fix(catalog): complete GPT-5.6 off and pricing support

(cherry picked from commit fc034d61ff69e8ad1870f674c72ff3f761741862)

packages/ai/CHANGELOG.md

@@ -51,7 +51,7 @@
 - Fixed the AWS credential resolver ignoring `role_arn` profiles: shared-config role chaining (`source_profile` recursion, `web_identity_token_file`, `credential_source`) now resolves via STS `AssumeRole`/`AssumeRoleWithWebIdentity`, honoring `role_session_name`/`duration_seconds`/`external_id`, so Bedrock is detected on EKS/IRSA and multi-account setups instead of reporting "No models available" ([#8209](https://github.com/can1357/oh-my-pi/issues/8209)).
 - Fixed Bedrock availability being under-detected on Nitro/EKS hosts: the EC2 metadata probe now recognizes Nitro DMI markers (`board_asset_tag` instance ids, `Amazon EC2` vendor fields) in addition to the Xen `ec2` UUID prefix ([#8209](https://github.com/can1357/oh-my-pi/issues/8209)).
 - Fixed DeepSeek Responses targets (opencode-go) rejecting a thinking-mode continuation with `400 The reasoning_text in the thinking mode must be passed back to the API` after a prewalk hand-off plus mid-run compaction: the Responses input builder re-encoded replayed assistant turns without a reasoning item, so the request enabled reasoning but shipped no `reasoning_text`. The encoder now synthesizes a `reasoning_text` reasoning item for every replayed assistant turn when the target requires reasoning replay in thinking mode (`requiresReasoningContentForAllAssistantTurns` / `requiresReasoningContentForToolCalls`), mirroring the chat-completions `reasoning_content` safety net ([#8248](https://github.com/can1357/oh-my-pi/issues/8248)).
-- Fixed OpenAI Daybreak `off` thinking requests serializing as `low`; models with explicit wire-level off support now send `reasoning.effort: "none"`.
+- Fixed OpenAI GPT-5.6 and Daybreak `off` thinking requests serializing as `low`; every first-party alias with explicit wire-level off support now sends `reasoning.effort: "none"`.
 
 ## [17.2.12] - 2026-08-08
 

packages/ai/test/models-cost.test.ts

@@ -196,4 +196,42 @@ describe("calculateCost", () => {
 
 		expect(usage.cost.total).toBeCloseTo(0.01005, 8);
 	});
+
+	it("keeps Daybreak Blue at short-context rates through 272K prompt tokens", () => {
+		const model = getBundledModel("openai", "daybreak-blue-latest");
+		const usage: Usage = {
+			input: 270_000,
+			output: 1_000,
+			cacheRead: 1_000,
+			cacheWrite: 1_000,
+			totalTokens: 273_000,
+			cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0, total: 0 },
+		};
+
+		calculateCost(model, usage);
+
+		expect(usage.cost.input).toBeCloseTo(1.35, 12);
+		expect(usage.cost.output).toBeCloseTo(0.03, 12);
+		expect(usage.cost.cacheRead).toBeCloseTo(0.0005, 12);
+		expect(usage.cost.cacheWrite).toBeCloseTo(0.00625, 12);
+	});
+
+	it("prices the full Daybreak Blue request at long-context rates above 272K prompt tokens", () => {
+		const model = getBundledModel("openai", "daybreak-blue-latest");
+		const usage: Usage = {
+			input: 270_001,
+			output: 1_000,
+			cacheRead: 1_000,
+			cacheWrite: 1_000,
+			totalTokens: 273_001,
+			cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0, total: 0 },
+		};
+
+		calculateCost(model, usage);
+
+		expect(usage.cost.input).toBeCloseTo(2.70001, 12);
+		expect(usage.cost.output).toBeCloseTo(0.045, 12);
+		expect(usage.cost.cacheRead).toBeCloseTo(0.001, 12);
+		expect(usage.cost.cacheWrite).toBeCloseTo(0.0125, 12);
+	});
 });

packages/ai/test/openai-daybreak-effort.test.ts

@@ -4,24 +4,36 @@ import type { Context } from "@oh-my-pi/pi-ai/types";
 import { Effort } from "@oh-my-pi/pi-catalog/effort";
 import { getBundledModel } from "@oh-my-pi/pi-catalog/models";
 
