Update TCO to July / 将 TCO 更新至 7 月

packages/app/cypress/e2e/chart-overflow-continuation.cy.ts

@@ -160,7 +160,11 @@ describe('Chart overflow continuations', () => {
             cy.wrap($continuation)
               .find('[data-testid="overflow-continuation-label"]')
               .should(($label) => {
-                expect(Number($label.attr('y'))).to.be.greaterThan(arrowY);
+                const offset = Number($label.attr('y')) - arrowY;
+                expect(
+                  Math.abs(offset - 18) < 0.01 || Math.abs(offset + 12) < 0.01,
+                  'label is below the arrow or uses the above-arrow bottom-edge fallback',
+                ).to.equal(true);
               });
           });
         cy.wrap($continuation)

packages/app/cypress/e2e/overview.cy.ts

@@ -28,9 +28,9 @@ const AGENTX_LABEL_ZH = '长上下文多轮真实智能体场景（AgentX）';
 
 const PAGE_TITLE = 'Inference Cost per Million Tokens';
 const PAGE_TITLE_ZH = '推理每百万 token 成本';
-const SOURCE_NOTE = 'Source: InferenceX & SemiAnalysis Market August 2025 AI Cloud TCO Model';
-const SOURCE_LINK_TEXT = 'SemiAnalysis Market August 2025 AI Cloud TCO Model';
-const SOURCE_NOTE_ZH = '来源：InferenceX 与 SemiAnalysis Market August 2025 AI Cloud TCO Model';
+const SOURCE_NOTE = 'Source: InferenceX & SemiAnalysis Market July 2026 AI Cloud TCO Model';
+const SOURCE_LINK_TEXT = 'SemiAnalysis Market July 2026 AI Cloud TCO Model';
+const SOURCE_NOTE_ZH = '来源：InferenceX 与 SemiAnalysis Market July 2026 AI Cloud TCO Model';
 const SOURCE_HREF = 'https://semianalysis.com/ai-cloud-tco-model/';
 const SCOPE_METRIC = 'Hyperscaler cost';
 const SCOPE_DIRECTION = '↓ Lower is better';
@@ -213,7 +213,7 @@ describe('Overview page', () => {
         // its hover/focus/screen-reader label, never as visible text.
         cy.get(
           '[data-testid="overview-pair-value"][data-hardware="b200"] [data-testid="overview-cost-evidence-link"]',
-        ).should('have.text', '$0.067');
+        ).should('have.text', '$0.059');
         cy.get(
           '[data-testid="overview-pair-value"][data-hardware="b200"] [data-testid="overview-cost-evidence-link"]',
         )
@@ -225,7 +225,7 @@ describe('Overview page', () => {
           .and(
             'have.attr',
             'aria-label',
-            'Approximately $0.067. Estimated from validated benchmark runs. Open raw source dashboard for Jul 18: DeepSeek V4 Pro 1.6T · B200 · SGLang · FP4 · MTP',
+            'Approximately $0.059. Estimated from validated benchmark runs. Open raw source dashboard for Jul 18: DeepSeek V4 Pro 1.6T · B200 · SGLang · FP4 · MTP',
           );
         cy.get('[data-testid="overview-pair-missing"]').should('not.exist');
       });
@@ -261,7 +261,7 @@ describe('Overview page', () => {
       platform('b200').find('[data-testid="overview-cost-delta"]').should('not.exist');
       platform('mi355x')
         .find('[data-testid="overview-cost-delta"]')
-        .should('contain.text', '25%')
+        .should('contain.text', '-15%')
         .and('have.attr', 'data-cost-polarity', 'cheaper')
         .then(($badge) => {
           // The shade lives on the cell now, never on the badge itself.
@@ -274,9 +274,9 @@ describe('Overview page', () => {
     desktopModel('DeepSeek-V4-Pro', SINGLE_TURN).within(() => {
       platform('gb200')
         .find('[data-testid="overview-cost-delta"]')
-        .should('contain.text', '+80%')
+        .should('contain.text', '+71%')
         .and('have.attr', 'data-cost-polarity', 'pricier');
-      // +80% saturates the alpha ramp; read the computed value so the
+      // +71% saturates the alpha ramp; read the computed value so the
       // assertion survives the browser normalizing `0.40` to `0.4`.
       expectCellTint('gb200', 'rgba(239, 68, 68, 0.4)');
       // No read at the tier means nothing to grade — the cell stays untinted.
@@ -316,18 +316,13 @@ describe('Overview page', () => {
       });
     });
 
