Ch.13 Check 2026 Model and Tool Changes

Problem: Models, clients, and commands change frequently, making older instructions stale.
Practice: Check official changes as of this edition and run compatibility checks before migrating.

The first twelve chapters built a version-independent orchestration methodology. But methodology must land on real tooling. This edition checks changes since September 24: model selection, CLI settings, desktop collaboration, and usage controls. Each migration step identifies its account or client boundary.

A Way to Think About It: Avionics Retrofit of a Supersonic Airliner

Do not panic over frequent tool upgrades. View this transition through the eyes of a pilot:

text

[Pilot Mindset]   ──> Your flight manual remains identical: goal-driven execution (takeoff & landing targets)
                      and strict boundary constraints (flight corridors & safe altitudes).
[Engines]         ──> Propulsion overhauled to next-generation powerplants:
                      - Frontier Flagship Core: "GPT-6 Astra" (beyond-visual-range radar & autonomous computer operator);
                      - Daily Primary Thrust Engine: "GPT-6.1 Sol" (complex coding);
                      - Auxiliary Cruise Engine: "GPT-6 Luna" (focused, frequent work).
[Cockpit Screen]  ──> Worktree terminals, review navigation, and mobile approvals improve collaboration.
                      Check feature access in the installed client and workspace.
[Autopilot]       ──> The old --full-auto compatibility path is deprecated; new calls specify sandbox and approval modes.

With your mental model intact, upgraded avionics only help you fly faster and steadier.

Practice: Start with Three Steps

Complete your 2026 toolchain health check and migration in 3 simple steps:

Step 1: Scan for Deprecated Legacy Model Codenames
Run a grep scan in your project root:
bash
```
grep -rn "gpt-5.4" ~/.codex/config.toml .
```
Step 2: Check the Installed CLI and Update If Needed Check the installed version first; run the global npm update when needed:
bash
```
codex --version
npm install -g @openai/codex@latest
codex --version
```
Step 3: Migrate Deprecated --full-auto Calls In all your shell aliases and CI scripts, replace --full-auto with:
bash
```
codex exec --sandbox workspace-write "Review the current changes and report issues"
```

13.1 Desktop and Mobile: Changes That Affect Daily Work

Use the Codex entry in your current desktop client and check account and workspace access. The previous blanket claim that a July merger guaranteed every feature to every account has been removed; client packaging and model access need separate checks.

Worktrees and steering: app 26.928 (September 29) improves terminal startup in attached worktrees and keeps earlier answers visible during steering. Later releases improve multi-select chat moves, review navigation, and Windows/WSL recovery. Official changelog
Composer predictions: the October 9 beta suggests a next message in eligible local and SSH threads. Tab accepts an editable draft; sending it is a separate action. Personal Pro, age 18+, supported regions, Astra or GPT-6.1 Sol are required. Toggle it in Settings → General → Composer. Predictions
Mobile handoff: recent iOS releases improve approval presentation, plugin access from the plus menu, and queued-task recovery. Confirm the selected computer and task before approving an operation. Mobile changelog

bash

# Check the repository before attaching or handing off a thread.
git status --short
git worktree list
codex --version

Check supported sign-in methods and feature access for each client; an API key and a ChatGPT subscription have separate access and billing rules. Codex models

13.2 The GPT-6 Family: Choose by Task

As of October 21, 2026, GPT-6.1 Sol, launched September 29, is the recommended starting point for complex Codex work when available. Astra remains the choice for the hardest tasks, and Luna for focused work. GPT-6 Sol and GPT-5.6 Sol/Terra/Luna remain available during the rollout. GPT-6.1 Sol launches on Plus, Pro, Business, Enterprise and Edu; administrators must enable it for Enterprise/Edu. Free and Go are excluded at launch. Codex models

Model ID	Best fit	`reasoning.effort`	Boundary
`gpt-6-astra`	The hardest workflows across code, browsers, and desktop tools	`low`, `medium`, `high`, `xhigh`, `max`	No `none`; the client and tools still execute computer actions
`gpt-6.1-sol`	Repeated complex coding and long tasks across apps and documents	`low`, `medium`, `high`, `xhigh`, `max`	Current example default; no `none` or `minimal`
`gpt-6-sol`	Everyday complex coding, code review, and multi-step agent work	`none`, `low`, `medium`, `high`, `xhigh`, `max`	Previous Sol generation; retained for migration comparison
`gpt-6-luna`	Focused edits, extraction, summaries, and high-volume tasks	`none`, `low`, `medium`, `high`, `xhigh`, `max`	Move to Sol or Astra when the task needs more capability