-const DAYBREAK_MODEL_IDS = ["daybreak-blue-latest", "daybreak-red-latest", "gpt-5.6-cyber", "gpt-5.6-sol"];
-const DAYBREAK_EFFORTS = [Effort.Low, Effort.Medium, Effort.High, Effort.XHigh, Effort.Max];
+const GPT_56_MODEL_IDS = [
+	"daybreak-blue-latest",
+	"daybreak-red-latest",
+	"gpt-5.6",
+	"gpt-5.6-cyber",
+	"gpt-5.6-luna",
+	"gpt-5.6-luna-pro",
+	"gpt-5.6-sol",
+	"gpt-5.6-sol-pro",
+	"gpt-5.6-terra",
+	"gpt-5.6-terra-pro",
+];
+const GPT_56_EFFORTS = [Effort.Low, Effort.Medium, Effort.High, Effort.XHigh, Effort.Max];
 const CONTEXT: Context = {
 	messages: [{ role: "user", content: "hello", timestamp: 0 }],
 };
 
-describe("OpenAI Daybreak Responses reasoning payload", () => {
-	for (const id of DAYBREAK_MODEL_IDS) {
+describe("OpenAI GPT-5.6 Responses reasoning payload", () => {
+	for (const id of GPT_56_MODEL_IDS) {
 		test(`${id} serializes off and every supported thinking level`, () => {
 			const model = getBundledModel<"openai-responses">("openai", id);
 			if (!model) throw new Error(`openai/${id} must be in bundled models.json`);
 
+			const mode = model.reasoningMode ? { mode: model.reasoningMode } : {};
 			const disabled = buildParams(model, CONTEXT, { disableReasoning: true }, undefined);
-			expect(disabled.params.reasoning).toEqual({ effort: "none" });
+			expect(disabled.params.reasoning).toEqual({ effort: "none", ...mode });
 
-			for (const effort of DAYBREAK_EFFORTS) {
+			for (const effort of GPT_56_EFFORTS) {
 				const enabled = buildParams(model, CONTEXT, { reasoning: effort }, undefined);
-				expect(enabled.params.reasoning).toEqual({ effort, summary: "auto" });
+				expect(enabled.params.reasoning).toEqual({ effort, summary: "auto", ...mode });
 			}
 		});
 	}

packages/catalog/CHANGELOG.md

@@ -13,6 +13,7 @@
 ### Fixed
 
 - Fixed Codex-discovered `gpt-daybreak-*` aliases being treated as unknown models, restoring the GPT-5.6 `low`/`medium`/`high`/`xhigh`/`max` effort ladder and its 372K fallback only when the Codex registry omits `context_window`.
+- Fixed first-party OpenAI GPT-5.6 aliases to preserve wire-level `off` through generated pro aliases and to price requests above 272K input at each SKU's documented long-context rates.
 
 ## [17.2.15] - 2026-08-12
 

packages/catalog/scripts/generated-policies.ts

@@ -21,9 +21,10 @@ import { resolveModelThinking } from "../src/model-thinking";
 import { isOllamaCloudOutputCapped, OLLAMA_CLOUD_MAX_OUTPUT_TOKENS } from "../src/provider-models/ollama";
 import {
 	ALIBABA_TOKEN_PLAN_STATIC_MODELS,
+	OPENAI_GPT_56_LONG_CONTEXT_COSTS,
 	resolveWaferServerlessThinkingFormat,
 } from "../src/provider-models/openai-compat";
-import type { Api, Model, ModelSpec } from "../src/types";
+import type { Api, LongContextTokenCost, Model, ModelSpec } from "../src/types";
 import { isVariantCollapsedSpec } from "../src/variant-collapse";
 import { buildCanonicalModelIndex, buildCanonicalReferenceData } from "./equivalence";
 
@@ -149,13 +150,33 @@ const CODEX_GPT_5_6_372K_MODEL_IDS: Record<string, true> = {
 	"gpt-5.6-terra": true,
 };
 
-const OPENAI_DAYBREAK_REASONING_MODEL_IDS: Record<string, true> = {
+const OPENAI_GPT_5_6_LONG_CONTEXT_COST_BY_MODEL_ID: Readonly<Record<string, LongContextTokenCost>> = {
+	"daybreak-blue-latest": OPENAI_GPT_56_LONG_CONTEXT_COSTS.sol,
+	"gpt-5.6": OPENAI_GPT_56_LONG_CONTEXT_COSTS.sol,
+	"gpt-5.6-luna": OPENAI_GPT_56_LONG_CONTEXT_COSTS.luna,
+	"gpt-5.6-sol": OPENAI_GPT_56_LONG_CONTEXT_COSTS.sol,
+	"gpt-5.6-terra": OPENAI_GPT_56_LONG_CONTEXT_COSTS.terra,
+};
+
+const OPENAI_NONE_EFFORT_MODEL_IDS: Record<string, true> = {
 	"daybreak-blue-latest": true,
 	"daybreak-red-latest": true,
+	"gpt-5.6": true,
 	"gpt-5.6-cyber": true,
+	"gpt-5.6-luna": true,
 	"gpt-5.6-sol": true,
+	"gpt-5.6-terra": true,
 };
 
