Using another model via OpenRouter

Claude Code can talk to any Anthropic-compatible backend. MulmoTerminal reads those backends from its config, their keys from the environment the server was started with, and lets you choose a model per session — so Kimi, DeepSeek, GLM, Gemini, GPT or Grok run in the same terminal you already use.

This page walks through OpenRouter end to end, from the first setup to adding models of your own. Moonshot, a company LiteLLM gateway, or any other Anthropic-compatible backend follows the same steps.

The shape of it

Configuration lives in three places, each for a reason:

What Where Why there
The backend (URL, name of the key variable) providers in ~/.mulmoterminal/config.json shared by the whole app. Nothing ships built in — without this, there is nothing to choose
The API key the server’s environment (.env) that config file is served to the browser and the phone — a key must never be in it
The default model a project’s .mulmoterminal.json it differs per project

On top of that, you can pick per session at launch — without rewriting the default.

1. Get an OpenRouter key

  1. Create an account at openrouter.ai
  2. Issue an API key under Keys (sk-or-…)
  3. Add credit — usage-based, and some models below are $0.08 per million input tokens

Also check your privacy settings. If they exclude every provider serving a model, that model answers 404 No endpoints available. The rows marked unreachable in the table below hit exactly that — not a defect in the model.

2. Register the backend (required)

Without this, there is no MODEL select at all. No backend ships with the app.

The 27 measured models are built in, but what they carry is only the model id and its measurements. Where to send requests (baseUrl) and which environment variable holds the key (tokenEnv) are not in them, so until a provider is registered there is nowhere to send anything. Measured:

providers Models offered MODEL select
unset (fresh install) 0 hidden
registered (id = openrouter) 27 shown

Add it in one command

Adds the provider without disturbing the rest of your config — it backs the file up to config.json.bak first, and running it twice does not duplicate the entry.

node -e '
const fs = require("fs"), os = require("os"), path = require("path");
const file = path.join(os.homedir(), ".mulmoterminal", "config.json");
const config = fs.existsSync(file) ? JSON.parse(fs.readFileSync(file, "utf8")) : {};
if (fs.existsSync(file)) fs.copyFileSync(file, file + ".bak");
config.providers = [
  ...(config.providers ?? []).filter((p) => p.id !== "openrouter"),
  { id: "openrouter", label: "OpenRouter", baseUrl: "https://openrouter.ai/api", tokenEnv: "OPENROUTER_API_KEY", maxOutputTokens: 16000 },
];
fs.mkdirSync(path.dirname(file), { recursive: true });
fs.writeFileSync(file, JSON.stringify(config, null, 2) + "\n");
console.log("added openrouter to " + file);
'

Or write it by hand

If ~/.mulmoterminal/config.json does not exist yet, paste this as the whole file:

{
  "providers": [
    {
      "id": "openrouter",
      "label": "OpenRouter",
      "baseUrl": "https://openrouter.ai/api",
      "tokenEnv": "OPENROUTER_API_KEY",
      "maxOutputTokens": 16000
    }
  ]
}

If the file already exists, add the providers key inside the existing { … } — do not replace the file. Replacing it drops your cwdPresets, header buttons and everything else.

{
  "cwdPresets": [ ... keep yours ... ],
  "chips": [ ... keep yours ... ],

  "providers": [
    {
      "id": "openrouter",
      "label": "OpenRouter",
      "baseUrl": "https://openrouter.ai/api",
      "tokenEnv": "OPENROUTER_API_KEY",
      "maxOutputTokens": 16000
    }
  ]
}

Or ask an LLM

In any directory, tell a Claude session add OpenRouter to my mulmoterminal config. The bundled mulmoterminal-config skill keeps your existing settings and writes a valid entry — without your key in it.

Do not list models here. Registering a provider with this id is enough — the 27 measured models appear in the picker on their own. You only list models to add ones that are not in that list (→ Adding models).

Key Meaning
id the name other settings refer to; letters, digits and . _ : / - ~. The built-in 27 models appear only when id is exactly openrouter — any other id (Moonshot, an in-house LiteLLM, …) gets no presets, so list models by hand
label what the picker shows
baseUrl no trailing /v1 — see below
tokenEnv the name of the environment variable holding the key, never the key
maxOutputTokens optional; defaults to 16000
models optional; only to add models not in the built-in list (→ Adding models)

Never end baseUrl in /v1

Claude Code appends /v1/messages itself, so https://openrouter.ai/api/v1 produces …/v1/v1/messages and every request 404s. MulmoTerminal rejects it before launching and says why.

