---
type: reference
title: Pi Models Configuration
description: Complete reference for models.json — provider definitions, model specs, and API endpoints for the Frank Program.
tags:
  - pi
  - models
  - providers
  - llamacpp
  - unverified
timestamp: 2026-08-28
---

# Pi Models Configuration (`models.json`)

`models.json` defines the LLM providers pi connects to. Each provider specifies a base URL, API type, authentication, and available models.

**Location:** `/home/dank/.pi/agent/models.json`

---

## Providers

Current providers in `models.json` (verified 2026-08-27, after the
2026-08-18 service swap):

### llamacpp (dankserver)

| Property | Value |
|----------|-------|
| **Base URL** | `http://192.168.0.235:7770/v1` |
| **API** | `openai-completions` |
| **Auth** | None (EMPTY) |
| **Host** | [[dankserver|dankserver]] |

#### Models

| Model ID | Context Window | maxTokens | Reasoning | Input Types |
|----------|---------------|-----------|-----------|-------------|
| `frank-default-small` | 262,144 | 262,144 | Yes | Text, image |

The server is upstream llama.cpp (b10121) serving HauhauCS
Qwen3.6-35B-A3B-Uncensored-Aggressive Q6_K_P with 36 MoE experts on CPU,
ngram-mod spec, 4 slots of ~175K context. The server serves the loaded
model regardless of the requested model ID. Requests with any `model`
value succeed.

### llamacpp (dankclaw)

| Property | Value |
|----------|-------|
| **Base URL** | `http://192.168.0.143:7770/v1` |
| **API** | `openai-completions` |
| **Auth** | None (EMPTY) |
| **Host** | [[dankclaw|dankclaw]] |

> 2026-08-22: `frank-default-large` moved from `:52625` to `:7770` on
> Dankclaw (operator request: the primary inference server sits on the
> standard llama.cpp port). The OpenWebUI quadlet
> (`OPENAI_API_BASE_URL`) was re-pointed to `:7770` in the same change.

#### Models

| Model ID | Context Window | maxTokens | Reasoning | Input Types |
|----------|---------------|-----------|-----------|-------------|
| `frank-default-large` | 262,144 | 262,144 | Yes | Text, image |

The server is the ROCmFPX llama.cpp runtime serving
[kingjones777's Qwen3.8-Flash-Next Uncensored ROCmFP4 STRIX_LEAN GGUF](https://huggingface.co/kingjones777/Qwen3.8-Flash-Next-Uncensored-ROCmFP4-STRIX_LEAN-GGUF)
— a 177B-parameter, 56B-MoE model sharded into 3 Q4_0-ROCmFP4 GGUF files
(98.3 GB total) with a standalone BF16 vision embedding project (0.85 GB).
Speculative decoding uses `--spec-type ngram-mod` because the ROCmFPX quantization
drops the 4B MTP head. The model is loaded from
`/home/dank/models/kingjones-Qwen3.8-Flash-Next-Uncensored-ROCmFP4-STRIX_LEAN/`;
the original Q4_0-ROCmFP4-STRIX variant remains as a `.backup` directory.
Context is 262144 (native max), 1 slot. Concurrent requests queue on the
single slot; the server never preempts a running generation. It exposes
`reasoning_content` in deepseek reasoning format and supports
multimodal (vision) inference via the embedded mmproj.

2026-08-27: Upgraded from the original Qwen3.8-Flash-Next Q4_0-ROCmFP4-STRIX
GGUF to the Uncensored STRIX_LEAN variant with vision support and
ngram-mod speculative decoding.

### Thinking Levels

Pi's default thinking level is configured globally in `settings.json` as
`"defaultThinkingLevel": "medium"`. The model entries map Pi's `max` level to the llama.cpp-supported `xhigh`
wire value. Pi shows `max` in the thinking selector from the global settings,
but sends `reasoning_effort: "xhigh"` to both local llama.cpp endpoints.
`thinkingLevelMap` can translate a UI level without changing the global default.
Verified 2026-07-22:
`getSupportedThinkingLevels` returns `off,minimal,low,medium,high,xhigh`
and the live server accepts `reasoning_effort: "xhigh"` and returns
`reasoning_content` (verified 2026-08-21).

Mechanism (pi-ai `models.js` + `openai-completions.js`):

- `getSupportedThinkingLevels`: extended levels `xhigh`/`max` appear only
  when `thinkingLevelMap` defines them (string = supported, `null` =
  hidden, omitted = not supported).
- Default request path (no `compat.thinkingFormat`): sends
  `reasoning_effort = thinkingLevelMap[level] ?? level` when
  `supportsReasoningEffort` is true (default for this provider).

## Token Budgets (`maxTokens`)

Verified in the pi source, 2026-08-16 (`@earendil-works/pi-coding-agent` 0.84.1 + `pi-ai`):

- `maxTokens` is an optional model field in `models.json`. When omitted, pi defaults the model object to 16,384 (`provider-composer.js`).
- The value is metadata. It drives the model-picker "max out" display and length-error recovery (`isRecoverableLength`).
- Normal chat turns do not send `max_tokens`. The request builder sends the field only when a per-request option is set (`openai-completions.js buildParams`: `if (options?.maxTokens)`). The agent loop passes no such option.
- The only pi calls that send `max_tokens` are context compaction and branch summarization. They are deliberately budgeted.

## Model Selection Strategy

```mermaid
graph LR
    A[User Request] --> B{Complexity?}
    B -->|Large context / long docs| C[frank-default-large<br/>CIRU llama.cpp dankclaw :7770, 262K ctx]
    B -->|Fast / interactive| D[frank-default-small<br/>llama.cpp dankserver :7770, 262K ctx]

The CIRU endpoint (dankclaw) serves the 177B 56B-MoE model with
262144 context, ngram-mod speculative decoding, 1 slot. Concurrent
requests queue on the single slot. The upstream
llama.cpp endpoint (dankserver) serves the 35B A3B MoE model with 36
experts on CPU and 262K context per slot.
## Live Defaults

`settings.json` picks the main session provider and model (verified 2026-08-19):

| Scope | Provider | Model |
|-------|----------|-------|
| Main session | `llamacpp (dankclaw)` | `frank-default-large` |
| Subagent default | `frank-default-small` (llamacpp dankserver) | ~262K ctx per slot, ngram-mod spec |
| Subagent overrides | scout, researcher | `frank-default-small` |
| Subagent overrides | planner, worker, reviewer, oracle, context-builder | `frank-default-large` (llamacpp dankclaw) |

The subagent model IDs (`frank-default-small`, `frank-default-large`) resolve against the new provider set in `models.json`. The current mappings are `max -> xhigh` for both local models; the global and subagent defaults remain `max`.

---

## See Also

- [[settings|settings]] — Main configuration file
- [[dankserver|dankserver]] — Primary llama.cpp server
- [[dankclaw|dankclaw]] — Secondary llama.cpp server