feat(billing): add GLM / Kimi / MiniMax fallback pricing for Chinese LLM providers

将 fix/deepseek-fallback-pricing 的 DeepSeek V4 Pro/Flash 定价收编，并扩展国产 LLM 兜底定价覆盖： - 智谱 GLM (z.ai 公开 SKU 13 个): glm-5.1 / glm-5 / glm-5-turbo / glm-4.7 / glm-4.7-flashx / glm-4.6 / glm-4.5 / glm-4.5-x / glm-4.5-air / glm-4.5-airx / glm-4-32b-0414-128k / glm-4.5-flash / glm-4.7-flash - 月之暗面 Kimi K 系列 4 个: kimi-k2.6 / kimi-k2.5 / kimi-k2-thinking / kimi-k2 (K2-0905/K2-0711 官方未保留定价，隐性回退到 kimi-k2) - MiniMax M 系列 6 个: minimax-m3 (≤512K) / minimax-m2.7 / minimax-m2.7-highspeed / minimax-m2.5 / minimax-m2.1 / minimax-m2 - DeepSeek V4 沿用原 fix/deepseek-fallback-pricing 的 entry 移植过来所有定价数据来自各家官方定价页 (USD/MTok 口径)，与现有 Claude/GPT 风格保持一致 (硬编码在 Go 代码里，admin channel 优先)。匹配策略：长 key 优先 (glm-5.1 优先于 glm-5, k2.6 优先于 k2)；未列出的国产厂商 alias (qwen/doubao/hunyuan) 一律不返回兜底价，避免误计价——这与 fix/deepseek-fallback-pricing 的白名单语义一致。数据源注释 (Source URL) 内嵌在每个 initFallbackPricing 分组开头，便于后续 PR 同步上游价格变化。
2026-09-24 16:05:44 +08:00 · 2026-06-16 19:37:02 +08:00
parent f597d98bdf
commit a4ce73391b
2 changed files with 460 additions and 1 deletions
@@ -323,6 +323,180 @@ func (s *BillingService) initFallbackPricing() {
 		CacheReadPricePerTokenPriority: 0.3e-6,
 		SupportsCacheBreakdown:         false,
 	}
+
+	// ============================================================
+	// 国产 LLM 兜底定价（数据源：各家官方定价页/USD 口径）
+	// 顺序：DeepSeek → 智谱 GLM → 月之暗面 Kimi → MiniMax
+	// 覆盖逻辑见同文件 getFallbackPricing()
+	// ============================================================
+
+	// ---- DeepSeek V4 系列 ----
+	// Source: https://api-docs.deepseek.com/quick_start/pricing
+	// （deepseek-chat / deepseek-reasoner 为 deepseek-v4-flash 的兼容别名，2026/07/24 弃用）
+	s.fallbackPrices["deepseek-v4-pro"] = &ModelPricing{
+		InputPricePerToken:     4.35e-7,  // $0.435 per MTok (cache miss)
+		OutputPricePerToken:    8.7e-7,   // $0.87 per MTok
+		CacheReadPricePerToken: 3.625e-9, // $0.003625 per MTok (cache hit)
+		SupportsCacheBreakdown: false,
+	}
+	s.fallbackPrices["deepseek-v4-flash"] = &ModelPricing{
+		InputPricePerToken:     1.4e-7, // $0.14 per MTok (cache miss)
+		OutputPricePerToken:    2.8e-7, // $0.28 per MTok
+		CacheReadPricePerToken: 2.8e-9, // $0.0028 per MTok (cache hit)
+		SupportsCacheBreakdown: false,
+	}
+
+	// ---- 智谱 GLM（Z.AI）----
+	// Source: https://docs.z.ai/guides/overview/pricing (USD per 1M tokens)
+	// 注意：CacheReadPricePerToken 即"缓存命中"价格，CacheCreationPricePerToken 留空（智谱未公开写入价，按 0 处理）。
+	// GLM-4.6 与 GLM-4.5 在 z.ai 国际版上定价一致；GLM-4.5 国内按 ¥0.8/¥2，汇率换算后约 $0.112/$0.28，与国际版 $0.6/$2.2 不同，本分支采用国际版 USD 口径与现有 Claude/GPT 一致。
+	s.fallbackPrices["glm-5.1"] = &ModelPricing{
+		InputPricePerToken:     1.4e-6, // $1.40 per MTok
+		OutputPricePerToken:    4.4e-6, // $4.40 per MTok
+		CacheReadPricePerToken: 0.26e-6,
+		SupportsCacheBreakdown: false,
+	}
+	s.fallbackPrices["glm-5"] = &ModelPricing{
+		InputPricePerToken:     1e-6, // $1.00 per MTok
+		OutputPricePerToken:    3.2e-6,
+		CacheReadPricePerToken: 0.2e-6,
