--- title: "AMD Helios | Aguasto" description: "Manufacturer reference for AMD Helios: MI455X / EPYC Venice / Pensando, rack system, with sourced specifications, variant boundaries and deployment considerations." canonical: "https://www.aguasto.com/gpus/helios" last-updated: "2026-10-12" --- # AMD Helios | Aguasto Canonical HTML: [AMD Helios](https://www.aguasto.com/gpus/helios) > Manufacturer reference for AMD Helios: MI455X / EPYC Venice / Pensando, rack system, with sourced specifications, variant boundaries and deployment considerations. [Aguasto](https://www.aguasto.com/) [GPU Library](https://www.aguasto.com/gpus) AMD Helios [Resources](https://www.aguasto.com/resources) [GPU Library](https://www.aguasto.com/gpus) [Model Index](https://www.aguasto.com/models) [Inference Stack](https://www.aguasto.com/inference-stack) [Learn](https://www.aguasto.com/learn) [Insights](https://www.aguasto.com/insights) [Research](https://www.aguasto.com/research) [Engineering tools](https://www.aguasto.com/tools) AMD / Rack-scale system ## AMD Helios AMD explicitly identifies Helios as a reference design rather than an AMD product for sale. The reviewed page expects OEM/ODM volume deployments in the second half of 2026. Original Aguasto conceptual illustration. Not manufacturer geometry, an operating Aguasto asset, or a measured benchmark. Aguasto Research documents third-party hardware, models and software. References do not represent Aguasto inventory, evaluated deployments or available inference services. ### Manufacturer specification reference Architecture MI455X / EPYC Venice / Pensando[AMD Helios rackscale reference design (external source)](https://www.amd.com/en/products/rackscale-solutions/helios.html) · [AMD Helios Rackscale Solution brochure (external source)](https://www.amd.com/content/dam/amd/en/documents/products/accelerators/instinct/amd-instinct-helios-blueprint-brochure.pdf) Category Complete rack-scale reference[AMD Helios rackscale reference design (external source)](https://www.amd.com/en/products/rackscale-solutions/helios.html) · [AMD Helios Rackscale Solution brochure (external source)](https://www.amd.com/content/dam/amd/en/documents/products/accelerators/instinct/amd-instinct-helios-blueprint-brochure.pdf) Accelerator memory 31,000 GBPublished rounded aggregate up to 31 TB GPU HBM converted to decimal GB; CPU memory excluded.[AMD Helios Rackscale Solution brochure (external source)](https://www.amd.com/content/dam/amd/en/documents/products/accelerators/instinct/amd-instinct-helios-blueprint-brochure.pdf) Memory type HBM4[AMD Helios rackscale reference design (external source)](https://www.amd.com/en/products/rackscale-solutions/helios.html) · [AMD Helios Rackscale Solution brochure (external source)](https://www.amd.com/content/dam/amd/en/documents/products/accelerators/instinct/amd-instinct-helios-blueprint-brochure.pdf) Memory bandwidth 1,670 TB/sBrochure's up to 1.67 PB/s aggregate GPU memory bandwidth converted to decimal TB/s; not scale-up interconnect bandwidth.[AMD Helios Rackscale Solution brochure (external source)](https://www.amd.com/content/dam/amd/en/documents/products/accelerators/instinct/amd-instinct-helios-blueprint-brochure.pdf) Power Not verified for this recordNo operating rack draw verified in reviewed Helios sources; power shelf description is not an operating-power measurement.[AMD Helios rackscale reference design (external source)](https://www.amd.com/en/products/rackscale-solutions/helios.html) · [AMD Helios Rackscale Solution brochure (external source)](https://www.amd.com/content/dam/amd/en/documents/products/accelerators/instinct/amd-instinct-helios-blueprint-brochure.pdf) Precision formats OCP-MXFP4, OCP-MXFP6, OCP-MXFP8[AMD Helios Rackscale Solution brochure (external source)](https://www.amd.com/content/dam/amd/en/documents/products/accelerators/instinct/amd-instinct-helios-blueprint-brochure.pdf) Cooling / integration Liquid-cooled reference rack.