+function modelOrRequestIdValue<T>(
+	model: Pick<ModelSpec<Api>, "id" | "requestModelId">,
+	values: Readonly<Record<string, T>>,
+): T | undefined {
+	const direct = values[bareModelId(model.id)];
+	if (direct !== undefined) return direct;
+	return model.requestModelId === undefined ? undefined : values[bareModelId(model.requestModelId)];
+}
+
 const COPILOT_GENERATED_LIMITS: Record<string, { contextWindow: number; maxTokens: number }> = {
 	"claude-opus-4.6": { contextWindow: 168000, maxTokens: 32000 },
 	"gpt-5.2": { contextWindow: 272000, maxTokens: 128000 },
@@ -477,13 +498,16 @@ function inferGeneratedApplyPatchToolType(
 }
 
 function applyOpenAICatalogPolicy(model: ModelSpec<Api>, parsedModel: OpenAIModel): void {
-	if (
-		model.provider === "openai" &&
-		model.api === "openai-responses" &&
-		OPENAI_DAYBREAK_REASONING_MODEL_IDS[model.id]
-	) {
+	const isFirstPartyResponses = model.provider === "openai" && model.api === "openai-responses";
+	if (isFirstPartyResponses && modelOrRequestIdValue(model, OPENAI_NONE_EFFORT_MODEL_IDS)) {
 		model.compat = { ...(model.compat ?? {}), reasoningDisableMode: "none-effort" };
 	}
+	const longContextCost = isFirstPartyResponses
+		? modelOrRequestIdValue(model, OPENAI_GPT_5_6_LONG_CONTEXT_COST_BY_MODEL_ID)
+		: undefined;
+	if (longContextCost) {
+		model.cost = { ...model.cost, longContext: longContextCost };
+	}
 
 	// Codex models: 400K figure includes output budget; input window is 272K.
 	if (parsedModel.variant.startsWith("codex") && parsedModel.variant !== "codex-spark") {

packages/catalog/src/model-manager.ts

@@ -1,7 +1,7 @@
 import { buildModel } from "./build";
 import { readModelCache, writeModelCache } from "./model-cache";
 import { type GeneratedProvider, getBundledModels } from "./models";
-import type { Api, Model, ModelSpec, Provider } from "./types";
+import type { Api, Model, ModelCost, ModelSpec, Provider, TokenCost } from "./types";
 import { isRecord } from "./utils";
 import { collapseBuiltModelVariants } from "./variant-collapse";
 
@@ -510,6 +510,7 @@ function mergeDynamicModel<TApi extends Api>(existingModel: Model<TApi>, dynamic
 	const reasoning = dynamicReasoningAuthoritative
 		? dynamicModel.reasoning
 		: existingModel.reasoning || dynamicModel.reasoning;
+	const longContextCost = dynamicModel.cost.longContext ?? existingModel.cost.longContext;
 	// Re-build from spec stage: sparse compat comes from `compatConfig` (the
 	// verbatim override vocabulary), never the resolved `compat` record.
 	return buildModel({
@@ -523,6 +524,7 @@ function mergeDynamicModel<TApi extends Api>(existingModel: Model<TApi>, dynamic
 			output: preferDiscoveryCost(dynamicModel.cost.output, existingModel.cost.output),
 			cacheRead: preferDiscoveryCost(dynamicModel.cost.cacheRead, existingModel.cost.cacheRead),
 			cacheWrite: preferDiscoveryCost(dynamicModel.cost.cacheWrite, existingModel.cost.cacheWrite),
+			...(longContextCost ? { longContext: longContextCost } : {}),
 		},
 		contextWindow: preferDiscoveryLimit(dynamicModel.contextWindow, existingModel.contextWindow),
 		maxTokens: preferDiscoveryLimit(dynamicModel.maxTokens, existingModel.maxTokens),
@@ -640,7 +642,7 @@ function isModelInputArray(value: unknown): value is ("text" | "image")[] {
 	return true;
 }
 