+		SupportsCacheBreakdown: false,
+	}
+	s.fallbackPrices["glm-5-turbo"] = &ModelPricing{
+		InputPricePerToken:     1.2e-6,
+		OutputPricePerToken:    4e-6,
+		CacheReadPricePerToken: 0.24e-6,
+		SupportsCacheBreakdown: false,
+	}
+	s.fallbackPrices["glm-4.7"] = &ModelPricing{
+		InputPricePerToken:     0.6e-6, // $0.60 per MTok
+		OutputPricePerToken:    2.2e-6,
+		CacheReadPricePerToken: 0.11e-6,
+		SupportsCacheBreakdown: false,
+	}
+	s.fallbackPrices["glm-4.7-flashx"] = &ModelPricing{
+		InputPricePerToken:     0.07e-6, // $0.07 per MTok
+		OutputPricePerToken:    0.4e-6,
+		CacheReadPricePerToken: 0.01e-6,
+		SupportsCacheBreakdown: false,
+	}
+	s.fallbackPrices["glm-4.6"] = &ModelPricing{
+		InputPricePerToken:     0.6e-6, // $0.60 per MTok
+		OutputPricePerToken:    2.2e-6,
+		CacheReadPricePerToken: 0.11e-6,
+		SupportsCacheBreakdown: false,
+	}
+	s.fallbackPrices["glm-4.5"] = &ModelPricing{
+		InputPricePerToken:     0.6e-6, // $0.60 per MTok
+		OutputPricePerToken:    2.2e-6,
+		CacheReadPricePerToken: 0.11e-6,
+		SupportsCacheBreakdown: false,
+	}
+	s.fallbackPrices["glm-4.5-x"] = &ModelPricing{
+		InputPricePerToken:     2.2e-6, // $2.20 per MTok
+		OutputPricePerToken:    8.9e-6,
+		CacheReadPricePerToken: 0.45e-6,
+		SupportsCacheBreakdown: false,
+	}
+	s.fallbackPrices["glm-4.5-air"] = &ModelPricing{
+		InputPricePerToken:     0.2e-6, // $0.20 per MTok
+		OutputPricePerToken:    1.1e-6,
+		CacheReadPricePerToken: 0.03e-6,
+		SupportsCacheBreakdown: false,
+	}
+	s.fallbackPrices["glm-4.5-airx"] = &ModelPricing{
+		InputPricePerToken:     1.1e-6,
+		OutputPricePerToken:    4.5e-6,
+		CacheReadPricePerToken: 0.22e-6,
+		SupportsCacheBreakdown: false,
+	}
+	s.fallbackPrices["glm-4-32b-0414-128k"] = &ModelPricing{
+		InputPricePerToken:     0.1e-6, // $0.10 per MTok
+		OutputPricePerToken:    0.1e-6,
+		SupportsCacheBreakdown: false,
+	}
+	// GLM-4.5-Flash / GLM-4.7-Flash 在 z.ai 上为 Free，保留 zero-cost entry 防止未知 alias 误计费。
+	s.fallbackPrices["glm-4.5-flash"] = &ModelPricing{
+		InputPricePerToken:     0,
+		OutputPricePerToken:    0,
+		SupportsCacheBreakdown: false,
+	}
+	s.fallbackPrices["glm-4.7-flash"] = &ModelPricing{
+		InputPricePerToken:     0,
+		OutputPricePerToken:    0,
+		SupportsCacheBreakdown: false,
+	}
+
+	// ---- 月之暗面 Kimi（K 系列）----
+	// Source: https://platform.moonshot.cn/docs/pricing/overview (元/百万 tokens 口径)
+	//       交叉验证：https://www.tmtpost.com/7961404.html (USD 口径)
+	// Moonshot V1 (¥2/¥5/¥10 多 tier) 公开页未直接标注 USD 价，本分支不覆盖，避免误计价。
+	// K2-0905 / K2-0711 官方页面未保留定价，不覆盖。
+	s.fallbackPrices["kimi-k2.6"] = &ModelPricing{
+		InputPricePerToken:     0.95e-6, // $0.95 per MTok (cache miss)
+		OutputPricePerToken:    4e-6,    // $4.00 per MTok
+		CacheReadPricePerToken: 0.15e-6, // $0.15 per MTok (cache hit, ¥1.10)
+		SupportsCacheBreakdown: false,
+	}
+	s.fallbackPrices["kimi-k2.5"] = &ModelPricing{
+		InputPricePerToken:     0.60e-6, // $0.60 per MTok
+		OutputPricePerToken:    3e-6,    // $3.00 per MTok
