[Feat] Add GLM 5.3 support to Z AI and OpenCode Go

packages/types/src/__tests__/lite-llm.test.ts

@@ -20,7 +20,7 @@ describe("LiteLLM preserveReasoning model detection", () => {
 
 	it("matches case-insensitively", () => {
 		expect(isLiteLLMPreserveReasoningModel("MiniMax-M2.7-Highspeed")).toBe(true)
-		expect(isLiteLLMPreserveReasoningModel("GLM-5.2")).toBe(true)
+		expect(isLiteLLMPreserveReasoningModel("GLM-5.3")).toBe(true)
 	})
 
 	it("does not match model ids that merely contain a known family as a substring", () => {

packages/types/src/__tests__/opencode-go.test.ts

@@ -21,6 +21,7 @@ describe("opencode-go registry", () => {
 		"glm-5",
 		"glm-5.1",
 		"glm-5.2",
+		"glm-5.3",
 		"kimi-k3",
 		"kimi-k2.5",
 		"kimi-k2.6",
@@ -78,6 +79,22 @@ describe("opencode-go registry", () => {
 			expect(info?.outputPrice).toBe(15.0)
 			expect(info?.cacheReadsPrice).toBe(0.3)
 		})
+
+		it("glm-5.3 exposes its native context, pricing, and always-on reasoning levels", () => {
+			const info = getOpencodeGoModelInfo("glm-5.3")
+			expect(info).toBeDefined()
+			expect(info?.maxTokens).toBe(131_072)
+			expect(info?.contextWindow).toBe(1_000_000)
+			expect(info?.supportsImages).toBe(false)
+			expect(info?.supportsPromptCache).toBe(true)
+			expect(info?.supportsMaxTokens).toBe(true)
+			expect(info?.supportsReasoningEffort).toEqual(["low", "high", "max"])
+			expect(info?.reasoningEffort).toBe("max")
+			expect(info?.preserveReasoning).toBe(true)
+			expect(info?.inputPrice).toBe(1.4)
+			expect(info?.outputPrice).toBe(4.4)
+			expect(info?.cacheReadsPrice).toBe(0.26)
+		})
 	})
 
 	describe("OPENCODE_GO_ANTHROPIC_FORMAT_MODELS", () => {

packages/types/src/__tests__/provider-settings.test.ts

@@ -139,7 +139,7 @@ describe("getApiProtocol", () => {
 		})
 
 		it("should return 'openai' for opencode-go OpenAI-format models (GLM/DeepSeek/etc.)", () => {
-			expect(getApiProtocol(providerIdentifiers.opencodeGo, "glm-5.2")).toBe(OPENAI_API_PROTOCOL)
+			expect(getApiProtocol(providerIdentifiers.opencodeGo, "glm-5.3")).toBe(OPENAI_API_PROTOCOL)
 			expect(getApiProtocol(providerIdentifiers.opencodeGo, "deepseek-v4-pro")).toBe(OPENAI_API_PROTOCOL)
 			expect(getApiProtocol(providerIdentifiers.opencodeGo, "kimi-k2.5")).toBe(OPENAI_API_PROTOCOL)
 			expect(getApiProtocol(providerIdentifiers.opencodeGo, "mimo-v2.5")).toBe(OPENAI_API_PROTOCOL)

packages/types/src/providers/lite-llm.ts

@@ -56,6 +56,7 @@ export const LITELLM_PRESERVE_REASONING_MODEL_IDS = [
 	"glm-5",
 	"glm-5.1",
 	"glm-5.2",
+	"glm-5.3",
 	"glm-5-turbo",
 
 	// bedrock.ts, minimax.ts, opencode-go.ts

packages/types/src/providers/opencode-go.ts

@@ -86,6 +86,21 @@ export const opencodeGoModels: Record<string, ModelInfo> = {
 		description:
 			"GLM-5.1 is Zhipu's most capable model with a 200k context window, 128k max output, and built-in thinking capabilities. Available via the Opencode Go plan.",
 	},
+	"glm-5.3": {
+		maxTokens: 131_072,
+		contextWindow: 1_000_000,
+		supportsImages: false,
+		supportsPromptCache: true,
+		supportsMaxTokens: true,
+		supportsReasoningEffort: ["low", "high", "max"],
+		reasoningEffort: "max",
+		preserveReasoning: true,
+		inputPrice: 1.4,
+		outputPrice: 4.4,
+		cacheReadsPrice: 0.26,
+		description:
+			"GLM-5.3 is Zhipu's flagship coding and agent model with a 1M context window, 128k max output, and always-on reasoning with configurable effort (Low/High/Max). Available via the Opencode Go plan.",
+	},
 	"glm-5.2": {
 		maxTokens: 131_072,
 		contextWindow: 1_000_000,

src/api/providers/__tests__/opencode-go.spec.ts

@@ -802,7 +802,7 @@ describe("OpencodeGoHandler", () => {
 		})
 
 		it("classifies OpenAI-compatible Go models as non-Anthropic-format", () => {
-			expect(isOpencodeGoAnthropicFormatModel("glm-5.2")).toBe(false)
+			expect(isOpencodeGoAnthropicFormatModel("glm-5.3")).toBe(false)
 			expect(isOpencodeGoAnthropicFormatModel("kimi-k2.6")).toBe(false)
 			expect(isOpencodeGoAnthropicFormatModel("deepseek-v4-pro")).toBe(false)
 			expect(isOpencodeGoAnthropicFormatModel("mimo-v2.5")).toBe(false)

src/api/providers/fetchers/__tests__/litellm.spec.ts

@@ -765,7 +765,7 @@ describe("getLiteLLMModels", () => {
 				data: {
 					data: [
 						{
-							model_name: "glm-5.2",
+							model_name: "glm-5.3",
 							model_info: {
 								max_tokens: 8192,
 								max_input_tokens: 128000,
@@ -782,7 +782,7 @@ describe("getLiteLLMModels", () => {
 
 			const result = await getLiteLLMModels("test-api-key", "http://localhost:4000")
 
-			expect(result["glm-5.2"]).toMatchObject({ preserveReasoning: true })
+			expect(result["glm-5.3"]).toMatchObject({ preserveReasoning: true })
 		})
 
 		it("does not match a model id that merely contains a known family as a substring", async () => {

src/api/providers/fetchers/__tests__/opencode-go.spec.ts

@@ -157,6 +157,20 @@ describe("Opencode Go Fetchers", () => {
 			expect(info.outputPrice).toBe(4.4)
 		})
 
+		it("resolves GLM-5.3 with always-on Low/High/Max reasoning effort", () => {
+			const info = parseOpencodeGoModel({ id: "glm-5.3" })
+			expect(info.contextWindow).toBe(1_000_000)
+			expect(info.maxTokens).toBe(131_072)
+			expect(info.supportsPromptCache).toBe(true)
+			expect(info.supportsMaxTokens).toBe(true)
+			expect(info.supportsReasoningEffort).toEqual(["low", "high", "max"])
+			expect(info.reasoningEffort).toBe("max")
+			expect(info.preserveReasoning).toBe(true)
+			expect(info.inputPrice).toBe(1.4)
+			expect(info.outputPrice).toBe(4.4)
+			expect(info.cacheReadsPrice).toBe(0.26)
+		})
+
 		it("falls back to defaults for an unknown model with no cache pricing", () => {
 			const info = parseOpencodeGoModel({ id: "x", context_window: 100000, max_tokens: 8000 })
 			expect(info.supportsPromptCache).toBe(false)