-function isModelCost(value: unknown): value is Model<Api>["cost"] {
+function isTokenCost(value: unknown): value is TokenCost {
 	if (!isRecord(value)) {
 		return false;
 	}
@@ -670,3 +672,12 @@ function isModelCost(value: unknown): value is Model<Api>["cost"] {
 	}
 	return true;
 }
+
+function isModelCost(value: unknown): value is ModelCost {
+	if (!isTokenCost(value)) return false;
+	const longContext = (value as TokenCost & { longContext?: unknown }).longContext;
+	if (longContext === undefined) return true;
+	if (!isTokenCost(longContext) || !isRecord(longContext)) return false;
+	const threshold = longContext.inputThreshold;
+	return typeof threshold === "number" && threshold > 0 && threshold < Infinity;
+}

packages/catalog/src/models.json

@@ -72354,7 +72354,14 @@
 				"input": 5,
 				"output": 30,
 				"cacheRead": 0.5,
-				"cacheWrite": 6.25
+				"cacheWrite": 6.25,
+				"longContext": {
+					"inputThreshold": 272000,
+					"input": 10,
+					"output": 45,
+					"cacheRead": 1,
+					"cacheWrite": 12.5
+				}
 			},
 			"contextWindow": 1050000,
 			"maxTokens": 128000,
@@ -72368,6 +72375,9 @@
 					"xhigh",
 					"max"
 				]
+			},
+			"compat": {
+				"reasoningDisableMode": "none-effort"
 			}
 		},
 		"gpt-5.6-luna": {
@@ -72385,7 +72395,14 @@
 				"input": 0.2,
 				"output": 1.2,
 				"cacheRead": 0.02,
-				"cacheWrite": 0.25
+				"cacheWrite": 0.25,
+				"longContext": {
+					"inputThreshold": 272000,
+					"input": 0.4,
+					"output": 1.8,
+					"cacheRead": 0.04,
+					"cacheWrite": 0.5
+				}
 			},
 			"contextWindow": 1050000,
 			"maxTokens": 128000,
@@ -72399,6 +72416,9 @@
 					"xhigh",
 					"max"
 				]
+			},
+			"compat": {
+				"reasoningDisableMode": "none-effort"
 			}
 		},
 		"gpt-5.6-luna-pro": {
@@ -72416,7 +72436,14 @@
 				"input": 0.2,
 				"output": 1.2,
 				"cacheRead": 0.02,
-				"cacheWrite": 0.25
+				"cacheWrite": 0.25,
+				"longContext": {
+					"inputThreshold": 272000,
+					"input": 0.4,
+					"output": 1.8,
+					"cacheRead": 0.04,
+					"cacheWrite": 0.5
+				}
 			},
 			"contextWindow": 1050000,
 			"maxTokens": 128000,
@@ -72432,6 +72459,9 @@
 					"xhigh",
 					"max"
 				]
+			},
+			"compat": {
+				"reasoningDisableMode": "none-effort"
 			}
 		},
 		"gpt-5.6-sol": {
@@ -72449,7 +72479,14 @@
 				"input": 5,
 				"output": 30,
 				"cacheRead": 0.5,
-				"cacheWrite": 6.25
+				"cacheWrite": 6.25,
+				"longContext": {
+					"inputThreshold": 272000,
+					"input": 10,
+					"output": 45,
+					"cacheRead": 1,
+					"cacheWrite": 12.5
+				}
 			},
 			"contextWindow": 1050000,
 			"maxTokens": 128000,
@@ -72483,7 +72520,14 @@
 				"input": 5,
 				"output": 30,
 				"cacheRead": 0.5,
-				"cacheWrite": 6.25
+				"cacheWrite": 6.25,
+				"longContext": {
+					"inputThreshold": 272000,
+					"input": 10,
+					"output": 45,
+					"cacheRead": 1,
+					"cacheWrite": 12.5
+				}
 			},
 			"contextWindow": 1050000,
 			"maxTokens": 128000,
@@ -72499,6 +72543,9 @@
 					"xhigh",
 					"max"
 				]
+			},
+			"compat": {
+				"reasoningDisableMode": "none-effort"
 			}
 		},
 		"gpt-5.6-terra": {
@@ -72516,7 +72563,14 @@
 				"input": 2,
 				"output": 12,
 				"cacheRead": 0.2,
-				"cacheWrite": 2.5
+				"cacheWrite": 2.5,
+				"longContext": {
+					"inputThreshold": 272000,
+					"input": 4,
+					"output": 18,
+					"cacheRead": 0.4,
+					"cacheWrite": 5
+				}
 			},
 			"contextWindow": 1050000,
 			"maxTokens": 128000,
@@ -72530,6 +72584,9 @@
 					"xhigh",
 					"max"
 				]
+			},
+			"compat": {
+				"reasoningDisableMode": "none-effort"
 			}
 		},
 		"gpt-5.6-terra-pro": {
@@ -72547,7 +72604,14 @@
 				"input": 2,
 				"output": 12,
 				"cacheRead": 0.2,
-				"cacheWrite": 2.5
+				"cacheWrite": 2.5,
+				"longContext": {
+					"inputThreshold": 272000,
+					"input": 4,
+					"output": 18,
+					"cacheRead": 0.4,
+					"cacheWrite": 5
+				}
 			},
 			"contextWindow": 1050000,
 			"maxTokens": 128000,
@@ -72563,6 +72627,9 @@
 					"xhigh",
 					"max"
 				]
+			},
+			"compat": {
+				"reasoningDisableMode": "none-effort"
 			}
 		},
 		"gpt-realtime-2.1": {
@@ -72857,7 +72924,14 @@
 				"input": 5,
 				"output": 30,
 				"cacheRead": 0.5,
-				"cacheWrite": 6.25
+				"cacheWrite": 6.25,
+				"longContext": {
+					"inputThreshold": 272000,
+					"input": 10,
+					"output": 45,
+					"cacheRead": 1,
+					"cacheWrite": 12.5
+				}
 			},
 			"contextWindow": 1050000,
 			"maxTokens": 128000,