These models accept text and image input and produce text. The API model catalog lists a 1,050,000-token context window and 128,000 maximum output tokens. Prefer the Responses API for tools; Astra requires Responses for tool calling. API model catalog · GPT-6 migration guidance

GPT-6.1 Sol migration: the API defaults to medium; use Responses for tool calling. Chat Completions supports this model without tool calling. Codex UI efforts can include Max/Ultra depending on settings: Ultra coordinates subagents and is not an API reasoning.effort value. API model · Codex effort controls

Keep API prices separate from Codex usage. These are standard API text-token prices per million tokens for requests with up to 272K input tokens, as checked for this edition. They are neither ChatGPT subscription prices nor Codex credit conversions. Longer prompts, caching, and other processing tiers have separate official prices.

API model	Input	Cached input	Output
`gpt-6-astra`	$10	$1	$50
`gpt-6.1-sol`	$2	$0.10	$10
`gpt-6-sol`	$2	$0.20	$10
`gpt-6-luna`	$0.10	$0.01	$0.50

GPT-6.1 Sol cache writes cost $2.50 per million tokens at Standard rates for inputs up to 272K. Longer prompts and speed tiers change these prices. Model pricing

Speed is a separate control. Since October 8, GPT-6.1 Sol Ultrafast is available on Pro $500 and eligible Enterprise/Edu plans, with Enterprise access off until enabled. Included subscription usage consumes 8× Standard limits; purchased credits and Enterprise pay-as-you-go consume 6× Standard. API-key billing uses API prices instead. Sol Ultrafast supports US and EEA + Switzerland inference residency. Start with Standard and compare a familiar task before enabling it. Speed and billing

Choose a model:

bash

codex --version
codex --model gpt-6.1-sol
codex exec -m gpt-6-luna "Review the current changes"

Use /model in an interactive session. If a new model is missing from the picker, check client and account availability. API availability does not imply Codex sign-in availability. Codex models

Local default configuration:

toml

# ~/.codex/config.toml
model = "gpt-6.1-sol"

This only selects the local default model. The --approve-for-me permission mode is not documented as using Luna.

Verified lifecycle dates

Date	Scope	Official record
March 26, 2026	API	`gpt-4-0314`, `gpt-4-1106-preview`, and `gpt-4-0125-preview` shut down
May 12, 2026	API	`dall-e-2` and `dall-e-3` shut down
August 26, 2026	API	Assistants API shut down; migrate to Responses API and Conversations API
August 31, 2026	Codex with ChatGPT sign-in	`gpt-5.4` and `gpt-5.4-mini` retired
September 3, 2026	API	GPT-6 Astra released
September 22, 2026	API / Codex	GPT-6 Sol and Luna released and began rolling out in Codex
September 29, 2026	API / Codex / Work	GPT-6.1 Sol launch
October 14, 2026	Codex with ChatGPT sign-in	GPT-5.5 retired; API and API-key sessions unaffected

Check API deprecations for API shutdown dates and official replacements. Check Codex models and the changelog for Codex sign-in scope. A retirement in one interface does not mean the API model is gone.

13.3 Codex CLI: 0.163.0 at This Edition's Cutoff

The official changelog lists CLI 0.163.0, released October 15, at this edition's October 21, 2026 cutoff. This is a dated verification, not a permanent latest-version claim. Your installed version can differ. Changelog

The 0.159.1 catalog added GPT-6.1 Sol. In 0.163.0, /config searches settings and shows restart requirements, /keymap configures a leader key, and /daemon manages background-server restarts. Steering responds immediately, and resumed threads restore saved permissions subject to current policy. Review potential interruption before restarting a server.

bash

codex --version
npm install -g @openai/codex@latest
codex --version

1. Migrate older `--full-auto` calls

codex exec --full-auto is a deprecated compatibility path that prints a warning. It has not been removed. For new non-interactive commands, specify the sandbox:

bash

codex exec --sandbox workspace-write "Review the current changes and report issues"

The sandbox constrains workspace access. --approve-for-me routes eligible escalation requests to automatic review; it does not define the sandbox. Approval and security docs

