⏱ Capsule Public Vibe Design
The Ghost Dashboard
Ezarwebmaster· Jul 10, 2026
Brief
# Brief — The Ghost Dashboard (Vibe Design)
## Rationale
This capsule tests aesthetic judgment rather than technical correctness. The prompt is deliberately vague on layout, palette, and composition — it only fixes the data points and the domain (fintech). The goal is to see whether a model makes deliberate, coherent design decisions or defaults to generic, unstyled, "bootstrap-y" output.
Unlike prior capsules (Ray Marching, Silent Regression), there's no single hidden bug to find. Instead, GT criteria are built around observable, low-ambiguity visual signals that a non-designer can judge from a screenshot: does it look intentional, is it legible, is it coherent. This keeps scoring objective despite the subjective subject matter.
## Expected model spread
- Frontier models with strong front-end training data (Claude, GPT, Gemini top tier) should produce a genuinely styled, cohesive dashboard with a real color system and considered spacing.
- Mid-tier models likely default to a generic card-grid layout with default chart library colors (Chart.js default rainbow palette) and inconsistent spacing.
- Weaker/smaller models risk one of: broken chart rendering (CDN script fails silently, blank canvas), Lorem-ipsum-style placeholder content instead of realistic fintech labels, or literal template-cloning of a well-known dashboard (Stripe, Linear) that isn't actually adapted to "Fenwick."
## Known implementation risks / cheats to watch for
- **CDN failure**: Chart.js or similar loaded from a CDN that doesn't resolve in the render sandbox — chart area renders blank. This must be treated as a hard fail on GT6, not a partial, since it's a broken deliverable regardless of surrounding design quality.
- **Palette cheat via screenshot bias**: a model could use a single flashy color (e.g., neon gradient hero header) that looks good in isolation but clashes with the rest of the page. Judge palette coherence across the *whole* page, not just the top fold.
- **Generic default detection**: watch for unmodified Bootstrap/Tailwind default component styling (default blue buttons, default table borders) sitting next to custom-styled sections — signals low design effort even if some parts look intentional.
- **Data realism cheat**: some models may reuse placeholder values like "Lorem ipsum" or "$XXXX" instead of committing to plausible numbers — this isn't a visual bug but reflects low effort and should count against GT3.
- **Exact clone risk**: a memorized close copy of a known real dashboard product (not just "inspired by" a style) should be flagged in notes even if it scores well, since it demonstrates memorization rather than design generation.
## Ground Truth checklist
Render each submission in headless Chromium at standard desktop viewport (1440×900) and capture a full-page screenshot before scoring.
- **GT1 — Visual hierarchy**: Is there one clear focal point (e.g., total balance or a headline metric) that draws the eye first, with everything else clearly secondary?
- **GT2 — Palette coherence**: Does the page use a limited, deliberate color palette (roughly 2–4 core colors plus neutrals), with a consistent accent color used purposefully rather than a rainbow of unrelated colors?
- **GT3 — Content realism**: Are the data labels and values plausible for a real fintech dashboard (real-sounding category names, sane dollar amounts), not placeholder/lorem-ipsum content?
- **GT4 — Layout & spacing consistency**: Is spacing/padding consistent across cards and sections, with proper alignment on a grid (no overlapping elements, no ragged edges)?
- **GT5 — Typography hierarchy**: Is there a clear, consistent distinction between headers, metric values, and body/labels (size and/or weight), rather than uniform text throughout?
- **GT6 — Functional chart**: Does at least one chart/graph render correctly and legibly (not blank, not broken, not illegible due to overlapping labels)?
- **GT7 — Generic-template avoidance**: Does the page avoid leaving visible, unstyled default component styling (raw Bootstrap buttons/tables) next to custom-styled sections?
- **GT8 — Domain trustworthiness (bonus, not required for pass)**: Does the overall look read as "trustworthy financial product" rather than a generic admin panel or consumer app? Note qualitatively, don't require for tier decisions.
## Tiers
- **PASS**: GT1, GT2, GT4, GT5, GT6 all met, plus at least one of GT3/GT7.
- **PARTIAL**: GT6 met (chart functional) but two or more of GT1/GT2/GT4/GT5 fail, OR GT6 fails but everything else is strong (broken chart pulling down an otherwise good design).
- **FAIL**: GT6 fails (broken/blank chart) AND two or more of GT1/GT2/GT4/GT5 also fail, or the output is not a working single HTML file.
## Scoring checklist block (per run)
```
Model: [name]
GT1 Visual hierarchy: [PASS/FAIL]
GT2 Palette coherence: [PASS/FAIL]
GT3 Content realism: [PASS/FAIL]
GT4 Layout/spacing: [PASS/FAIL]
GT5 Typography hierarchy: [PASS/FAIL]
GT6 Functional chart: [PASS/FAIL]
GT7 Generic-template avoid.: [PASS/FAIL]
GT8 Trustworthiness (bonus): [note only]
Tier: [PASS/PARTIAL/FAIL]
Notes: [cheats detected, clone risk, CDN failure, etc.]
```
Locked Reference Prompt
IMMUTABLEScientific timeline lock active
Design and build a single-page analytics dashboard for "Fenwick", a fintech startup that helps small businesses track cash flow and spending.
Requirements:
Deliver as a single self-contained HTML file (inline CSS and JS; you may use CDN links for libraries such as Chart.js or similar).
The dashboard should give a business owner an at-a-glance view of their financial health.
Include at least the following data points, with realistic sample values you invent: total balance, monthly revenue, monthly expenses, a spending breakdown by category, and a trend over the last 6 months.
The dashboard must include at least one chart or graph.
Design it to feel modern and trustworthy, appropriate for a financial product.
You have full creative freedom over layout, color palette, typography, and how information is organized. There is no wireframe to follow.
Do not include any explanatory text about your design choices — output only the working HTML file.
Add a Benchmark Run
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Timeline (25 runs)
Run Activity
25 runs in the last 6 months
Jan
Feb
Mar
Apr
May
Jun
Jul
LessMore
Cost vs Speed
size = output tokens · top-left is best
size = tokens
value frontier — no model is faster & cheaper Capsule Stats
Runs
25
Total cost
$2.3383
Tokens
208k
Avg latency
5.52 s
Models
25
Web Searches
0
Fastest
openai/gpt-4.1-2025-04-14449 ms
openai/gpt-4.1-2025-04-14449 ms Cheapest
deepseek/deepseek-v4-flash-20260423$0.0013
deepseek/deepseek-v4-flash-20260423$0.0013 Top provider
OpenAI×10
OpenAI×10 15k reasoning last yesterday
Tip: Select 2 or more runs via their "Compare" buttons — or filter by company below and compare them all at once — then open the Compare Studio: verdicts, benchmark bars, charts, side-by-side reading and response diff.
⏱
Benchmark Run — Jul 10, 2026 Latest

