Tools
AMD Enterprise AI Suite (SiloGen) vs Together AI
AMD Enterprise AI Suite (SiloGen) 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 inglese
In short
- Both: API, Runs models for you, Builds agents and workflows, Traces and evaluates
- Only AMD Enterprise AI Suite (SiloGen) states: Command line, Self-hosted, Search over your data
- Only Together AI states: Runs commands, Choice of models
AMD Enterprise AI Suite (SiloGen)
Open-source Kubernetes software stack for deploying, managing, and scaling AI workloads on AMD compute.
Plans
AMD Enterprise AI Suite
Free
- Modular open-source platform with four components: Solution Blueprints, Inference Microservices (AIMs), AI Workbench, Resource Manager
- Prebuilt optimized containers for AMD hardware, OpenAI-compatible APIs, open models
- Dynamic workspaces, fine-tuning pipelines, inference deployment
- Intelligent workload scheduling, quota management, telemetry for GPU utilization
- Kubernetes-native, enterprise security (SSO, RBAC), no vendor lock-in
- Accelerates from bare metal/cloud to production AI in minutes on AMD Instinct GPUs
Prices checked 2026-09-24 by web search.
Capabilities
- Command line — “workspaces and CLI reference workloads for the expert users.” source
- Self-hosted — “from bare metal compute to production-grade AI in minutes” source
- API — “Supports OpenAI-compatible APIs and open weight models, enabling rapid deployment without re-engineering.” source
- Runs models for you — “Prebuilt inference containers that bundle model, engine, and optimized configuration for AMD hardware.” source
- Builds agents and workflows — “such as agentic workflows, document summarization, RAG chatbots, and AI coding assistants.” source
- Search over your data — “such as agentic workflows, document summarization, RAG chatbots, and AI coding assistants.” source
- Traces and evaluates — “Observability and model management through real-time monitoring dashboards and life cycle management of models and keys.” source
Latest updates
- Version: 2.2.2 (2.2.2)
Fixed a first-boot race condition; added support for a custom Envoy Gateway HTTPS port.
- Version: 2.2.1 (2.2.1)
Fixed custom-model onboarding on Radeon clusters and inference metrics for AIMs on EPYC; improved ROCm version detection.
- Version: 2.2 (2.2)
AIMs run across Instinct GPUs, Radeon Pro GPUs, and EPYC CPUs; adds Envoy AI Gateway, SeaweedFS, model onboarding, and API access.
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.