-    // Within the ±5% parity band the cell reads as even, not polarity.
+    // Outside the ±5% parity band the cell carries the matching polarity.
     desktopModel('Kimi-K2.5').within(() => {
       platform('b300')
         .find('[data-testid="overview-cost-delta"]')
-        .should('contain.text', '+2%')
-        .and('have.attr', 'data-cost-polarity', 'even');
-      platform('b300').then(([cell]) => {
-        const [r, g, b] = getComputedStyle(cell.closest('td')!)
-          .backgroundColor.match(/\d+/g)!
-          .map(Number);
-        expect(Math.max(r, g, b) - Math.min(r, g, b)).to.be.lessThan(60);
-      });
+        .should('contain.text', '+11%')
+        .and('have.attr', 'data-cost-polarity', 'pricier');
+      expectCellTint('b300', 'rgba(239, 68, 68,');
     });
   });
 
@@ -440,7 +435,7 @@ describe('Overview page', () => {
       // Priced from the AgentX rows alone — the single-turn sweep never leaks in.
       cy.get(
         '[data-testid="overview-pair-value"][data-hardware="b200"] [data-testid="overview-cost-evidence-link"]',
-      ).should('have.text', '$0.072');
+      ).should('have.text', '$0.064');
       cy.get(
         '[data-testid="overview-pair-value"][data-hardware="mi355x"] [data-testid="overview-cost-evidence-link"]',
       ).should('have.text', '$0.069');
@@ -508,7 +503,7 @@ describe('Overview page', () => {
         cy.get(
           '[data-testid="overview-pair-value"][data-hardware="mi355x"] [data-testid="overview-cost-evidence-link"]',
         )
-          .should('have.text', '$0.061')
+          .should('have.text', '$0.062')
           .and(
             'have.attr',
             'title',
@@ -517,7 +512,7 @@ describe('Overview page', () => {
           .and(
             'have.attr',
             'aria-label',
-            '$0.061. Open raw source dashboard for Jul 18: Qwen3.5 397B · MI355X · SGLang · FP8 · MTP',
+            '$0.062. Open raw source dashboard for Jul 18: Qwen3.5 397B · MI355X · SGLang · FP8 · MTP',
           )
           .should('have.attr', 'href')
           .and('include', '/inference?')
@@ -530,7 +525,7 @@ describe('Overview page', () => {
         cy.get(
           '[data-testid="overview-pair-value"][data-hardware="b200"] [data-testid="overview-cost-evidence-link"]',
         )
-          .should('contain.text', '$0.082')
+          .should('contain.text', '$0.073')
           .should('have.attr', 'href')
           .and('include', 'i_prec=fp4')
           .and('include', 'i_gpus=b200_sglang_mtp');
@@ -576,7 +571,7 @@ describe('Overview page', () => {
       platform('gb300').within(() => {
         cy.get('[data-testid="overview-pair-value"][data-hardware="gb300"]').should(
           'contain.text',
-          '$0.113',
+          '$0.099',
         );
         cy.get('[data-testid="overview-cost-delta"][data-hardware="gb300"]').should(
           'have.attr',
@@ -628,7 +623,7 @@ describe('Overview page', () => {
     });
 