+		CacheReadPricePerToken: 0.098e-6,
+		SupportsCacheBreakdown: false,
+	}
+	s.fallbackPrices["kimi-k2-thinking"] = &ModelPricing{
+		InputPricePerToken:     0.56e-6, // ¥4/百万 ≈ $0.56
+		OutputPricePerToken:    2.24e-6, // ¥16/百万
+		CacheReadPricePerToken: 0.14e-6, // ¥1/百万
+		SupportsCacheBreakdown: false,
+	}
+	s.fallbackPrices["kimi-k2"] = &ModelPricing{
+		InputPricePerToken:     0.56e-6, // ¥4/百万
+		OutputPricePerToken:    2.24e-6, // ¥16/百万
+		CacheReadPricePerToken: 0.14e-6, // ¥1/百万
+		SupportsCacheBreakdown: false,
+	}
+
+	// ---- MiniMax M 系列 ----
+	// Source: https://platform.minimax.io/docs/guides/pricing-paygo
+	// 注意：MiniMax M3 在 >512K context 时价格翻倍，本兜底采用 ≤512K 标准 tier（保守口径，对用户有利）。
+	// 如需支持长上下文 multiplier，可后续参考 GPT-5.4 模式扩展 LongContextXxx 字段。
+	s.fallbackPrices["minimax-m3"] = &ModelPricing{
+		InputPricePerToken:     0.60e-6, // $0.60 per MTok (≤512K standard tier, 含 50% 永久折扣前原价 $1.20)
+		OutputPricePerToken:    2.40e-6,
+		CacheReadPricePerToken: 0.12e-6,
+		SupportsCacheBreakdown: false,
+	}
+	s.fallbackPrices["minimax-m2.7"] = &ModelPricing{
+		InputPricePerToken:     0.30e-6, // $0.30 per MTok
+		OutputPricePerToken:    1.20e-6,
+		CacheReadPricePerToken: 0.06e-6,
+		SupportsCacheBreakdown: false,
+	}
+	s.fallbackPrices["minimax-m2.7-highspeed"] = &ModelPricing{
+		InputPricePerToken:     0.60e-6,
+		OutputPricePerToken:    2.40e-6,
+		CacheReadPricePerToken: 0.06e-6,
+		SupportsCacheBreakdown: false,
+	}
+	s.fallbackPrices["minimax-m2.5"] = &ModelPricing{
+		InputPricePerToken:     0.30e-6,
+		OutputPricePerToken:    1.20e-6,
+		CacheReadPricePerToken: 0.03e-6,
+		SupportsCacheBreakdown: false,
+	}
+	s.fallbackPrices["minimax-m2.1"] = &ModelPricing{
+		InputPricePerToken:     0.30e-6,
+		OutputPricePerToken:    1.20e-6,
+		CacheReadPricePerToken: 0.03e-6,
+		SupportsCacheBreakdown: false,
+	}
+	s.fallbackPrices["minimax-m2"] = &ModelPricing{
+		InputPricePerToken:     0.30e-6,
+		OutputPricePerToken:    1.20e-6,
+		CacheReadPricePerToken: 0.03e-6,
+		SupportsCacheBreakdown: false,
+	}
 }

 // getFallbackPricing 根据模型系列获取回退价格
@@ -374,6 +548,87 @@ func (s *BillingService) getFallbackPricing(model string) *ModelPricing {
 		return s.fallbackPrices["deepseek-v4-flash"]
 	}

+	// ---- 国产 LLM 兜底匹配 ----
+	// 匹配策略：长 key 优先（具体模型 → 系列 / 厂商），未知型号不回退以避免误计价。
+	// 与 DeepSeek 一样采用"白名单"语义：未在本表命中的国产模型 alias 一律不返回兜底价。
+
+	// 智谱 GLM（z.ai 公开 SKU：glm-5.1 / glm-5 / glm-5-turbo / glm-4.7 / glm-4.6 / glm-4.5 等）
+	// 匹配顺序：先判别最高 tier，再依次降级。
+	if strings.Contains(modelLower, "glm-5.1") {
+		return s.fallbackPrices["glm-5.1"]
+	}
+	if strings.Contains(modelLower, "glm-5-turbo") || strings.Contains(modelLower, "glm-5turbo") {
+		return s.fallbackPrices["glm-5-turbo"]
+	}
+	if strings.Contains(modelLower, "glm-5") {
+		return s.fallbackPrices["glm-5"]
+	}
+	if strings.Contains(modelLower, "glm-4.7-flashx") {
+		return s.fallbackPrices["glm-4.7-flashx"]
+	}
+	if strings.Contains(modelLower, "glm-4.7-flash") {
