Gradient
Gradient — Fine-tuning and deployment platform for LLMs with a simple API and managed GPU infrastructure.
Our Verdict
A pragmatic middle ground for teams who want fine-tuning without running their own GPUs.
Pros
- Simple API for fine-tuning open LLMs
- Managed GPU infra removes DevOps overhead
- Decent pricing for small fine-tune jobs
Cons
- Smaller model catalog than Together or Fireworks
- Limited customization beyond standard LoRA flows
- Roadmap uncertainty after market consolidation
Best for: Product teams fine-tuning open LLMs without dedicated ML infra staff
Not for: Research labs needing cutting-edge models or deep training control
When to Use Gradient
Good fit if you need
- Fine-tuning open LLMs on proprietary data through a managed API
- Deploying private fine-tuned models without managing GPUs
- Running domain adaptation on Llama-based models via REST API
- Combining fine-tuning with RAG for enterprise knowledge tasks
Lock-in Assessment
Low 4/5
Lock-in Score 4/5
Pricing
Price wrong?Gradient 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.
Community Discussion
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