2. Use the supported Hooks event structure

Hooks in config.toml use event arrays and handler arrays. [hooks] stop = "..." is not a valid replacement. This example checks whitespace errors in the current repository at the end of a turn. Review and trust the hook source through /hooks when first enabled. Hooks docs

toml

# ~/.codex/config.toml
[[hooks.Stop]]

[[hooks.Stop.hooks]]
type = "command"
command = "git diff --check"

3. Install plugins by IDs shown in the current catalog

bash

codex plugin list
codex plugin add --help

codex plugin add accepts the PLUGIN@MARKETPLACE form shown by the catalog. codex plugin install is not a current CLI subcommand. Check the ID and source before installing. Codex changelog

4. Automatic approval does not have a documented fixed model

--approve-for-me sends eligible approval requests to automatic review. It does not expand sandbox permissions or guarantee approval of every risky action. The documentation does not say the reviewer always runs GPT-6 Luna. Permissions docs

bash

codex --approve-for-me "Review the current changes and suggest fixes"

13.4 The Skills Economy: Compounding Repeated Workflows into Assets

If AGENTS.md is a project's "constitutional law," Skills are the standard operating procedures for specific task types:

text

skills/
└── pr-review/
    └── SKILL.md      # A procedural manual with YAML frontmatter

13.5 Codex Security: Use Verified Capabilities

Codex Security is a separate security review capability. Check the Codex Security entry and instructions in your client's plugin directory before selecting a scan workflow. Commands can differ by version. This book does not present unverified Daybreak model routing, cybersecurity ratings, or scanner flags as executable facts. Codex Security docs

bash

codex plugin list

13.6 A 3D Workflow Example: GPT-6 Astra, Tripo3D, and Blender

This is a workflow developers can assemble themselves: use Astra to structure asset requirements, a 3D service such as Tripo3D to generate a GLB, and a Blender bpy script to inspect a render. These are separate tools. This example does not imply an official OpenAI integration with a third party or guarantee quality or completion time. The official GPT-6 sources consulted for this edition do not provide the BenchCAD figure published in the previous edition. Official GPT-6 guide

1. Workflow boundaries

The model structures requirements and helps write scripts; the 3D service generates a mesh; Blender imports and renders it. A developer reviews geometry, materials, and performance before shipping.

text

Concept and scale → GPT-6 Astra structures prompt → Tripo3D generates GLB
                                             ↓
                           Blender bpy render and review → Three.js display

2. Four-step walkthrough

Step 1: Structure 3D Prompts via GPT-6 Astra

Instruct Astra in your terminal or desktop prompt:

text

Act as a Lead 3D Technical Artist. I want to build a "Cyberpunk Holographic Vending Machine" for a Web 3D product showcase.
Generate an engine-optimized, structured 3D prompt for Tripo3D.

Requirements:
1. Emphasize silhouette and geometric symmetry;
2. Enforce mesh topology tags (Clean quad topology, game-ready, low-poly);
3. Define PBR material specifications (Matte painted metal, glowing neon emissive panels).

For example, the model can draft the following prompt for a 3D service; inspect the actual generated result:

text

Cyberpunk holographic vending machine, freestanding rectangular kiosk with chamfered edges.
Center features transparent acrylic dispenser bay with internal glowing LED strip.
Materials: Brushed matte dark gray titanium alloy (roughness: 0.35, metallic: 0.85),
glowing cyan neon emissive trim lines (emission strength: 5.0), scratched hazard decals on base.
Topology tags: clean quad-dominant topology, watertight mesh, manifold geometry, PBR 4K textures, game-ready asset.

Step 2: Generate & Export Standardized GLB via Tripo3D

Enter the prompt in a service such as Tripo3D, inspect the generated mesh and materials, then export vending_machine.glb into public/models/. Speed and topology quality depend on the service and input.