+		return s.fallbackPrices["glm-4.7-flash"]
+	}
+	if strings.Contains(modelLower, "glm-4.7") {
+		return s.fallbackPrices["glm-4.7"]
+	}
+	if strings.Contains(modelLower, "glm-4.6") {
+		return s.fallbackPrices["glm-4.6"]
+	}
+	if strings.Contains(modelLower, "glm-4.5-flash") {
+		return s.fallbackPrices["glm-4.5-flash"]
+	}
+	if strings.Contains(modelLower, "glm-4.5-x") || strings.Contains(modelLower, "glm-4.5x") {
+		return s.fallbackPrices["glm-4.5-x"]
+	}
+	if strings.Contains(modelLower, "glm-4.5-airx") || strings.Contains(modelLower, "glm-4.5airx") {
+		return s.fallbackPrices["glm-4.5-airx"]
+	}
+	if strings.Contains(modelLower, "glm-4.5-air") || strings.Contains(modelLower, "glm-4.5air") {
+		return s.fallbackPrices["glm-4.5-air"]
+	}
+	if strings.Contains(modelLower, "glm-4.5") {
+		return s.fallbackPrices["glm-4.5"]
+	}
+	if strings.Contains(modelLower, "glm-4-32b") {
+		return s.fallbackPrices["glm-4-32b-0414-128k"]
+	}
+
+	// 月之暗面 Kimi（kimi-k2.6 / kimi-k2.5 / kimi-k2-thinking / kimi-k2）
+	// K2-0905 / K2-0711 官方未保留定价，不进入 fallback。
+	if strings.Contains(modelLower, "kimi-k2.6") || strings.Contains(modelLower, "kimi-k2-6") {
+		return s.fallbackPrices["kimi-k2.6"]
+	}
+	if strings.Contains(modelLower, "kimi-k2.5") || strings.Contains(modelLower, "kimi-k2-5") {
+		return s.fallbackPrices["kimi-k2.5"]
+	}
+	if strings.Contains(modelLower, "kimi-k2-thinking") || strings.Contains(modelLower, "kimi-k2-thinking-") {
+		return s.fallbackPrices["kimi-k2-thinking"]
+	}
+	if strings.Contains(modelLower, "kimi-k2") || strings.Contains(modelLower, "kimi/k2") {
+		return s.fallbackPrices["kimi-k2"]
+	}
+
+	// MiniMax M 系列（M3 / M2.7 / M2.5 / M2.1 / M2；含 highspeed 变体）
+	if strings.Contains(modelLower, "minimax-m3") || strings.Contains(modelLower, "MiniMax-M3") {
+		return s.fallbackPrices["minimax-m3"]
+	}
+	if strings.Contains(modelLower, "minimax-m2.7-highspeed") || strings.Contains(modelLower, "minimax-m2-7-highspeed") {
+		return s.fallbackPrices["minimax-m2.7-highspeed"]
+	}
+	if strings.Contains(modelLower, "minimax-m2.7") || strings.Contains(modelLower, "minimax-m2-7") {
+		return s.fallbackPrices["minimax-m2.7"]
+	}
+	if strings.Contains(modelLower, "minimax-m2.5") || strings.Contains(modelLower, "minimax-m2-5") {
+		return s.fallbackPrices["minimax-m2.5"]
+	}
+	if strings.Contains(modelLower, "minimax-m2.1") || strings.Contains(modelLower, "minimax-m2-1") {
+		return s.fallbackPrices["minimax-m2.1"]
+	}
+	if strings.Contains(modelLower, "minimax-m2") || strings.Contains(modelLower, "minimax-m-2") {
+		return s.fallbackPrices["minimax-m2"]
+	}
+
 	// OpenAI（GPT-5 / Codex 族）：仅匹配已知型号，避免未知 OpenAI 型号误计价。
 	if normalized := normalizeKnownOpenAICodexModel(modelLower); normalized != "" {
 		switch normalized {
@@ -383,7 +383,211 @@ func TestGetFallbackPricing_FamilyMatching(t *testing.T) {
 			expectedOutput:    2.8e-7,
 			expectedCacheRead: 2.8e-9,
 		},
-		{name: "non supported family", model: "qwen-max", expectNilPricing: true},
+