packages/catalog/src/models.ts

@@ -1,6 +1,6 @@
 import { buildModel } from "./build";
 import MODELS from "./models.json" with { type: "json" };
-import type { Api, KnownProvider, Model, ModelSpec, Usage } from "./types";
+import type { Api, KnownProvider, Model, ModelSpec, TokenCost, Usage } from "./types";
 
 /**
  * Static bundled model registry loaded from `models.json`.
@@ -42,13 +42,22 @@ export function getBundledModels(provider: GeneratedProvider): Model<Api>[] {
 	const models = getProviderModels(provider);
 	return models ? (Array.from(models.values()) as Model<Api>[]) : [];
 }
+function resolveTokenCost(cost: Model["cost"], usage: Usage): TokenCost {
+	const longContext = cost.longContext;
+	if (!longContext) return cost;
+	const orchestration = usage.orchestration;
+	const promptInputTokens =
+		usage.input + usage.cacheRead + usage.cacheWrite + (orchestration?.input ?? 0) + (orchestration?.cacheRead ?? 0);
+	return promptInputTokens > longContext.inputThreshold ? longContext : cost;
+}
 
 export function calculateCost<TApi extends Api>(model: Model<TApi>, usage: Usage): Usage["cost"] {
+	const rates = resolveTokenCost(model.cost, usage);
 	const orchestration = usage.orchestration;
-	usage.cost.input = (model.cost.input / 1000000) * (usage.input + (orchestration?.input ?? 0));
-	usage.cost.output = (model.cost.output / 1000000) * (usage.output + (orchestration?.output ?? 0));
-	usage.cost.cacheRead = (model.cost.cacheRead / 1000000) * (usage.cacheRead + (orchestration?.cacheRead ?? 0));
-	usage.cost.cacheWrite = cacheWriteCost(model, usage);
+	usage.cost.input = (rates.input / 1000000) * (usage.input + (orchestration?.input ?? 0));
+	usage.cost.output = (rates.output / 1000000) * (usage.output + (orchestration?.output ?? 0));
+	usage.cost.cacheRead = (rates.cacheRead / 1000000) * (usage.cacheRead + (orchestration?.cacheRead ?? 0));
+	usage.cost.cacheWrite = cacheWriteCost(rates, usage);
 	usage.cost.total = usage.cost.input + usage.cost.output + usage.cost.cacheRead + usage.cost.cacheWrite;
 	return usage.cost;
 }
@@ -56,7 +65,7 @@ export function calculateCost<TApi extends Api>(model: Model<TApi>, usage: Usage
 /**
  * Price cache-write tokens, honoring the TTL breakdown when the provider reports one.
  *
- * `model.cost.cacheWrite` is the 5-minute write rate (Anthropic bills 5m writes at
+ * `rates.cacheWrite` is the 5-minute write rate (Anthropic bills 5m writes at
  * 1.25x base input). When `usage.cttl` is present the write mixes 5m and 1h
  * breakpoints — omp defaults to 1h retention on first-party Anthropic, and 1h writes
  * bill at 2x base input — so each component is priced at its own rate instead of the
@@ -70,14 +79,14 @@ export function calculateCost<TApi extends Api>(model: Model<TApi>, usage: Usage
  * so any unattributed remainder is priced at the flat rate instead of being dropped:
  * a partial or stale breakdown must never make write tokens free.
  */
-function cacheWriteCost<TApi extends Api>(model: Model<TApi>, usage: Usage): number {
-	const rate5m = model.cost.cacheWrite / 1000000;
+function cacheWriteCost(rates: TokenCost, usage: Usage): number {
+	const rate5m = rates.cacheWrite / 1000000;
 	const cttl = usage.cttl;
 	if (!cttl) return rate5m * usage.cacheWrite;
 	const fiveMinute = cttl.ephemeral5m ?? 0;
 	const oneHour = cttl.ephemeral1h ?? 0;
 	const residual = Math.max(0, usage.cacheWrite - fiveMinute - oneHour);
-	return rate5m * (fiveMinute + residual) + ((model.cost.input * 2) / 1000000) * oneHour;
+	return rate5m * (fiveMinute + residual) + ((rates.input * 2) / 1000000) * oneHour;
 }
 