Step 3: Automate Blender via GPT-6 Astra (`pipeline.py`)

Instead of wrestling with manual GUI dials, have Astra write and execute a headless Blender Python automation script:

python

import bpy
import math
from pathlib import Path

# 1. Clean factory environment
bpy.ops.wm.read_factory_settings(use_empty=True)

# 2. Import Tripo3D GLB asset
asset_path = Path("public/models/vending_machine.glb").resolve()
if not asset_path.is_file():
    raise FileNotFoundError(asset_path)
bpy.ops.import_scene.gltf(filepath=str(asset_path))

# 3. Compute bounding box, center origin, and ground asset (Z=0)
imported_objs = [obj for obj in bpy.context.selected_objects if obj.type == 'MESH']
if imported_objs:
    bpy.ops.object.select_all(action='DESELECT')
    for obj in imported_objs:
        obj.select_set(True)
    bpy.context.view_layer.objects.active = imported_objs[0]
    bpy.ops.object.origin_set(type='ORIGIN_GEOMETRY', center='BOUNDS')
    
    min_z = min([v[2] for obj in imported_objs for v in [obj.matrix_world @ v.co for v in obj.data.vertices]])
    for obj in imported_objs:
        obj.location.z -= min_z

# 4. Automated Studio Three-Point Lighting
# Key Light
key_light_data = bpy.data.lights.new(name="Key_Light", type='AREA')
key_light_data.energy = 500
key_light_data.size = 2.0
key_light = bpy.data.objects.new(name="Key_Light", object_data=key_light_data)
key_light.location = (3.0, -3.0, 4.0)
bpy.context.collection.objects.link(key_light)

# Fill Light
fill_light_data = bpy.data.lights.new(name="Fill_Light", type='AREA')
fill_light_data.energy = 200
fill_light_data.size = 3.0
fill_light = bpy.data.objects.new(name="Fill_Light", object_data=fill_light_data)
fill_light.location = (-3.0, -2.0, 2.0)
bpy.context.collection.objects.link(fill_light)

# Rim Light
rim_light_data = bpy.data.lights.new(name="Rim_Light", type='SUN')
rim_light_data.energy = 3.0
rim_light = bpy.data.objects.new(name="Rim_Light", object_data=rim_light_data)
rim_light.location = (0.0, 4.0, 3.0)
rim_light.rotation_euler = (math.radians(-45), 0, math.radians(180))
bpy.context.collection.objects.link(rim_light)

# 5. Product Showcase Camera
cam_data = bpy.data.cameras.new("Product_Camera")
cam_obj = bpy.data.objects.new("Product_Camera", cam_data)
cam_obj.location = (0, -4.5, 2.0)
cam_obj.rotation_euler = (math.radians(72), 0, 0)
bpy.context.collection.objects.link(cam_obj)
bpy.context.scene.camera = cam_obj

# 6. Eevee Next Headless Inspection Render
bpy.context.scene.render.engine = 'BLENDER_EEVEE_NEXT'
bpy.context.scene.render.resolution_x = 1280
bpy.context.scene.render.resolution_y = 720
render_path = Path("public/renders/validation_preview.png").resolve()
render_path.parent.mkdir(parents=True, exist_ok=True)
bpy.context.scene.render.filepath = str(render_path)

bpy.ops.render.render(write_still=True)
print("✅ Headless Blender validation frame generated: ./public/renders/validation_preview.png")

Execute in background mode:

bash

blender --background --python pipeline.py

After rendering, provide validation_preview.png to a Codex session with image input and ask it to inspect visible geometry and lighting issues. Verify normals, UVs, and performance manually in Blender.

Step 4: Instant Web Embed (React Three Fiber / Three.js)

Distribute the optimized GLB asset directly inside your Next.js 15 or Vite web application:

tsx

// components/VendingMachineViewer.tsx
import { Canvas } from '@react-three/fiber';
import { useGLTF, OrbitControls, Environment } from '@react-three/drei';

export function VendingMachineViewer() {
  const { scene } = useGLTF('/models/vending_machine.glb');
  return (
    <div className="w-full h-[500px] bg-slate-900 rounded-xl overflow-hidden shadow-2xl">
      <Canvas camera={{ position: [0, 2, 4], fov: 45 }}>
        <ambientLight intensity={0.7} />
        <directionalLight position={[5, 10, 5]} intensity={1.2} />
        <primitive object={scene} position={[0, -1, 0]} />
        <Environment preset="city" />
        <OrbitControls autoRotate autoRotateSpeed={2.0} enableZoom={true} />
      </Canvas>
    </div>
  );
}

13.7 Cost and Task-Based Routing

Start everyday complex coding with gpt-6.1-sol, use gpt-6-luna for focused extraction and small edits, and evaluate gpt-6-astra for the hardest cross-app work. Check what your account and client can select, then compare quality, latency, and cost on your own tasks. Codex models

If a project uses other providers, verify session formats and tool support independently. The companion Codex Switch is a third-party tool; rely on its current documentation and your own compatibility tests.