     desktopModel('Qwen-3.5-397B-A17B', SINGLE_TURN).within(() => {
-      platform('b200').should('contain.text', '$0.139').and('contain.text', 'FP8');
+      platform('b200').should('contain.text', '$0.124').and('contain.text', 'FP8');
       platform('mi355x').within(() => {
         cy.get('[data-testid="overview-pair-value"][data-hardware="mi355x"]').should(
           'contain.text',
@@ -659,7 +654,7 @@ describe('Overview page', () => {
       platform('b300').within(() => {
         cy.get('[data-testid="overview-pair-value"][data-hardware="b300"]').should(
           'contain.text',
-          '$0.050',
+          '$0.049',
         );
         cy.get('[data-testid="overview-cost-delta"][data-hardware="b300"]')
           .should('contain.text', '∞')
@@ -700,13 +695,13 @@ describe('Overview page', () => {
         platform('mi355x').within(() => {
           cy.get(
             '[data-testid="overview-pair-value"][data-hardware="mi355x"] [data-testid="overview-cost-evidence-link"]',
-          ).should('have.text', '$0.061');
+          ).should('have.text', '$0.062');
         });
       });
       mobileModel('DeepSeek-V4-Pro', SINGLE_TURN).within(() => {
         cy.get(
           '[data-testid="overview-pair-value"][data-hardware="b200"] [data-testid="overview-cost-evidence-link"]',
-        ).should('have.text', '$0.067');
+        ).should('have.text', '$0.059');
         cy.get('[data-testid="overview-pair-missing"][data-hardware="gb300"]').should(
           'have.attr',
           'title',
@@ -915,8 +910,8 @@ describe('Overview page', () => {
       .and('include', '原始数据仪表板：DeepSeek V4 Pro 1.6T · B200 · SGLang · FP4 · MTP');
     cy.get('@estimatedB200')
       .invoke('attr', 'aria-label')
-      .should('include', '约 $0.067。根据已验证的基准运行结果估算。');
-    cy.get('@estimatedB200').should('have.text', '$0.067');
+      .should('include', '约 $0.059。根据已验证的基准运行结果估算。');
+    cy.get('@estimatedB200').should('have.text', '$0.059');
     cy.get('@estimatedB200')
       .should('have.attr', 'href')
       .and('include', '/zh/inference?')
@@ -958,7 +953,7 @@ describe('Overview page', () => {
       cy.get('[data-testid="overview-model-scenario"]').should('have.text', AGENTX_LABEL_ZH);
       cy.get(
         '[data-testid="overview-pair-value"][data-hardware="b200"] [data-testid="overview-cost-evidence-link"]',
-      ).should('have.text', '$0.072');
+      ).should('have.text', '$0.064');
     });
     cy.contains('若某款芯片不支持 FP4 推测解码，则采用次优的可用配置。').should('exist');
 

packages/app/src/app/compare-per-dollar/[slug]/page-client.tsx

@@ -214,7 +214,7 @@ export default function ComparePerDollarPageClient({
                     className="underline hover:text-primary"
                     onClick={() => track('compare_per_dollar_tco_source_clicked', { slug })}
                   >
-                    SemiAnalysis Market August 2025 Pricing Surveys & AI Cloud TCO Model
+                    SemiAnalysis Market July 2026 Pricing Surveys & AI Cloud TCO Model
                   </a>
                   .
                 </p>

packages/app/src/components/calculator/FleetPlanner.tsx

@@ -399,7 +399,7 @@ export default function FleetPlanner({
             className="underline hover:text-foreground"
             href="https://semianalysis.com/ai-cloud-tco-model/"
           >
-            SemiAnalysis Market August 2025 Pricing Surveys & AI Cloud TCO Model
+            SemiAnalysis Market July 2026 Pricing Surveys & AI Cloud TCO Model
             <ExternalLinkIcon />
           </Link>
         </small>

packages/app/src/components/calculator/ThroughputCalculatorDisplay.tsx

@@ -1140,7 +1140,7 @@ function ThroughputCalculatorInner({ initialPercentile }: { initialPercentile: P
                                 className="underline hover:text-foreground"
                                 href="https://semianalysis.com/ai-cloud-tco-model/"
                               >
-                                SemiAnalysis Market August 2025 Pricing Surveys & AI Cloud TCO Model
+                                SemiAnalysis Market July 2026 Pricing Surveys & AI Cloud TCO Model
                                 <ExternalLinkIcon />
                               </Link>
                             </small>