[AMD Helios rackscale reference design (external source)](https://www.amd.com/en/products/rackscale-solutions/helios.html) · [AMD Helios Rackscale Solution brochure (external source)](https://www.amd.com/content/dam/amd/en/documents/products/accelerators/instinct/amd-instinct-helios-blueprint-brochure.pdf) ### Configuration boundaries - Rounded manufacturer rack totals are retained, rather than presenting exact capacity derived from GPU count. - Bandwidth in this record is the brochure aggregate; the webpage separately quotes a per-GPU peak. Interconnect throughput is a different metric. - Manufacturer theoretical throughput is not a benchmark or a delivered token-rate claim. ### Published arithmetic throughput Manufacturer peaks, not Aguasto measurements or tokens per second **Specification** OCP-MXFP4 peak compute **Precision** OCP-MXFP4 **Published peak** 2.9 EFLOPS **Boundary & source** Whole reference rack; manufacturer peak theoretical specification[Manufacturer source ↗](https://www.amd.com/content/dam/amd/en/documents/products/accelerators/instinct/amd-instinct-helios-blueprint-brochure.pdf) **Specification** OCP-MXFP8 peak compute **Precision** OCP-MXFP8 **Published peak** 1.4 EFLOPS **Boundary & source** Whole reference rack; manufacturer peak theoretical specification[Manufacturer source ↗](https://www.amd.com/content/dam/amd/en/documents/products/accelerators/instinct/amd-instinct-helios-blueprint-brochure.pdf) ### Deployment considerations - An OEM implementation needs its own electrical, thermal, networking and acceptance specification. - Rack memory is distributed across GPUs; compare the reference rack only with other complete rack configurations. - Track OEM availability separately from AMD's reference-design publication. #### Software ecosystem ROCm. Confirm the exact model, runtime release, server integration and vendor support matrix before evaluating a deployment. ### Continue the research [AMD ROCm](https://www.aguasto.com/inference-stack/rocm) [vLLM](https://www.aguasto.com/inference-stack/vllm) [SGLang](https://www.aguasto.com/inference-stack/sglang) [Kubernetes GPU orchestration — NVIDIA device plugin](https://www.aguasto.com/inference-stack/kubernetes) [Model weights versus runtime memory](https://www.aguasto.com/learn/model-weights-and-runtime-memory) [Compare compatible hardware categories](https://www.aguasto.com/gpus/compare) [Why modular infrastructure?](https://www.aguasto.com/why-modular) ### Sources & verification Reference revision 1 · Reviewed October 12, 2026. Manufacturer claims and documentation are attributed; Aguasto has not run the cited products in production. - [AMD Helios rackscale reference design ↗](https://www.amd.com/en/products/rackscale-solutions/helios.html) 72 MI455X GPUs; Helios is a reference design not an AMD product for sale; Volume deployments expected in 2H 2026; ROCm ecosystem; Liquid-cooled Open Rack Wide architecture. Publication: date not stated in the reviewed source. Verified: 2026-10-12. - [AMD Helios Rackscale Solution brochure ↗](https://www.amd.com/content/dam/amd/en/documents/products/accelerators/instinct/amd-instinct-helios-blueprint-brochure.pdf) 72 GPUs in 18 four-GPU compute trays; Up to 31 TB HBM4; Up to 1.67 PB/s aggregate GPU memory bandwidth; Liquid cooling; ROCm; Up to 2.9 EFLOPS OCP MXFP4 and 1.4 EFLOPS OCP MXFP6/MXFP8. Publication: date not stated in the reviewed source. Verified: 2026-10-12. ### Reference journey [Compare hardware ↗](https://www.aguasto.com/gpus/compare) [Model Index ↗](https://www.aguasto.com/models) [Serving software ↗](https://www.aguasto.com/inference-stack) [OEM