Coding agents

Before you start

export GRAPHN_API_KEY="gn_..."

curl https://model.graphn.ai/v1/messages \
  -H "x-api-key: $GRAPHN_API_KEY" \
  -H "content-type: application/json" \
  -d '{"model": "deepseek-v4.1-flash", "max_tokens": 64,
       "messages": [{"role": "user", "content": "Say hi"}]}'

Claude Code

export ANTHROPIC_BASE_URL=https://model.graphn.ai
export ANTHROPIC_API_KEY="$GRAPHN_API_KEY"
export ANTHROPIC_MODEL=deepseek-v4.1-flash
export ANTHROPIC_DEFAULT_OPUS_MODEL=deepseek-v4.1-flash
export ANTHROPIC_DEFAULT_SONNET_MODEL=deepseek-v4.1-flash
export ANTHROPIC_DEFAULT_HAIKU_MODEL=deepseek-v4.1-flash
export CLAUDE_CODE_MAX_CONTEXT_TOKENS=1048576
export CLAUDE_CODE_AUTO_MODE_SERVER=0
claude

• Set every model variable. Claude Code sends background work, such as titles and summaries, to its Haiku model, and subagents launched with the Task tool use its Opus model. Any of those left unset asks for a claude- model and gets 404 model not found, so a subagent fails while the main session keeps working.
• Tell it the real context window. Claude Code assumes 200K tokens for a model it doesn't know and compacts the conversation at that point. CLAUDE_CODE_MAX_CONTEXT_TOKENS sets the model's actual window, so DeepSeek gets its full 1M and gpt-oss-120b compacts before 131K.
• Turn off server-side auto mode checks. In auto mode, Claude Code normally asks Anthropic's servers to check each action. Those checks don't exist on GraphN, so without CLAUDE_CODE_AUTO_MODE_SERVER=0 Claude Code pauses on a notice saying the session "isn't eligible". With it set, Claude Code runs its own checks on your GraphN model, billed at GraphN's rates.
• Ignore its cost readout. Claude Code estimates cost at Anthropic's prices. Your GraphN usage page shows what you are actually billed.

Codex

model = "deepseek-v4.1-flash"
model_provider = "graphn"
model_context_window = 1048576

[model_providers.graphn]
name = "GraphN"
base_url = "https://model.graphn.ai/v1"
env_key = "GRAPHN_API_KEY"
wire_api = "responses"

model = "kimi-k2.5"
model_context_window = 256000

• Model metadata for … not found is harmless. Codex prints it for any model outside OpenAI's catalog. model_context_window gives Codex what it needs to compact a long session at the right point.
• The Responses API on GraphN is stateless. Nothing is stored between requests, so previous_response_id, conversation and background are refused. Codex sends the full conversation every turn, so it is unaffected.

Cursor

1. Open Cursor Settings > Models and expand API Keys.
2. Paste your GraphN key into OpenAI API Key and turn it on.
3. Turn on Override OpenAI Base URL and set it to https://model.graphn.ai/v1.
4. Add each model by its GraphN ID, such as deepseek-v4.1-flash, then pick it in Chat or Agent.

• Pick an ID Cursor doesn't also ship. Cursor sends the model name you choose, so a name that exists in its own catalog, such as kimi-k2.5, goes to Cursor's copy rather than GraphN's and fails with a not-found or "model is deprecated" error. deepseek-v4.1-flash doesn't collide.
• Cursor calls GraphN from its own servers, so a request from Cursor shows in your Logs like any other.
• Your key covers Chat and Agent. Tab completion keeps using Cursor's models.
• The base URL override is global. It applies to every OpenAI model in Cursor, so turn it off when you want Cursor's built-in OpenAI models back.
• Check your plan. Cursor's Free and Plus plans don't allow your own API key.

OpenCode

{
  "$schema": "https://opencode.ai/config.json",
  "provider": {
    "graphn": {
      "npm": "@ai-sdk/openai-compatible",
      "name": "GraphN",
      "options": {
        "baseURL": "https://model.graphn.ai/v1",
        "apiKey": "{env:GRAPHN_API_KEY}"
      },
      "models": {
        "deepseek-v4.1-flash": { "name": "DeepSeek V4.1 Flash" },
        "glm-5.3": {
          "name": "GLM-5.3",
          "options": { "reasoningEffort": "high" }
        }
      }
    }
  }
}

• Bound GLM-5.3's thinking. Without a reasoning effort, GLM-5.3 can think until it hits the output limit, and OpenCode then ends the session without a word. "reasoningEffort": "high" keeps its thinking bounded.

Troubleshooting

Next steps

• Coding Agent Support Is Now Available on GraphN compares the agents on a real bug fix across these models, with cost per session.
• Getting started with inference covers the API itself: streaming, thinking and parameters.