Together AI vs Unsloth
Agent-native side-by-side. Scores are curated estimates on a 0–10 scale. Lock-in: higher = worse. Prefer JTBD picks via /api/decide when choosing for a job.
| Dimension | Together AI | Unsloth |
|---|---|---|
| Overall | 8.2 | 8.5 |
| Capability fit | 8.5 | 8.8 |
| Price / performance | 9.0 | 9.2 |
| Latency / reliability | 8.0 | 7.5 |
| Developer & agent DX | 8.4 | 9.0 |
| Privacy / data retention | 7.2 | 8.5 |
| Lock-in risk (higher = worse) | 3.5 | 2.0 |
| Maturity / track record | 8.2 | 7.8 |
| Pricing | As of 2026-09-14: Open-model inference + fine-tune on one OpenAI-compatible API; competitive per-token rates (often ~$0.15–$0.90/MTok class depending on model). Strong for Llama/Qwen/DeepSeek families; Dedicated endpoint… | As of 2026-09-14 (unsloth.ai/pricing): Free OSS local training (4/16-bit LoRA, Llama/Mistral/Gemma). Pro/Enterprise = contact-sales speed/VRAM multi-GPU claims (2.5×–30× marketing). No Unsloth-hosted GPU rate card — pair… |
| Tagline | Best catalog breadth for OSS models. Watch minimums and lifetime spend gates before you design around a gated… | Depot OSS fine-tune default. Hosted LoRA → Predibase/Fireworks/Together; dead OpenPipe → do not resurrect… |
Together AI
Best catalog breadth for OSS models. Watch minimums and lifetime spend gates before you design around a gated model. Strengths: Huge open model catalog; Fine-tuning + inference under one roof; Competitive open-model pricing.
Strengths
- Huge open model catalog
- Fine-tuning + inference under one roof
- Competitive open-model pricing
Weaknesses
- Billing tiers/spend gates can surprise mid-build
- Quality variance across catalog models
- Support uneven at small spend
Unsloth
Depot OSS fine-tune default. Hosted LoRA → Predibase/Fireworks/Together; dead OpenPipe → do not resurrect. Run Unsloth on Modal/RunPod/HF Jobs. Strengths: Best-in-class OSS LoRA speed/VRAM efficiency; Huge community defaults; Works on rented GPUs.
Strengths
- Best-in-class OSS LoRA speed/VRAM efficiency
- Huge community defaults
- Works on rented GPUs
Weaknesses
- Not a hosted fine-tune SaaS
- Pro pricing opaque
- You still buy GPUs elsewhere
More pairs: anthropic-vs-openai · openai-vs-google-ai · groq-vs-fireworks · fireworks-vs-together · qdrant-vs-pinecone · pinecone-vs-supabase-pgvector · e2b-vs-modal · browserbase-vs-firecrawl