Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add agents/kilo-org/kilocode/custom-modelsgit clone --depth 1 https://github.com/Kilo-Org/kilocodeWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00011 | $0.04289 |
| Opus 5 | $0.00005 | $0.02145 |
| Sonnet 5 | $0.00002 | $0.00858 |
| Haiku 4.5 | $0.00001 | $0.00429 |
Grade A, and why
custom-models scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 429 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Custom Models
Kilo Code ships with a curated list of models for each provider, but you can use any model your provider supports — including models that aren't in the built-in list. This is useful for:
- Using a newly released model before it's added to the built-in catalog
- Running a custom or fine-tuned model via LM Studio, Ollama, or another local provider
- Connecting to a self-hosted model through a custom API endpoint
- Configuring model-specific options like token limits, pricing, or reasoning settings
Defining a Custom Model
Add custom models under the provider.<provider_id>.models key in your config file. The model key becomes the model ID you reference elsewhere.
{% tabs %} {% tab label="VSCode" %}
-
Open Settings (gear icon) and go to the Providers tab.
-
Scroll to the bottom of the provider list and click Custom provider.

- Fill in the custom provider dialog:

- Provider ID — A unique identifier using lowercase letters, numbers, hyphens, or underscores (e.g.,
myprovider). This becomes theprovider_idin theprovider_id/model_idformat. - Display name — A human-readable name shown in the UI (e.g.,
My AI Provider). - Provider API — The protocol used by the provider. Use OpenAI Responses for OpenAI and xAI models. Use Anthropic Messages for Anthropic and MiniMax models. OpenAI Compatible is the default for other OpenAI Chat Completions-compatible endpoints.
- Base URL — The provider's API endpoint (e.g.,
https://api.myprovider.com/v1). When a valid URL is entered, Kilo automatically fetches available models from the endpoint if it exposes an OpenAI-compatible models endpoint. - API key — Your provider's API key. Optional — leave empty if you manage authentication via headers.
- Models — Add models manually by ID and display name, or select from the auto-fetched list that appears after entering a valid base URL.
- Headers (optional) — Add custom HTTP headers as key-value pairs if your provider requires them.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 429 lines · 11 tokens per session scan A 4dfef420566d
custom-models is an agent published in the GitHub repository Kilo-Org/kilocode (27,119 stars, last pushed today), licensed MIT. It adds 11 tokens to every session and 4,289 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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