AMD vs Together AI
Relationship
AMD Ryzen AI Software and Together Batch Inference both serve buyers who need to serve a model in production; smaller scale (private).
Assembled from the recorded fields for this pair, not hand-checked. The comparison below is read from each company’s own profile.
4 of 9 capabilities — Shares GPU cloud, model hosting, model inference and 1 more.
Ludbee capability tags · from the product recordsShared product type — Both ship infrastructure service.
Ludbee product recordsSmaller scale — Together AI: $8.3B valuation, against AMD's $785.1B market cap.
Ludbee scale figures · valuation, market cap or revenue estimateAligned comparison
Capability overlap
Shared · 4
Not verified for Together AI · 5
Recorded for AMD. Together AI’s product records say nothing either way — a missing record is not a missing capability.
Together AI has no capability AMD lacks, among the 4 recorded here.
Products, side by side
Algorithmic pairing — assembled from recorded fields, not hand-checked
AMD
Infrastructure service
An on-demand cloud service giving developers browser and API access to AMD Instinct MI300X GPU instances for AI, ML and HPC workloads.
Together AI
Infrastructure service
Dedicated, reserved GPU containers for model inference with guaranteed performance, billed per GPU-hour.
Reserved NVIDIA GPU clusters for training and large-scale inference.
No counterpart
AMD sells these in a stack layer with no product recorded for Together AI yet — nothing on the other side to compare them against.
Platform
An open-source reference stack for running enterprise AI workloads at scale on AMD compute: open-source AI frameworks and generative models connected to an enterprise-ready Kubernetes platform, with AMD Inference Microservices — prebuilt inference containers bundling model, engine and optimised configuration for AMD hardware.
Open-source GPU computing stack of compilers, runtimes and libraries for running AI and HPC workloads on AMD hardware.
A development stack of compiler, runtime and tools for porting pretrained models onto the NPU and integrated GPU of Ryzen AI processors.
An open-source AI inference development stack of compiler, optimised NPU IP and runtime for deploying deep-learning models on AMD adaptive SoCs, FPGAs and Alveo cards.
Hardware
A rack-scale AI system combining 72 Instinct MI455X GPUs with EPYC CPUs and Pensando networking for frontier-model training and large-scale inference.
Data-centre GPU accelerators for training and serving models, sold in OEM servers and rack systems.
System-on-module family for deploying edge and physical AI, with production SOMs and partner-validated carrier systems.
AI NIC family (Pollara 400 at 400 Gbps, Vulcano 800 at 800 Gbps Ethernet) for scale-out inter-GPU communication in AI training and inference clusters, built on the Ultra Ethernet Consortium specification.
Data processing unit family (Salina, Giglio) offloading networking, security and storage services from host CPUs in AI data centres, programmable via the P4-based Pensando software stack.
Second-generation Versal AI Edge adaptive SoC family for embedded AI preprocessing, inference and postprocessing.
Together AI sells these in a stack layer with no product recorded for AMD yet — nothing on the other side to compare them against.
API service
Asynchronous bulk inference for workloads that do not need a real-time response, priced below Together's serverless rate.
A managed service for fine-tuning open-source models on a customer's own data and serving the result on Together's infrastructure.
Developer tool
Custom model training service covering supervised fine-tuning and direct preference optimization, billed per token.
Model API
Hosted API serving open-weight text, image and audio models, billed per token.