 /**

packages/catalog/src/provider-models/openai-compat.ts

@@ -867,7 +867,36 @@ export function umansModelManagerOptions(config?: UmansModelManagerConfig): Mode
 // ---------------------------------------------------------------------------
 
 const OPENAI_API_BASE_URL = "https://api.openai.com/v1";
-const OPENAI_GPT_56_SOL_STANDARD_COST = { input: 5, output: 30, cacheRead: 0.5, cacheWrite: 6.25 } as const;
+export const OPENAI_GPT_56_LONG_CONTEXT_COSTS = {
+	luna: {
+		inputThreshold: 272_000,
+		input: 0.4,
+		output: 1.8,
+		cacheRead: 0.04,
+		cacheWrite: 0.5,
+	},
+	sol: {
+		inputThreshold: 272_000,
+		input: 10,
+		output: 45,
+		cacheRead: 1,
+		cacheWrite: 12.5,
+	},
+	terra: {
+		inputThreshold: 272_000,
+		input: 4,
+		output: 18,
+		cacheRead: 0.4,
+		cacheWrite: 5,
+	},
+} as const;
+const OPENAI_GPT_56_SOL_STANDARD_COST = {
+	input: 5,
+	output: 30,
+	cacheRead: 0.5,
+	cacheWrite: 6.25,
+	longContext: OPENAI_GPT_56_LONG_CONTEXT_COSTS.sol,
+} as const;
 const OPENAI_GPT_56_CYBER_STANDARD_COST = {
 	input: 12.5,
 	output: 75,

packages/catalog/src/types.ts

@@ -820,6 +820,28 @@ export interface RemoteCompactionConfig<TApi extends Api = Api> {
 	model?: string;
 }
 
+/** Per-million-token rates for one model pricing tier. */
+export interface TokenCost {
+	input: number;
+	output: number;
+	cacheRead: number;
+	cacheWrite: number;
+}
+
+/**
+ * Rates applied to the full request when its prompt exceeds `inputThreshold`.
+ * Prompt input is the sum of uncached, cached-read, cache-write, and
+ * provider-orchestration input tokens.
+ */
+export interface LongContextTokenCost extends TokenCost {
+	inputThreshold: number;
+}
+
+/** Base token rates plus an optional long-context tier. */
+export interface ModelCost extends TokenCost {
+	longContext?: LongContextTokenCost;
+}
+
 // Model interface for the unified model system
 export interface Model<TApi extends Api = Api> {
 	id: string;
@@ -865,12 +887,7 @@ export interface Model<TApi extends Api = Api> {
 	gitlabDuoWorkflowRootNamespaceId?: string;
 	/** Cursor `max_mode` request flag returned by `GetUsableModels` for premium models that require max mode. */
 	cursorMaxMode?: boolean;
-	cost: {
-		input: number; // $/million tokens
-		output: number; // $/million tokens
-		cacheRead: number; // $/million tokens
-		cacheWrite: number; // $/million tokens
-	};
+	cost: ModelCost;
 	/** Premium Copilot requests charged per user-initiated request (defaults to 1). */
 	premiumMultiplier?: number;
 	contextWindow: number | null;

packages/catalog/test/build.test.ts

@@ -763,6 +763,52 @@ describe("model cache spec round trip", () => {
 		}
 	});
 
+	it("preserves static long-context pricing through dynamic refresh and cache restore", async () => {
+		const tempDir = await fs.mkdtemp(path.join(os.tmpdir(), "pi-catalog-tiered-cost-"));
+		const dbPath = path.join(tempDir, "models.db");
+		const staticModel = completionsSpec({
+			id: "tiered-model",
+			provider: "tiered-cost-test",
+			cost: {
+				input: 1,
+				output: 2,
+				cacheRead: 0.1,
+				cacheWrite: 1.25,
+				longContext: {
+					inputThreshold: 272_000,
+					input: 2,
+					output: 3,
+					cacheRead: 0.2,
+					cacheWrite: 2.5,
+				},
+			},
+		});
+		const dynamicModel = completionsSpec({
+			...staticModel,
+			cost: { input: 3, output: 4, cacheRead: 0.3, cacheWrite: 3.75 },
+		});
+		const options = {
+			providerId: "tiered-cost-test",
+			staticModels: [staticModel],
+			cacheDbPath: dbPath,
+		};
+		try {
+			const online = await resolveProviderModels<"openai-completions">(
+				{ ...options, fetchDynamicModels: async () => [dynamicModel] },
+				"online",
+			);
+			expect(online.models[0]?.cost).toEqual({
+				...dynamicModel.cost,
+				longContext: staticModel.cost.longContext,
+			});
+
+			const offline = await resolveProviderModels<"openai-completions">(options, "offline");
+			expect(offline.models[0]?.cost.longContext).toEqual(staticModel.cost.longContext);
+		} finally {
+			await fs.rm(tempDir, { recursive: true, force: true });
+		}
+	});
+
 	it("invalidates schema-v10 rows that predate computer-use capability provenance", async () => {
 		const tempDir = await fs.mkdtemp(path.join(os.tmpdir(), "pi-catalog-legacy-computer-cache-"));
 		const dbPath = path.join(tempDir, "models.db");