13.8 Migration Checklist

bash

codex --version
npm install -g @openai/codex@latest
codex --version
codex --model gpt-6.1-sol
codex exec --sandbox workspace-write "Review the current changes and report issues"
codex plugin list

Check GPT-6 access for your account and workspace in Codex models.
Search saved gpt-5.4, gpt-5.4-mini, and --full-auto settings; migrate each according to its actual scope.
If using Hooks, verify the event-array structure in the Hooks docs and inspect trust with /hooks.

Troubleshooting

Symptom	Check
GPT-6.1 Sol or Luna is absent from the picker	Check CLI version, plan, rollout, and workspace administrator settings
`--full-auto` prints a deprecation warning	Use `--sandbox workspace-write` for new non-interactive calls; the old path remains compatible
A configured model is unavailable	Distinguish Codex sign-in from API access and select an available model with `/model`
Hooks do not run	Check the event-array structure and review hook trust with `/hooks`

13.9 Principles That Outlast Versions

Keep changing model IDs and CLI options in one place. Check official documentation and local behavior during each upgrade. Continue to state the task goal, permission boundary, and acceptance criteria clearly.

🏠 Index | ⬅️ Prev (Ch.12) | 🌐 中文版

For concise updates and setup reminders, visit the PMER Codex tool channel. It uses the same October 21, 2026 baseline; use this chapter for configuration details.

Ch.13 Check 2026 Model and Tool Changes ​

A Way to Think About It: Avionics Retrofit of a Supersonic Airliner ​

Practice: Start with Three Steps ​

13.1 Desktop and Mobile: Changes That Affect Daily Work ​

13.2 The GPT-6 Family: Choose by Task ​

Verified lifecycle dates ​

13.3 Codex CLI: 0.163.0 at This Edition's Cutoff ​

1. Migrate older --full-auto calls ​

2. Use the supported Hooks event structure ​

3. Install plugins by IDs shown in the current catalog ​

4. Automatic approval does not have a documented fixed model ​

13.4 The Skills Economy: Compounding Repeated Workflows into Assets ​

13.5 Codex Security: Use Verified Capabilities ​

13.6 A 3D Workflow Example: GPT-6 Astra, Tripo3D, and Blender ​

1. Workflow boundaries ​

2. Four-step walkthrough ​

Step 1: Structure 3D Prompts via GPT-6 Astra ​

Step 2: Generate & Export Standardized GLB via Tripo3D ​

Step 3: Automate Blender via GPT-6 Astra (pipeline.py) ​

Step 4: Instant Web Embed (React Three Fiber / Three.js) ​

13.7 Cost and Task-Based Routing ​

13.8 Migration Checklist ​

Troubleshooting ​

13.9 Principles That Outlast Versions ​

Related tool channel ​

Ch.13 Check 2026 Model and Tool Changes

A Way to Think About It: Avionics Retrofit of a Supersonic Airliner

Practice: Start with Three Steps

13.1 Desktop and Mobile: Changes That Affect Daily Work

13.2 The GPT-6 Family: Choose by Task

Verified lifecycle dates

13.3 Codex CLI: 0.163.0 at This Edition's Cutoff

1. Migrate older `--full-auto` calls

2. Use the supported Hooks event structure

3. Install plugins by IDs shown in the current catalog

4. Automatic approval does not have a documented fixed model

13.4 The Skills Economy: Compounding Repeated Workflows into Assets

13.5 Codex Security: Use Verified Capabilities

13.6 A 3D Workflow Example: GPT-6 Astra, Tripo3D, and Blender

1. Workflow boundaries

2. Four-step walkthrough

Step 1: Structure 3D Prompts via GPT-6 Astra

Step 2: Generate & Export Standardized GLB via Tripo3D

Step 3: Automate Blender via GPT-6 Astra (`pipeline.py`)

Step 4: Instant Web Embed (React Three Fiber / Three.js)

13.7 Cost and Task-Based Routing

13.8 Migration Checklist

Troubleshooting

13.9 Principles That Outlast Versions

Related tool channel