Lamini
Enterprise LLM platform for fine-tuning, inference and deployment that reduces hallucinations up to 95% via Memory Tuning.
Our Verdict
Worth evaluating when hallucination is the actual blocker for your LLM rollout.
Pros
- Memory Tuning reduces hallucinations measurably
- Enterprise deployment options including on-prem
- Focused on fine-tuning over API tricks
Cons
- Expensive enterprise pricing model
- Memory Tuning is proprietary — lock-in risk
- Smaller community vs Together or Fireworks
Best for: Enterprises needing factual grounding on private data via fine-tuning
Not for: Teams that can get by with RAG on a managed LLM API
When to Use Lamini
Good fit if you need
- Fine-tuning LLMs on private enterprise data with exact accuracy
- Running deterministic model outputs for compliance-critical tasks
- Hosting private fine-tuned models on enterprise GPU infrastructure
- Eliminating hallucinations with memory-tuned Llama models
Lock-in Assessment
Medium 3/5
Lock-in Score 3/5
Pricing
Price wrong?Lamini Pricing
- Pricing Model
- usage
- Free Tier
- No
- Entry Price
- —
- Enterprise Available
- No
- Transparency Score
- —
Beta — estimates may differ from actual pricing
1,000
1001K10K100K1M
10,000
1K10K100K1M10M
Estimated Monthly Cost
$25
Estimated Annual Cost
$300
Estimates are approximate and may not reflect current pricing. Always check the official pricing page.
Project Health
F
Health Score
2.5k 153
Bus Factor
3
Last Commit
1.0 years
Release Freq
N/A
Open Issues
6
Issue Response
N/A
License
Apache-2.0
Last checked: 2026-04-21
Community Discussion
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