packages/catalog/test/generated-policies.test.ts

@@ -91,6 +91,35 @@ describe("generated model policies", () => {
 		expect(models[3]?.priority).toBe(1);
 	});
 
+	it("applies GPT-5.6 off and long-context pricing through request-model aliases", () => {
+		const models: ModelSpec<Api>[] = [
+			createSpec({ id: "gpt-5.6", api: "openai-responses", provider: "openai" }),
+			createSpec({ id: "gpt-5.6-luna", api: "openai-responses", provider: "openai" }),
+			{
+				...createSpec({ id: "gpt-5.6-sol-pro", api: "openai-responses", provider: "openai" }),
+				requestModelId: "gpt-5.6-sol",
+			},
+			{
+				...createSpec({ id: "gpt-5.6-terra-pro", api: "openai-responses", provider: "openai" }),
+				requestModelId: "gpt-5.6-terra",
+			},
+			createSpec({ id: "gpt-5.6", api: "openai-responses", provider: "openrouter" }),
+		];
+
+		applyGeneratedModelPolicies(models);
+
+		for (const model of models.slice(0, 4)) {
+			expect(model.compat).toMatchObject({ reasoningDisableMode: "none-effort" });
+			expect(model.cost.longContext?.inputThreshold).toBe(272_000);
+		}
+		expect(models[0]?.cost.longContext).toMatchObject({ input: 10, output: 45 });
+		expect(models[1]?.cost.longContext).toMatchObject({ input: 0.4, output: 1.8 });
+		expect(models[2]?.cost.longContext).toMatchObject({ input: 10, output: 45 });
+		expect(models[3]?.cost.longContext).toMatchObject({ input: 4, output: 18 });
+		expect(models[4]?.compat).toBeUndefined();
+		expect(models[4]?.cost.longContext).toBeUndefined();
+	});
+
 	it("pins GPT-5.6 Codex-transport context window to the 372K hard capacity (#5705)", () => {
 		const models: ModelSpec<Api>[] = [
 			// Codex discovery underreports these via DEFAULT_CONTEXT_WINDOW=272000.

packages/catalog/test/openai-daybreak.test.ts

@@ -2,19 +2,32 @@ import { describe, expect, test } from "bun:test";
 import { buildModel } from "@oh-my-pi/pi-catalog/build";
 import { Effort } from "@oh-my-pi/pi-catalog/effort";
 import { getSupportedEfforts } from "@oh-my-pi/pi-catalog/model-thinking";
+import { getBundledModel } from "@oh-my-pi/pi-catalog/models";
 import { OPENAI_DAYBREAK_CURATED_FALLBACK_MODELS } from "@oh-my-pi/pi-catalog/provider-models/openai-compat";
 import type { Api, ModelSpec } from "@oh-my-pi/pi-catalog/types";
 import { applyGeneratedModelPolicies } from "../scripts/generated-policies";
 
 const DAYBREAK_EFFORTS = [Effort.Low, Effort.Medium, Effort.High, Effort.XHigh, Effort.Max];
 
-describe("OpenAI Daybreak models", () => {
+describe("OpenAI Daybreak and GPT-5.6 models", () => {
 	test("curates the documented aliases and Cyber snapshot with standard API pricing", () => {
 		const byId = Object.fromEntries(OPENAI_DAYBREAK_CURATED_FALLBACK_MODELS.map(model => [model.id, model]));
 		expect(Object.keys(byId)).toEqual(["daybreak-blue-latest", "daybreak-red-latest", "gpt-5.6-cyber"]);
 		expect(byId["daybreak-blue-latest"]).toMatchObject({
 			name: "Daybreak Blue",
-			cost: { input: 5, output: 30, cacheRead: 0.5, cacheWrite: 6.25 },
+			cost: {
+				input: 5,
+				output: 30,
+				cacheRead: 0.5,
+				cacheWrite: 6.25,
+				longContext: {
+					inputThreshold: 272_000,
+					input: 10,
+					output: 45,
+					cacheRead: 1,
+					cacheWrite: 12.5,
+				},
+			},
 			contextWindow: 1_050_000,
 			maxTokens: 128_000,
 		});
@@ -27,6 +40,29 @@ describe("OpenAI Daybreak models", () => {
 		}
 	});
 