xAI (Grok)grok-4.3-20260430
Extended
stop
Latency
32.66 s
client → response
Input Tokens
375
prompt tokens
Output
4,161
generated
Total Tokens
4,536
in + out
Billed Cost
$0.0107
OR Credits
Reasoning
592
thinking tokens
Model Output
grok-4.3-20260430 — Canvas
Researcher Notes
⏱
Benchmark Run — Jul 10, 2026

Anthropicclaude-5-fable-20260609
Extended
stop
Latency
77.59 s
client → response
Input Tokens
299
prompt tokens
Output
8,171
generated
Total Tokens
8,470
in + out
Billed Cost
$0.4115
OR Credits
Reasoning
87
thinking tokens
Model Output
claude-5-fable-20260609 — Canvas
Researcher Notes
⏱
Benchmark Run — Jul 10, 2026
Z Aiglm-5.2-20260616
Extended
stop
Latency
1.99 s
client → response
Input Tokens
199
prompt tokens
Output
10,679
generated
Total Tokens
10,878
in + out
Billed Cost
$0.0142
OR Credits
Reasoning
489
thinking tokens
Model Output
glm-5.2-20260616 — Canvas
Researcher Notes
⏱
Benchmark Run — Jul 10, 2026

NVIDIAnemotron-3-ultra-550b-a55b-20260604
Extended
stop
Latency
636 ms
client → response
Input Tokens
208
prompt tokens
Output
8,476
generated
Total Tokens
8,684
in + out
Billed Cost
$0.0187
OR Credits
Reasoning
207
thinking tokens
Model Output
nemotron-3-ultra-550b-a55b-20260604 — Canvas
Researcher Notes
⏱
Benchmark Run — Jul 10, 2026

