These tools competes with
UnslothvsTinker
2× faster, 70% less memory LoRA fine-tuning versus Managed distributed fine-tuning API from Thinking Machines Lab
Compare interactively in Explore →Choose Unsloth when…
- •You want the fastest OSS LoRA fine-tuning with minimal GPU memory
- •You're fine-tuning Llama, Mistral, or Gemma models
- •Memory constraints are the bottleneck in your training setup
Choose Tinker when…
- •You want a managed fine-tuning API instead of running training infra yourself
- •You need to fine-tune large open-weight MoE models without provisioning GPU clusters
- •You're comparing a hosted training loop against library-based options like Axolotl/Unsloth
Side-by-side comparison
Field
Unsloth
Tinker
Category
Fine-tuning
Fine-tuning
Type
Open Source
Commercial
Free Tier
✓ Yes
✗ No
Pricing Plans
Pro: $29/mo
Usage-based: Per-token, varies by model
GitHub Stars
⭐ 32,000
—
Health
●95 — Active
—
Unsloth
Dramatically speeds up LoRA and QLoRA fine-tuning by rewriting GPU kernels. Compatible with HuggingFace and works with Llama, Mistral, Gemma, and more. No accuracy loss.
Tinker
Hosted fine-tuning API (LoRA and full fine-tune) for open-weight models, including large MoE models, from Mira Murati's Thinking Machines Lab. A managed-training-loop alternative to library-based tools like Axolotl or Unsloth — usage-based per-token pricing that varies by model.
Shared Connections1 tool both integrate with
Only Unsloth (5)
AxolotlLlamaFactoryTorchtunevLLMTinker
Only Tinker (1)
Unsloth
Explore the full AI landscape
See how Unsloth and Tinker fit into the bigger picture — 256 tools, 553 relationships, all mapped.