RigBase vs YABANIN
A side-by-side comparison built from both listings. Blank cells mean the company has not given that detail; we never guess.
RigBase compared with YABANIN
| Detail | 
RigBase | 
YABANIN |
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| What it does | Local LLM hardware benchmarks with measured tokens per second from real home AI rigs
| Self-hosted AI infrastructure with measurable returns
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| Stage | Not given
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| Founded | Not given
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| Based in | Not given
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| Pricing model | Free
| Contact for pricing
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| Pricing | Not given
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| Key features | - 172 real home AI builds with measured performance data
- Performance metrics for 31 current LLM models
- Search by GPU, VRAM, budget and target model
- VRAM and KV cache calculator
- All results linked to original public sources
- Comparison guides and hardware recommendations
| - Model provider support through a single common gateway
- Usage attribution to teams, tasks, and agents
- Agent workflows in Scala for repositories and code
- Apache-2.0 open-source core with enterprise deployment option
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| What makes it different | - Real measured performance data from 172 actual home AI rigs, not marketing claims
- Every benchmark result linked to its original public source for verification
- Open data under Creative Commons license
- Practical guides for choosing AI hardware by budget and model
| - Full visibility into AI costs attributed to specific teams, tasks and agents
- Self-hosted deployment keeps data and models under company control
- Model agnostic with support for multiple providers through one gateway
- Structured four-step implementation path with clear ownership and baselines
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| Community votes | 0 | 0 |
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| DR (Domain Rating by Ahrefs) | Not checked yet ● no change since last check | Not checked yet ● no change since last check |
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| Trust Flow (Majestic) | 0 | 0 |
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| Citation Flow (Majestic) | 20 | 0 |
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| Referring domains (Majestic) | 2 | 0 |
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4 details filled in for both companies.
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