Qwen (Alibaba)qwen3.7-max-20260520
Extended
stop
Latency
877 ms
client → response
Input Tokens
205
prompt tokens
Output
11,722
generated
Total Tokens
11,927
in + out
Billed Cost
$0.0442
OR Credits
Reasoning
312
thinking tokens
Model Output
qwen3.7-max-20260520 — Canvas
Researcher Notes
⏱
Benchmark Run — Jul 10, 2026

MiniMaxminimax-m3-20260531
Extended
stop
Latency
1.17 s
client → response
Input Tokens
311
prompt tokens
Output
9,208
generated
Total Tokens
9,519
in + out
Billed Cost
$0.0111
OR Credits
Reasoning
421
thinking tokens
Model Output
minimax-m3-20260531 — Canvas
Researcher Notes
⏱
Benchmark Run — Jul 10, 2026

Moonshot AI (Kimi)kimi-k2.7-code-20260612
Extended
stop
Latency
613 ms
client → response
Input Tokens
194
prompt tokens
Output
5,200
generated
Total Tokens
5,394
in + out
Billed Cost
$0.0197
OR Credits
Reasoning
352
thinking tokens
Model Output
kimi-k2.7-code-20260612 — Canvas
Researcher Notes
⏱
Benchmark Run — Jul 10, 2026

Tencent (Hunyuan)hy3-20260706
Extended
stop
Latency
2.85 s
client → response
Input Tokens
204
prompt tokens
Output
2,252
generated
Total Tokens
2,456
in + out
Billed Cost
$0.0013
OR Credits
Reasoning
—
thinking tokens
Model Output
hy3-20260706 — Canvas
Researcher Notes
⏱
Benchmark Run — Jul 10, 2026

Google DeepMindgemini-3.1-pro-preview-20260219
Extended
stop
Latency
3.53 s
client → response
Input Tokens
197
prompt tokens
Output
8,869
generated
Total Tokens
9,066
in + out
Billed Cost
$0.1068
OR Credits
Reasoning
2,256
thinking tokens
Model Output
gemini-3.1-pro-preview-20260219 — Canvas
Researcher Notes
⏱
Benchmark Run — Jul 10, 2026

Anthropicclaude-sonnet-5-20260630
Extended
stop
Latency
1.76 s
client → response
Input Tokens
299
prompt tokens
Output
13,569
generated
Total Tokens
13,868
in + out
Billed Cost
$0.1363
OR Credits
Reasoning
—
thinking tokens
Model Output
claude-sonnet-5-20260630 — Canvas
Researcher Notes
⏱
Benchmark Run — Jul 10, 2026

Anthropicclaude-4.8-opus-20260528
Extended
stop
Latency
1.74 s
client → response
Input Tokens
299
prompt tokens
Output
5,970
generated
Total Tokens
6,269
in + out
Billed Cost
$0.1507
OR Credits
Reasoning
—
thinking tokens
Model Output
claude-4.8-opus-20260528 — Canvas
Researcher Notes
⏱
Benchmark Run — Jul 10, 2026

Anthropicclaude-4.5-haiku-20251001
Extended
stop
Latency
1.29 s
client → response
Input Tokens
213
prompt tokens
Output
5,073
generated
Total Tokens
5,286
in + out
Billed Cost
$0.0256
OR Credits
Reasoning
—
thinking tokens
Model Output
claude-4.5-haiku-20251001 — Canvas
Researcher Notes
⏱
Benchmark Run — Jul 10, 2026

OpenAIgpt-5-2025-08-07
Extended
stop
Latency
2.73 s
client → response
Input Tokens
190
prompt tokens
Output
8,437
generated
Total Tokens
8,627
in + out
Billed Cost
$0.0846
OR Credits
Reasoning
2,560
thinking tokens
Model Output
gpt-5-2025-08-07 — Canvas
Researcher Notes
⏱
Benchmark Run — Jul 10, 2026

OpenAIgpt-5.1-20251113
Extended
stop
Latency
595 ms
client → response
Input Tokens
190
prompt tokens
Output
11,043
generated
Total Tokens
11,233
in + out
Billed Cost
$0.1107
OR Credits
Reasoning
—
thinking tokens
Model Output
gpt-5.1-20251113 — Canvas
Researcher Notes
⏱
Benchmark Run — Jul 10, 2026

OpenAIgpt-5.2-20251211
Extended
stop
Latency
893 ms
client → response
Input Tokens
190
prompt tokens
Output
9,617
generated
Total Tokens
9,807
in + out
Billed Cost
$0.1350
OR Credits
Reasoning
—
thinking tokens
Model Output
gpt-5.2-20251211 — Canvas
Researcher Notes
⏱
Benchmark Run — Jul 10, 2026