+	test("bakes off support and long-context pricing onto every first-party GPT-5.6 alias", () => {
+		const longContextCosts = {
+			"daybreak-blue-latest": { input: 10, output: 45, cacheRead: 1, cacheWrite: 12.5 },
+			"gpt-5.6": { input: 10, output: 45, cacheRead: 1, cacheWrite: 12.5 },
+			"gpt-5.6-luna": { input: 0.4, output: 1.8, cacheRead: 0.04, cacheWrite: 0.5 },
+			"gpt-5.6-luna-pro": { input: 0.4, output: 1.8, cacheRead: 0.04, cacheWrite: 0.5 },
+			"gpt-5.6-sol": { input: 10, output: 45, cacheRead: 1, cacheWrite: 12.5 },
+			"gpt-5.6-sol-pro": { input: 10, output: 45, cacheRead: 1, cacheWrite: 12.5 },
+			"gpt-5.6-terra": { input: 4, output: 18, cacheRead: 0.4, cacheWrite: 5 },
+			"gpt-5.6-terra-pro": { input: 4, output: 18, cacheRead: 0.4, cacheWrite: 5 },
+		} as const;
+		for (const [id, longContext] of Object.entries(longContextCosts)) {
+			const model = getBundledModel<"openai-responses">("openai", id);
+			expect(model.compat.reasoningDisableMode).toBe("none-effort");
+			expect(model.cost.longContext).toEqual({ inputThreshold: 272_000, ...longContext });
+		}
+		for (const id of ["daybreak-red-latest", "gpt-5.6-cyber"]) {
+			const model = getBundledModel<"openai-responses">("openai", id);
+			expect(model.compat.reasoningDisableMode).toBe("none-effort");
+			expect(model.cost.longContext).toBeUndefined();
+		}
+	});
+
 	test("exposes off and every GPT-5.6 wire effort on all Daybreak IDs", () => {
 		const generated: ModelSpec<Api>[] = OPENAI_DAYBREAK_CURATED_FALLBACK_MODELS.map(model => ({
 			...model,

packages/coding-agent/src/config/model-patch.ts

@@ -223,11 +223,13 @@ export function applyModelPatch(base: Model<Api>, patch: ModelPatch, transport:
 	}
 	if (patch.premiumMultiplier !== undefined) result.premiumMultiplier = patch.premiumMultiplier;
 	if (patch.cost) {
+		const longContext = patch.cost.longContext ?? base.cost.longContext;
 		result.cost = {
 			input: patch.cost.input ?? base.cost.input,
 			output: patch.cost.output ?? base.cost.output,
 			cacheRead: patch.cost.cacheRead ?? base.cost.cacheRead,
 			cacheWrite: patch.cost.cacheWrite ?? base.cost.cacheWrite,
+			...(longContext ? { longContext } : {}),
 		};
 	}
 	let compat: ModelSpec<Api>["compat"];

packages/coding-agent/test/model-registry.test.ts

@@ -1312,7 +1312,7 @@ describe("ModelRegistry", () => {
 				},
 			});
 			costPartial = readonlyRegistry({
-				providers: { openrouter: { modelOverrides: { "anthropic/claude-sonnet-4": { cost: { input: 99 } } } } },
+				providers: { openai: { modelOverrides: { "gpt-5.6": { cost: { input: 99 } } } } },
 			});
 			addHeaders = readonlyRegistry({
 				providers: {
@@ -1438,12 +1438,15 @@ describe("ModelRegistry", () => {
 			expect(invalid.find("myprovider", "my-model")).toBeUndefined();
 		});
 
-		test("model override can change cost fields partially", () => {
-			const sonnet = getModelsForProvider(costPartial, "openrouter").find(m => m.id === "anthropic/claude-sonnet-4");
-			// Input cost should be overridden
-			expect(sonnet?.cost.input).toBe(99);
-			// Other cost fields should be preserved from built-in
-			expect(sonnet?.cost.output).toBeGreaterThan(0);
+		test("model override can change cost fields partially without dropping long-context pricing", () => {
+			const gpt56 = getModelsForProvider(costPartial, "openai").find(m => m.id === "gpt-5.6");
+			expect(gpt56?.cost.input).toBe(99);
+			expect(gpt56?.cost.output).toBeGreaterThan(0);
+			expect(gpt56?.cost.longContext).toMatchObject({
+				inputThreshold: 272_000,
+				input: 10,
+				output: 45,
+			});
 		});
 
 		test("model override can add headers", () => {