Do not lower maxOutputTokens

Starved of output headroom, a thinking model spends its whole budget thinking and returns empty visible text — which reads as a hung session. Keep it at 16000 or above.

3. Put the key in the server’s environment

In the shell that starts MulmoTerminal, or a .env beside it:

OPENROUTER_API_KEY=sk-or-…

Never put it in the config file. config.json is served to the browser and the phone through GET /api/config — that is exactly why tokenEnv is a variable name.

Restart the server afterwards; the environment is read at startup.

A provider whose key cannot be resolved refuses to start the session. Quietly falling back to Anthropic would send that session’s prompts to a backend the directory never selected.

4. Use it

Choose at launch

Once at least one provider is usable, the empty cell’s launch form grows a MODEL select.

  • The choice applies to that session only
  • It does not rewrite .mulmoterminal.json
  • Choosing nothing keeps the directory’s default

Once the session runs, the badge on the header’s first row shows the running model and how full its context is — Kimi K2.7 Code · ctx 12%. If you don’t see it, check that ctx is in your chips.

Make it a project default

In that project’s .mulmoterminal.json:

{
  "provider": "openrouter",
  "model": "moonshotai/kimi-k2.7-code"
}

Omit provider and give only model to pick a different model on Anthropic itself.

Ids may contain letters, digits and . _ : / - ~ — the same rule as a provider’s id, so OpenRouter’s “always the latest” aliases such as ~anthropic/claude-opus-latest work too. A value shaped differently (whitespace, a leading dash) makes sessions in that directory refuse to start, rather than quietly running on some other model. The directory’s other settings still load.

What happens on resume

  • A model picked at launch is kept when that session resumes (for as long as the server runs)
  • A .mulmoterminal.json default is live like every other field there — edit it and the next launch uses it

5. Adding models

Models outside the built-in presets work too.

List them in the config 

{
  "providers": [
    {
      "id": "openrouter",
      "label": "OpenRouter",
      "baseUrl": "https://openrouter.ai/api",
      "tokenEnv": "OPENROUTER_API_KEY",
      "models": ["qwen/qwen3-coder", "inception/mercury-coder"]
    }
  ]
}

They appear in the picker marked not tested — meaning we have not checked them, which is more honest than implying we had.

Model ids are the vendor/model strings shown on each model’s page at openrouter.ai/models.

Or ask an LLM to configure it

If you would rather not edit JSON, ask a Claude session in any directory:

set up OpenRouter in my mulmoterminal config

The bundled mulmoterminal-config skill knows this file’s shape and the tested model list, and writes a valid config — without ever writing your key into it.

Measure whether a model actually works

Answering a prompt and driving Claude Code are different things. Measured here, some models replied fluently and never called a tool once — one printed Read(file_path=…) as prose instead of using it.

So a probe that cannot be completed by talking — read one file, write another — runs through the real spawn path:

yarn tsx scripts/model-trials.ts --provider openrouter --trials 3 qwen/qwen3-coder

3/3    16s    qwen/qwen3-coder

Two models flipped between pass and fail across runs, so this records a ratio, not a verdict. The numbers in the built-in presets (common/modelPresets.ts) were measured the same way.

Measured models

As of 2026-07-22, from a single OpenRouter account. Passed is how many attempts completed the tool-using probe above; median is over the attempts that passed; price is per million input / output tokens.

