Products/AI Metrics and Evaluation/QuickCompare by Trismik

QuickCompare by Trismik

Compare LLMs on your data, measure, and pick the best.

AI Metrics and Evaluation8 peopleReal evaluations on your own prompts and use case50+ models compared in a single workflowClear trade-offs between quality, cost, and speedSide-by-side comparison of performance, cost, and speedSlice-level breakdown showing where models actually fail on harder examplesNo manual scripts or ad-hoc testing requiredZiggy AI Scientist assistant for no-code setup and running comparisons
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Our Take

QuickCompare is the tool that makes you wonder why everyone isn't doing this already — most teams just grab GPT-4 and overpay for inference when cheaper models might actually handle their specific use case better, and this lets you test 50+ models against your own data instead of generic benchmarks. The slice-level breakdown showing exactly where cheaper models choke on harder examples is genuinely useful, way more actionable than aggregate scores. That said, $10 in free credits won't get you far if you're running comprehensive comparisons, and I'm skeptical how much value Ziggy the AI Scientist assistant actually adds versus just running the comparison yourself. The early traction is solid (279 users, Day Rank #3), but this is still in "prove it works at scale" territory.

Upload your data, compare 50+ models, and see quality, cost, and speed side by side. Pick the best model for your use case without manual testing or generic benchmarks.

Problem It Solves
Teams shipping LLM features making model decisions with surprisingly little evidence, often defaulting to the biggest or most familiar models, relying on public benchmarks or manual testing. Results in spending far more than necessary on inference without getting the best result for their use case.
Target Customer
Teams building with LLMs, especially those building AI products at scale who need to make data-driven model decisions.
Use Cases
Finding the right LLM for your specific use case, Cutting inference cost without sacrificing output quality, Identifying where cheaper models match or outperform expensive defaults, Tracking model performance drift over time, Evaluating which model performs best on your prompts and tasks
Pricing Details
Get $10 free credits
Free Tier
$10 free credits
Differentiator
Real evaluations on your own data rather than generic benchmarks; slice-level breakdown showing where models actually fail on harder examples (most eval tools stop at aggregate metrics)
Why Now
With LLMs being used at scale, model choice has real business impact on inference bills, product experience, and speed to market. Teams need data-driven decisions instead of guesswork.
Traction
User Count: 279 · Notable Metrics: 218 upvotes, Day Rank #3

Key Facts

Category
AI Metrics and Evaluation
Team Size
8 people
Pricing
Free
Discovered via
product-hunt

The people behind QuickCompare by Trismik

A

Alice Pernthaller

profile
E

Esma Balkır

profile
K

Kieran Vail

profile
M

Marco Basaldella

profile
M

Mateusz Biskup

profile
N

Nigel Collier

profile
R

Rebekka Mikkola

profile
V

Vincenzo Carlino

profile

Links

WebsiteSource: product-hunt

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