+		// ---- 智谱 GLM（z.ai USD 口径）----
+		{
+			name:              "glm 5.1 flagship",
+			model:             "glm-5.1",
+			expectedInput:     1.4e-6,
+			expectedOutput:    4.4e-6,
+			expectedCacheRead: 0.26e-6,
+		},
+		{
+			name:              "glm 5 base",
+			model:             "glm-5",
+			expectedInput:     1e-6,
+			expectedOutput:    3.2e-6,
+			expectedCacheRead: 0.2e-6,
+		},
+		{
+			name:              "glm 5 turbo",
+			model:             "glm-5-turbo",
+			expectedInput:     1.2e-6,
+			expectedOutput:    4e-6,
+			expectedCacheRead: 0.24e-6,
+		},
+		{
+			name:              "glm 4.7",
+			model:             "glm-4.7",
+			expectedInput:     0.6e-6,
+			expectedOutput:    2.2e-6,
+			expectedCacheRead: 0.11e-6,
+		},
+		{
+			name:              "glm 4.6",
+			model:             "glm-4.6",
+			expectedInput:     0.6e-6,
+			expectedOutput:    2.2e-6,
+			expectedCacheRead: 0.11e-6,
+		},
+		{
+			name:              "glm 4.5",
+			model:             "glm-4.5",
+			expectedInput:     0.6e-6,
+			expectedOutput:    2.2e-6,
+			expectedCacheRead: 0.11e-6,
+		},
+		{
+			name:              "glm 4.5-x premium",
+			model:             "glm-4.5-x",
+			expectedInput:     2.2e-6,
+			expectedOutput:    8.9e-6,
+			expectedCacheRead: 0.45e-6,
+		},
+		{
+			name:              "glm 4.5-air lightweight",
+			model:             "glm-4.5-air",
+			expectedInput:     0.2e-6,
+			expectedOutput:    1.1e-6,
+			expectedCacheRead: 0.03e-6,
+		},
+		{
+			name:              "glm 4.7-flashx",
+			model:             "glm-4.7-flashx",
+			expectedInput:     0.07e-6,
+			expectedOutput:    0.4e-6,
+			expectedCacheRead: 0.01e-6,
+		},
+		{
+			name:              "glm 4.5-flash free tier",
+			model:             "glm-4.5-flash",
+			expectedInput:     0, // Free tier on z.ai
+			expectedOutput:    0,
+			expectedCacheRead: 0,
+		},
+		{
+			name:              "glm 4.7-flash free tier",
+			model:             "glm-4.7-flash",
+			expectedInput:     0,
+			expectedOutput:    0,
+			expectedCacheRead: 0,
+		},
+		{
+			name:              "glm 4-32b legacy",
+			model:             "glm-4-32b-0414-128k",
+			expectedInput:     0.1e-6,
+			expectedOutput:    0.1e-6,
+			expectedCacheRead: 0,
+		},
+		// 关键：5.1 必须先于 5 匹配（避免被 glm-5 抢走）
+		{
+			name:              "glm 5.1 vs glm 5 ordering (verbatim 5.1)",
+			model:             "glm-5.1",
+			expectedInput:     1.4e-6, // = glm-5.1 价格
+			expectedOutput:    4.4e-6,
+			expectedCacheRead: 0.26e-6,
+		},
+		{
+			name:              "glm 4.5-air vs glm 4.5 ordering",
+			model:             "glm-4.5-air",
+			expectedInput:     0.2e-6, // = glm-4.5-air 价格（不是 glm-4.5 的 0.6e-6）
+			expectedOutput:    1.1e-6,
+			expectedCacheRead: 0.03e-6,
+		},
+
+		// ---- 月之暗面 Kimi ----
+		{
+			name:              "kimi k2.6 flagship",
+			model:             "kimi-k2.6",
+			expectedInput:     0.95e-6,
+			expectedOutput:    4e-6,
+			expectedCacheRead: 0.15e-6,
+		},
+		{
+			name:              "kimi k2.5",
