomic Embed Text](https://hub.gourmand.dev/ollama/nomic-embed-text-latest)", "Qwen3 Embedding"],
      closed: ["[Voyage Code 3](https://hub.gourmand.dev/voyageai/voyage-code-3)", "[Morph Embeddings](https://hub.gourmand.dev/morphllm/morph-embedding-v2)", "Codestral Embed"],
      notes: "Closed models are slightly better than open models"
    },
    rerank: {
      open: ["zerank-1", "zerank-1-small", "Qwen3 Reranker"],
      closed: ["[Voyage Rerank 2.5](https://hub.gourmand.dev/voyageai/rerank-2-5)", "Relace Code Rerank", "[Morph Rerank](https://hub.gourmand.dev/morphllm/morph-rerank-v2)"],
      notes: "Open models are beginning to emerge for this model role"
    },
    next_edit: {
      open: ["[Instinct](https://hub.gourmand.dev/gobi/instinct)"],
      closed: ["[Mercury Coder](https://hub.gourmand.dev/inception/mercury-coder)"],
      notes: "Closed models are better than open models"
    }
  };
  let rolesToShow = [];
  if (!role || role === "all") {
    rolesToShow = Object.keys(modelRecs);
  } else {
    const key = role.toLowerCase().replace(/\s|\//g, "_").replace(/-/g, "_");
    if (modelRecs[key]) {
      rolesToShow = [key];
    }
  }
  if (rolesToShow.length === 0) {
    return <div>No recommendations found for role: {role}</div>;
  }
  return <table style={{
    width: "100%",
    borderCollapse: "collapse",
    marginTop: "1rem"
  }}>
      <thead>
        <tr>
          <th style={{
    textAlign: "left",
    borderBottom: "1px solid #ddd",
    padding: "8px"
  }}>
            Model role
          </th>
          <th style={{
    textAlign: "left",
    borderBottom: "1px solid #ddd",
    padding: "8px"
  }}>
            Best open models
          </th>
          <th style={{
    textAlign: "left",
    borderBottom: "1px solid #ddd",
    padding: "8px"
  }}>
            Best closed models
          </th>
          <th style={{
    textAlign: "left",
    borderBottom: "1px solid #ddd",
    padding: "8px"
  }}>
            Notes
          </th>
        </tr>
      </thead>
      <tbody>
        {rolesToShow.map(roleKey => {
    const rec = modelRecs[roleKey];
    if (!rec) return null;
    return <tr key={roleKey}>
              <td style={{
      fontWeight: 600,
      verticalAlign: "top",
      padding: "8px"
    }}>
                {roleKey.replace(/_/g, " ").replace(/\b\w/g, l => l.toUpperCase())}
              </td>
              <td style={{
      padding: "8px",
      verticalAlign: "top"
    }}>
                {rec.open.map((m, i) => <div key={i} style={{
      marginBottom: "4px"
    }}>
                    {parseMarkdownLinks(m)}
                  </div>)}
              </td>
              <td style={{
      padding: "8px",
      verticalAlign: "top"
    }}>
                {rec.closed.map((m, i) => <div key={i} style={{
      marginBottom: "4px"
    }}>
                    {parseMarkdownLinks(m)}
                  </div>)}
              </td>
              <td style={{
      padding: "8px",
      verticalAlign: "top"
    }}>
                {rec.notes}
              </td>
            </tr>;
  })}
      </tbody>
    </table>;
};

The models you set up for Chat mode will be used with Agent mode if the model supports tool calling. The recommended models and how to set them up can be found [here](/ide-extensions/chat/model-setup).

## How System Message Tools Work

Gobi implements an innovative approach called **system message tools** that ensures consistent tool functionality across all models, regardless of their native capabilities. This allows Agent mode to work seamlessly with a wider range of models and providers.

### How System Message Tools Function

Instead of relying solely on native tool calling APIs (which vary between providers), Gobi converts tools into XML format and includes them in the system message. The model generates tool calls as structured XML within its response, which Gobi then parses and executes. This approach provides:

* **Universal compatibility** - Any model capable of following instructions can use tools, not just those with native tool support
* **Consistent behavior** - Tool calls work identically across OpenAI, Anthropic, local models, and others
* **Better reliability** - Models that struggle with native tools often perform better with system message tools
* **Seamless switching** - Change between providers without modifying your workflow

## Recommended Agent Models

<ModelRecommendations role="all" />

### How to Configure Agent Mode

Agent mode automatically determines whether to use native or system message tools based on the model's capabilities. No additional configuration is required - simply select your model and Gobi handles the rest.

## How to Check Model Compatibility

To see which models support specific features like tool use (for Agent mode) and image input, check out our [Model Capabilities guide](/customize/deep-dives/model-capabilities).