Tools
Hugging Face vs Together AI
Hugging Face or Together AI? Their plans monthly and yearly, the capabilities their makers state, security and latest updates, side by side — read from the makers' own pages.
In short
- Both: Choice of models, API, Runs models for you, Builds agents and workflows
- Only Hugging Face states: Official SDKs
- Only Together AI states: Runs commands, Traces and evaluates
Hugging Face
Hugging Face hosts AI models, datasets, apps, libraries, and tools for building, sharing, and deploying machine-learning systems.
Plans
PRO Account
- $9 /month
- 10× private storage capacity
- 2× public storage capacity
- 20× included inference credits
- 8× ZeroGPU quota and highest queue priority
- Host ZeroGPU, Gradio & Docker Spaces
- Spaces Dev Mode
Team
- $20 /month per user
- SSO support (SAML & OIDC)
- Data location control with Storage Regions
- Detailed action reviews with Audit Logs
- Granular access control via Resource Groups
- Repository usage Analytics
- Advanced auth policies and repository visibility controls
Enterprise
- $50 /month per user
- + All benefits from the Team plan
- Highest storage, bandwidth, and API rate limits
- Automated user management with SCIM provisioning
- Advanced security and access controls
- Managed billing with annual commitments
- Legal and Compliance processes
Prices checked 2026-09-24 on the maker’s page.
Capabilities
- Choice of models — “Browse 2M+ models” source
- API — “Access 45,000+ models from leading AI providers through a single, unified API with no service fees.” source
- Official SDKs — “Python client to interact with the Hugging Face Hub” source
- Runs models for you — “Deploy any ML model on dedicated and autoscaling infrastructure, right from the HF Hub.” source
- Builds agents and workflows — “Smol library to build great agents in Python” source
Latest updates
- Transformers now runs llama.cpp quants
Transformers now runs llama.cpp quants.
- tokenizers v1: encode, decode and scaling, measured (v1)
tokenizers v1 covers encode, decode, and scaling.
- NeoMME: an efficient Multimodal-native and Multilingual Encoder
NeoMME is a multimodal-native and multilingual encoder.
Together AI
Together AI provides APIs and infrastructure for running, fine-tuning, and training open AI models.
Plans
Serverless Inference
- MiniMax M3 — $0.30 per 1M tokens (Input)
- MiniMax M3 — $1.20 per 1M tokens (output)
- Kimi K3 — $3.00 per 1M tokens (Input)
- Kimi K3 — $15.00 per 1M tokens (output)
- GLM-5.3-Flash — $0.15 per 1M tokens (Input)
- GLM-5.3-Flash — $0.50 per 1M tokens (output)
- GPT Image 2 — $0.053 per image
- Wan 2.6 Image — $0.03 per image
- ByteDance Seedance 2.5 — $0.115 per video
- ByteDance Seedance 2.0 — $0.16 per video
- NVIDIA Nemotron 3 ASR Streaming 0.6B — $0.0015 per audio minute
- Whisper Large v3 — $0.0015 per audio minute
- High-performance inference as APIs
- Prices vary by model and task; the page also lists batch API prices.
Dedicated Inference — NVIDIA HGX H100
- $5.49 per gpu per hour
- $3.99 per gpu per hour
- Single-tenant GPU instances
- Guaranteed performance (no sharing)
- Support for custom models
- Autoscaling & traffic spike handling
Dedicated Inference — NVIDIA HGX B200
- $8.99 per gpu per hour
- Single-tenant GPU instances
- Guaranteed performance (no sharing)
- Support for custom models
- Autoscaling & traffic spike handling
Dedicated Inference — other hardware
Price on request
- NVIDIA HGX H200, NVIDIA HGX B300, NVIDIA GB200 NVL72, and NVIDIA GB300 NVL72
- Contact sales
GPU Clusters — On-demand
- NVIDIA HGX B200 $8.19 per GPU per hour
- NVIDIA HGX B300 $9.99 per GPU per hour
- NVIDIA HGX H100 $3.99 per GPU per hour
- NVIDIA HGX H200 $5.99 per GPU per hour
- Pay-as-you-go GPU capacity on an hourly basis
GPU Clusters — Preemptible and reserved
- NVIDIA HGX H100 Preemptible Compute $1.99 per GPU per hour
- NVIDIA HGX H100 ON-Demand $3.99 per GPU per hour
- NVIDIA HGX H100 7-30 days $3.69 per GPU per hour
- NVIDIA HGX H100 31-90 days $3.45 per GPU per hour
- NVIDIA HGX H100 91-180 days $3.19 per GPU per hour
- On-demand hourly rates and reserved capacity
- Reservation terms shown as 7-30, 31-90, and 91-180 days, and 181+ days
Code Sandbox
- Per vCPU $0.0446 per hour
- Per GiB RAM $0.0149 per hour
- Customize a deployment of VM sandboxes for large development environments
Code Interpreter
- Session (60 minutes) $0.03 per session
- Execute LLM-generated code securely using the API
Managed Storage
- Shared Filesystem $0.16 GiB/month
- High-bandwidth, parallel filesystem colocated with your compute
Prices checked 2026-09-25 on the maker’s page.
Capabilities
- Runs commands — “await client.commands.run("npm install && npm run build")” source
- Choice of models — “Scale to 30 billion tokens per model with any serverless model or private deployment.” source
- API — “High-performance inference as APIs” source
- Runs models for you — “The fastest way to run open-source models on demand.” source
- Builds agents and workflows — “Build voice agents for production” source
- Traces and evaluates — “Measure model quality” source
Latest updates
- How to train your own Jev for $17
Launched the together/Tev1-4B-experimental classifier on Together’s serverless platform.
- Canary rollouts: upgrade models in production without downtime
Dedicated inference supports staged traffic ramps, metric gates, and automatic rollback for model upgrades.
- Together AI expands fine-tuning service with more models, live metrics, and finer controls
Together Fine-Tuning added more models, live experiment tracking, Expert LoRA, early stopping, dataset previews, and pre-flight validation.