+			model:             "kimi-k2.5",
+			expectedInput:     0.60e-6,
+			expectedOutput:    3e-6,
+			expectedCacheRead: 0.098e-6,
+		},
+		{
+			name:              "kimi k2-thinking",
+			model:             "kimi-k2-thinking",
+			expectedInput:     0.56e-6,
+			expectedOutput:    2.24e-6,
+			expectedCacheRead: 0.14e-6,
+		},
+		{
+			name:              "kimi k2 base",
+			model:             "kimi-k2",
+			expectedInput:     0.56e-6,
+			expectedOutput:    2.24e-6,
+			expectedCacheRead: 0.14e-6,
+		},
+		// 关键：k2.6 / k2.5 / k2-thinking 必须先于 k2 匹配
+		{
+			name:              "kimi k2.6 vs k2 ordering",
+			model:             "kimi-k2.6",
+			expectedInput:     0.95e-6, // = k2.6 不是 k2 的 0.56e-6
+			expectedOutput:    4e-6,
+			expectedCacheRead: 0.15e-6,
+		},
+		{
+			name:              "kimi k2 thinking hyphenated variant",
+			model:             "kimi-k2-thinking-preview",
+			expectedInput:     0.56e-6,
+			expectedOutput:    2.24e-6,
+			expectedCacheRead: 0.14e-6,
+		},
+
+		// ---- MiniMax M 系列 ----
+		{
+			name:              "minimax m3",
+			model:             "minimax-m3",
+			expectedInput:     0.60e-6,
+			expectedOutput:    2.40e-6,
+			expectedCacheRead: 0.12e-6,
+		},
+		{
+			name:              "minimax m3 long ctx boundary keep standard tier",
+			model:             "minimax-m3-long", // 仍按 standard tier (≤512K)
+			expectedInput:     0.60e-6,
+			expectedOutput:    2.40e-6,
+			expectedCacheRead: 0.12e-6,
+		},
+		{
+			name:              "minimax m2.7",
+			model:             "minimax-m2.7",
+			expectedInput:     0.30e-6,
+			expectedOutput:    1.20e-6,
+			expectedCacheRead: 0.06e-6,
+		},
+		{
+			name:              "minimax m2.7 highspeed",
+			model:             "minimax-m2.7-highspeed",
+			expectedInput:     0.60e-6,
+			expectedOutput:    2.40e-6,
+			expectedCacheRead: 0.06e-6,
+		},
+		{
+			name:              "minimax m2.5",
+			model:             "minimax-m2.5",
+			expectedInput:     0.30e-6,
+			expectedOutput:    1.20e-6,
+			expectedCacheRead: 0.03e-6,
+		},
+		{
+			name:              "minimax m2 legacy",
+			model:             "minimax-m2",
+			expectedInput:     0.30e-6,
+			expectedOutput:    1.20e-6,
+			expectedCacheRead: 0.03e-6,
+		},
+
+		// ---- 负向用例：未覆盖的国产厂商 / alias 不应误计价 ----
+		{name: "qwen unknown no fallback", model: "qwen-max", expectNilPricing: true},
+		{name: "doubao unknown no fallback", model: "doubao-pro", expectNilPricing: true},
+		{name: "hunyuan unknown no fallback", model: "hunyuan-t1", expectNilPricing: true},
+		{name: "moonshot v1 not covered", model: "moonshot-v1-8k", expectNilPricing: true},
+		// kimi-k2-0905 / kimi-k2-0711 官方未公布独立价，走 kimi-k2 隐性回退（接受）——
+		// 如未来官方公布独立价，需在 getFallbackPricing 加显式分支。
+		{
+			name:              "kimi k2-0905-preview implicit fallback to k2",
+			model:             "kimi-k2-0905-preview",
+			expectedInput:     0.56e-6,
+			expectedOutput:    2.24e-6,
+			expectedCacheRead: 0.14e-6,
+		},
 	}

 	for _, tt := range tests {