OpenAIgpt-5.5-20260423
Extended
stop
Latency
791 ms
client → response
Input Tokens
190
prompt tokens
Output
9,278
generated
Total Tokens
9,468
in + out
Billed Cost
$0.2793
OR Credits
Reasoning
49
thinking tokens
Model Output
gpt-5.5-20260423 — Canvas
Researcher Notes
⏱
Benchmark Run — Jul 10, 2026

OpenAIgpt-4.1-2025-04-14
Extended
stop
Latency
449 ms
client → response
Input Tokens
191
prompt tokens
Output
2,996
generated
Total Tokens
3,187
in + out
Billed Cost
$0.0244
OR Credits
Reasoning
—
thinking tokens
Model Output
gpt-4.1-2025-04-14 — Canvas
Researcher Notes
⏱
Benchmark Run — Jul 10, 2026

OpenAIgpt-5.3-codex-20260224
Extended
stop
Latency
515 ms
client → response
Input Tokens
190
prompt tokens
Output
4,149
generated
Total Tokens
4,339
in + out
Billed Cost
$0.0584
OR Credits
Reasoning
301
thinking tokens
Model Output
gpt-5.3-codex-20260224 — Canvas
Researcher Notes
⏱
Benchmark Run — Jul 10, 2026

OpenAIgpt-5.4-20260305
Extended
stop
Latency
660 ms
client → response
Input Tokens
190
prompt tokens
Output
7,311
generated
Total Tokens
7,501
in + out
Billed Cost
$0.1101
OR Credits
Reasoning
—
thinking tokens
Model Output
gpt-5.4-20260305 — Canvas
Researcher Notes
⏱
Benchmark Run — Jul 10, 2026

OpenAIgpt-5.6-sol-20260709
Extended
stop
Latency
598 ms
client → response
Input Tokens
190
prompt tokens
Output
9,045
generated
Total Tokens
9,235
in + out
Billed Cost
$0.2723
OR Credits
Reasoning
197
thinking tokens
Model Output
gpt-5.6-sol-20260709 — Canvas
Researcher Notes
⏱
Benchmark Run — Jul 10, 2026

OpenAIgpt-5.6-terra-20260709
Extended
stop
Latency
536 ms
client → response
Input Tokens
190
prompt tokens
Output
7,845
generated
Total Tokens
8,035
in + out
Billed Cost
$0.1182
OR Credits
Reasoning
31
thinking tokens
Model Output
gpt-5.6-terra-20260709 — Canvas
Researcher Notes
⏱
Benchmark Run — Jul 10, 2026

OpenAIgpt-5.6-luna-20260709
Extended
stop
Latency
737 ms
client → response
Input Tokens
190
prompt tokens
Output
7,523
generated
Total Tokens
7,713
in + out
Billed Cost
$0.0453
OR Credits
Reasoning
73
thinking tokens
Model Output
gpt-5.6-luna-20260709 — Canvas
Researcher Notes
⏱
Benchmark Run — Jul 10, 2026

DeepSeekdeepseek-v4-pro-20260423
Extended
stop
Latency
613 ms
client → response
Input Tokens
193
prompt tokens
Output
13,123
generated
Total Tokens
13,316
in + out
Billed Cost
$0.0197
OR Credits
Reasoning
4,949
thinking tokens
Model Output
deepseek-v4-pro-20260423 — Canvas
Researcher Notes
⏱
Benchmark Run — Jul 10, 2026

Google DeepMindgemini-3.5-flash-20260519
Extended
stop
Effort: Medium Latency
1.53 s
client → response
Input Tokens
197
prompt tokens
Output
14,200
generated
Total Tokens
14,397
in + out
Billed Cost
$0.1281
OR Credits
Reasoning
1,827
thinking tokens
Model Output
gemini-3.5-flash-20260519 — Canvas
Researcher Notes
⏱
Benchmark Run — Jul 10, 2026

DeepSeekdeepseek-v4-flash-20260423
Extended
stop
Latency
609 ms
client → response
Input Tokens
193
prompt tokens
Output
4,556
generated
Total Tokens
4,749
in + out
Billed Cost
$0.0013
OR Credits
Reasoning
—
thinking tokens
Model Output
deepseek-v4-flash-20260423 — Canvas