packages/app/src/components/overview/overview-scorecard.tsx

@@ -26,7 +26,7 @@ export const OVERVIEW_STRINGS = {
     // The unit is dropped from the visible line but kept for screen readers.
     scopeAria: 'Hyperscaler cost per one million total tokens. Lower is better.',
     sourcePrefix: 'Source: InferenceX & ',
-    sourceLinkText: 'SemiAnalysis Market August 2025 AI Cloud TCO Model',
+    sourceLinkText: 'SemiAnalysis Market July 2026 AI Cloud TCO Model',
     tierNavLabel: 'SLO',
     tierUnit: 'tok/s/user',
     engineScopeNavLabel: 'Engine scope',
@@ -73,7 +73,7 @@ export const OVERVIEW_STRINGS = {
     scopeDirection: '↓ 越低越好',
     scopeAria: '超大规模云（hyperscaler）每百万总 token 成本，越低越好。',
     sourcePrefix: '来源：InferenceX 与 ',
-    sourceLinkText: 'SemiAnalysis Market August 2025 AI Cloud TCO Model',
+    sourceLinkText: 'SemiAnalysis Market July 2026 AI Cloud TCO Model',
     tierNavLabel: 'SLO',
     tierUnit: 'tok/s/用户',
     engineScopeNavLabel: '引擎范围',

packages/app/src/components/ui/chart-display-helpers.test.tsx

@@ -85,7 +85,7 @@ describe('MetricAssumptionNotes', () => {
 
     expect(getVisibleText()).toContain('TCO $/GPU/hr:');
     expect(getVisibleText()).toContain(
-      'SemiAnalysis Market August 2025 Pricing Surveys & AI Cloud TCO Model',
+      'SemiAnalysis Market July 2026 Pricing Surveys & AI Cloud TCO Model',
     );
     expect(getVisibleCaveatText()).toContain('calculate cost per decode GPU or per prefill GPU');
   });

packages/app/src/components/ui/chart-display-helpers.tsx

@@ -182,7 +182,7 @@ export function MetricAssumptionNotes({
         <>
           <MetricBadges label={costLabel} values={costValues} />
           <SourceLink href="https://semianalysis.com/ai-cloud-tco-model/" sourceLabel={sourceLabel}>
-            SemiAnalysis Market August 2025 Pricing Surveys & AI Cloud TCO Model
+            SemiAnalysis Market July 2026 Pricing Surveys & AI Cloud TCO Model
           </SourceLink>
         </>
       )}

packages/app/src/lib/constants.test.ts

@@ -188,6 +188,24 @@ describe('getHardwareConfig', () => {
       expect(entry.costr).toBeGreaterThanOrEqual(0);
     }
   });
+
+  it('uses the July 2026 TCO rates for modeled datacenter GPUs', () => {
+    const expectedRates = {
+      h100: [1.168, 1.5501205804741525, 1.78],
+      h200: [1.2174257813639555, 1.5918579041035947, 2.05],
+      b200: [1.7349236084834354, 2.0693175588620671, 2.6],
+      b300: [2.2550110908541448, 2.5151486614356386, 3],
+      gb200: [1.8648110244453284, 2.263552701012252, 2.6],
+      gb300: [2.313899859674561, 2.7890137161029926, 3.3],
+      mi300x: [0.9535220083742874, 1.1567197344221469, 1.3],
+      mi325x: [1.0998080408523334, 1.3234578915100057, 1.6],
+      mi355x: [1.4960710469526235, 2.089023971578409, 2.1],
+    } as const;
+
+    for (const [gpu, [costh, costn, costr]] of Object.entries(expectedRates)) {
+      expect(HW_REGISTRY[gpu]).toMatchObject({ costh, costn, costr });
+    }
+  });
 });
 
 // ===========================================================================
@@ -197,9 +215,9 @@ describe('getGpuSpecs', () => {
   it('returns specs for a base GPU key', () => {
     const specs = getGpuSpecs('h100');
     expect(specs.power).toBe(1.37);
-    expect(specs.costh).toBe(1.3);
-    expect(specs.costn).toBe(1.69);
-    expect(specs.costr).toBe(1.3);
+    expect(specs.costh).toBe(1.168);
+    expect(specs.costn).toBe(1.5501205804741525);
+    expect(specs.costr).toBe(1.78);
   });
 
   it('extracts base from compound key (e.g. h100_vllm)', () => {
@@ -210,7 +228,7 @@ describe('getGpuSpecs', () => {
   it('extracts base from dash-separated key (e.g. h200-dynamo-trt)', () => {
     const specs = getGpuSpecs('h200-dynamo-trt');
     expect(specs.power).toBe(1.37);
-    expect(specs.costh).toBe(1.41);
+    expect(specs.costh).toBe(1.2174257813639555);
   });
 
   it('returns zero specs for unknown GPU', () => {