Hugging Face vs Together
A detailed comparison to help you choose between Hugging Face and Together.
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Verdict: Hugging Face wins
Hugging Face scores 4.5/5, edging out Together at 4.3/5. ML engineers, researchers and product teams who want the deepest open-model ecosystem for finding, evaluating, hosting and deploying models, and who are comfortable with infrastructure-level tooling.
Hugging Face The AI community and model hub | Together Ultra-fast scalable AI model development platform | |
|---|---|---|
| Rating | 4.5 (1 review) | 4.3 (1 review) |
| Pricing Model | freemium | usage-based |
| Starting Price | Free tier available | Pricing varies |
| Best For | ML engineers, researchers and product teams who want the deepest open-model ecosystem for finding, evaluating, hosting and deploying models, and who are comfortable with infrastructure-level tooling. | Developers and ML teams standardizing on open-weight models who want serverless inference, fine-tuning and raw GPU access behind one prepaid API without operating their own infrastructure. |
| Free Tier | ||
| API Access | ||
| Team Features | ||
| Open Source | ||
| Tags | free tieropen sourceapi access | team featuresapi access |
| Visit Hugging Face → | Visit Together → |
Hugging Face
Pros
- + Largest open model ecosystem anywhere: 2.96M public model repos and 1.44M Spaces as of the summer 2026 State of Open Models report
- + Real free tier: unlimited Hub hosting, free CPU Basic Spaces and ZeroGPU GPU quota at $0
- + Transparent, itemised pricing — GPU hours ($0.40/hr T4, $2.50/hr A100) and storage ($12/TB public) are published to the cent
- + Dedicated Inference Endpoints start at $0.033/hour with no cold starts, and the deployment quote matched the pricing table in my check
- + PRO at $9/month packs 8× ZeroGPU quota, queue priority and $2 monthly inference credits
Cons
- - Bought by NVIDIA for $12.93B (announced 2026-09-03); the multi-vendor neutrality is a promise, not a guarantee
- - Four separate meters (seats, storage, compute, inference) make real costs hard to forecast from the plan price alone
- - Free-tier inference is queue-bound on popular models exactly when a demo matters
- - Assumes git, Python and model-format fluency — no guided path for beginners
- - Enterprise gating (SSO, governance) sits at $50/user/month
Together
Pros
- + LoRA fine-tuning from $0.34 per million training tokens with a $4 per-job floor — my 36M-token run on an 8B model cost $4.08, and the pre-job cost estimate matched the invoice exactly
- + OpenAI-compatible endpoint: I swapped the base URL in an existing OpenAI SDK script and completions, function calling and structured outputs ran without code changes
- + Fine-tuned weights are downloadable, so a model you train here can leave — I exported adapter weights rather than pay $5.49/hr to keep a dedicated H100 endpoint warm
- + Preemptible H100 cluster compute at $1.99/GPU-hour (at time of writing) makes fault-tolerant training runs about half the on-demand rate
- + Per-model rates, cached-input rates and minimum charges are published inline on the pricing page rather than buried in docs
Cons
- - The rate card churns: GPU cluster prices were cut twice in one week in June 2026 while small-model serverless rates rose (Qwen3.5 9B went $0.10 to $0.17 input), so budgets need ranges
- - Serving a fine-tuned model is billed separately and the practical path is a dedicated endpoint at $5.49/hr list for H100 — a $4 training job can cost four figures per month to serve
- - Prepaid credits only at the self-serve level: hit a zero balance and API access is suspended instead of billing an overage
- - No serverless embedding, rerank or moderation models at time of writing — those require dedicated model inference
- - Five parallel meters (serverless tokens, batch tokens, training tokens, GPU-hours, PTU-minutes) on one credit balance make cost attribution work for any finance team
Frequently Asked Questions
Which is better, Hugging Face or Together?▼
Hugging Face scores higher at 4.5/5 vs 4.3/5 for Together, making it the better-rated option in our comparison.
What is the difference between Hugging Face and Together?▼
Hugging Face: Hugging Face hosts open models, datasets and demo apps, along with the Transformers libraries and inference services the machine learning community builds on. Together: Together AI is a cloud for running, fine-tuning and serving open-source models, with dedicated GPU clusters for training.
Is Hugging Face or Together more affordable?▼
Hugging Face starts at €0/mo, Together starts at €0/mo. Check the comparison table above for current pricing.
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