Model id Name Passed Median Context Price (in/out)
nvidia/nemotron-3-super-120b-a12b Nemotron 3 Super 120B 3/3 18s 1M $0.08 / $0.45
qwen/qwen3-235b-a22b-2507 Qwen3 235B A22B 3/3 16s 262k $0.09 / $0.55
minimax/minimax-m2.7 MiniMax M2.7 3/3 16s 205k $0.25 / $1
deepseek/deepseek-v3.2 DeepSeek V3.2 3/3 42s 164k $0.269 / $0.4
minimax/minimax-m3 MiniMax M3 3/3 14s 1M $0.3 / $1.2
deepseek/deepseek-v4-pro DeepSeek V4 Pro 3/3 20s 1M $0.435 / $0.87
deepseek/deepseek-v4-flash DeepSeek V4 Flash 3/4 26s 1M $0.094 / $0.188
openai/gpt-oss-120b GPT-OSS 120B 3/4 18s 131k $0.037 / $0.17
moonshotai/kimi-k2-0905 Kimi K2 0905 3/3 18s 262k $0.6 / $2.5
moonshotai/kimi-k2-thinking Kimi K2 Thinking 3/3 20s 262k $0.6 / $2.5
moonshotai/kimi-k2.6 Kimi K2.6 3/3 46s 262k $0.684 / $3.42
z-ai/glm-5.2 GLM 5.2 3/3 21s 1M $0.819 / $2.574
moonshotai/kimi-k2.7-code Kimi K2.7 Code 3/3 14s 262k $0.82 / $3.75
moonshotai/kimi-k3 Kimi K3 3/3 29s 1M $3 / $15
tencent/hy3 Tencent Hy3 3/3 17s 262k $0.14 / $0.58
nvidia/nemotron-3-ultra-550b-a55b Nemotron 3 Ultra 550B 3/3 13s 512k $0.6 / $3.6
google/gemini-3.5-flash-lite Gemini 3.5 Flash-Lite 3/3 11s 1M $0.3 / $2.5
amazon/nova-2-lite-v1 Nova 2 Lite 2/3 20s 1M $0.3 / $2.5
openai/gpt-5.6-luna GPT-5.6 Luna 3/3 27s 1M $1 / $6
openai/gpt-5.6-luna-pro GPT-5.6 Luna Pro 3/3 69s 1M $1 / $6
google/gemini-3.6-flash Gemini 3.6 Flash 3/3 16s 1M $1.5 / $7.5
x-ai/grok-4.5 Grok 4.5 3/3 13s 500k $2 / $6
openai/gpt-5.6-terra-pro GPT-5.6 Terra Pro 3/3 38s 1M $2.5 / $15
meta-llama/llama-4-maverick Llama 4 Maverick 0/4 — 1M $0.2 / $0.8
qwen/qwen3.7-plus Qwen3.7 Plus unreachable * — 1M $0.32 / $1.28
mistralai/mistral-medium-3-5 Mistral Medium 3.5 unreachable * — 262k $1.5 / $7.5
mistralai/devstral-2512 Devstral 2512 unreachable * — 262k $0.4 / $2

* unreachable — the account used for the measurement had every serving provider excluded by its privacy settings. Not a defect in the model; another account may run it fine.

meta-llama/llama-4-maverick passed 0 of 4. It connects and replies, but never calls a tool. It stays in the list rather than being dropped, so “what about that one?” is answered with a measurement instead of silence.

If you are unsure where to start, try Kimi K2.7 Code (fast, coding-oriented) or Nemotron 3 Super 120B (cheap).

When it doesn’t work

Symptom Cause and fix
Refuses to start, saying OPENROUTER_API_KEY is needed the key isn’t in the server’s environment — add it to .env and restart
Every request 404s baseUrl ends in /v1
404 No endpoints available … that model is excluded by your privacy settings
Empty replies, looks hung maxOutputTokens too low — keep it at 16000+
Talks but never uses tools the model’s own limitation — check the table or model-trials.ts
No MODEL select in the launch form no provider is registered (step 2) or its key is missing; “Use another model…” in the form names what’s missing
No model in the header ctx is not in your chips
Can’t start under the Docker sandbox not supported together. The container inherits no environment, so the session would run against Anthropic instead of the backend you picked — it is refused rather than downgraded

What protects the key

  • The key is never stored in a config file — only the name of the variable is
  • It reaches the session through a 0600 file, not a command-line argument, so ps doesn’t expose it to other users on the machine
  • An unresolvable key refuses the launch, so prompts never reach an unintended backend
  • ANTHROPIC_API_KEY is removed from a provider session’s environment — left in place it would outrank the auth token

Running a local LLM (claude-ollama)

To run Claude Code fully locally against an Ollama model — no cloud — use the bundled claude-ollama command (npx -p mulmoterminal claude-ollama qwen3:4b). See Local models with claude-ollama for the details.

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