collaboration ↗](https://www.aguasto.com/partners) [Sources & verification ↓](https://www.aguasto.com/gpus/helios#sources) Research reference · No available Aguasto service ## Company navigation - [Home](https://www.aguasto.com/) - [Infrastructure](https://www.aguasto.com/infrastructure) - [GPU Cloud](https://www.aguasto.com/gpu-cloud) - [AI Inference](https://www.aguasto.com/ai-inference) - [Development & Investment](https://www.aguasto.com/development) - [Company](https://www.aguasto.com/company) - [Contact](https://www.aguasto.com/contact) - [Privacy](https://www.aguasto.com/privacy) - [Resources](https://www.aguasto.com/resources) - [GPU Library](https://www.aguasto.com/gpus) - [Model Index](https://www.aguasto.com/models) - [Inference Stack](https://www.aguasto.com/inference-stack) - [Learn](https://www.aguasto.com/learn) - [Insights](https://www.aguasto.com/insights) - [Research](https://www.aguasto.com/research) - [Industry cases](https://www.aguasto.com/research/cases) - [Why Modular](https://www.aguasto.com/why-modular) - [Partners](https://www.aguasto.com/partners) - [GPU comparison](https://www.aguasto.com/gpus/compare) - [Model comparison](https://www.aguasto.com/models/compare) - [Engineering tools](https://www.aguasto.com/tools) - [Development friction](https://www.aguasto.com/research/hyperscale-development-friction) - [NVIDIA H100 SXM](https://www.aguasto.com/gpus/h100) - [NVIDIA H200 SXM](https://www.aguasto.com/gpus/h200) - [NVIDIA B200 SXM](https://www.aguasto.com/gpus/b200) - [NVIDIA B300](https://www.aguasto.com/gpus/b300) - [NVIDIA GB200 NVL72](https://www.aguasto.com/gpus/gb200-nvl72) - [NVIDIA GB300 NVL72](https://www.aguasto.com/gpus/gb300-nvl72) - [NVIDIA Vera Rubin NVL72](https://www.aguasto.com/gpus/vera-rubin-nvl72) - [AMD Instinct MI300X](https://www.aguasto.com/gpus/mi300x) - [AMD Instinct MI325X](https://www.aguasto.com/gpus/mi325x) - [AMD Instinct MI355X](https://www.aguasto.com/gpus/mi355x) - [AMD Instinct MI455X](https://www.aguasto.com/gpus/mi455x) - [AMD Helios](https://www.aguasto.com/gpus/helios) - [GLM-4.5](https://www.aguasto.com/models/glm-4-5) - [Qwen3-235B-A22B](https://www.aguasto.com/models/qwen3-235b-a22b) - [DeepSeek-R1](https://www.aguasto.com/models/deepseek-r1) - [Llama 3.3 70B Instruct](https://www.aguasto.com/models/llama-3-3-70b-instruct) - [Gemma 3 27B IT](https://www.aguasto.com/models/gemma-3-27b-it) - [gpt-oss-120b](https://www.aguasto.com/models/gpt-oss-120b) - [Kimi-K2-Instruct](https://www.aguasto.com/models/kimi-k2-instruct) - [vLLM](https://www.aguasto.com/inference-stack/vllm) - [SGLang](https://www.aguasto.com/inference-stack/sglang) - [TensorRT-LLM](https://www.aguasto.com/inference-stack/tensorrt-llm) - [NVIDIA Dynamo](https://www.aguasto.com/inference-stack/dynamo) - [NVIDIA Triton Inference Server](https://www.aguasto.com/inference-stack/triton) - [AMD ROCm](https://www.aguasto.com/inference-stack/rocm) - [Ray Serve](https://www.aguasto.com/inference-stack/ray-serve) - [Kubernetes GPU orchestration — NVIDIA device plugin](https://www.aguasto.com/inference-stack/kubernetes) - [Model weights are only the beginning of the memory budget](https://www.aguasto.com/learn/model-weights-and-runtime-memory) - [Why tokens per second is not enough to benchmark inference](https://www.aguasto.com/research/inference-benchmark-methodology) - [Prefill, decode and the cost of separating them](https://www.aguasto.com/learn/prefill-decode-and-disaggregated-serving) - [Choosing between vLLM, SGLang and TensorRT-LLM](https://www.aguasto.com/learn/choosing-an-inference-serving-framework) - [From Power to Inference—Building a Distributed AI Compute Network](https://www.aguasto.com/learn/from-power-to-inference) - [Dedicated compute and shared inference: compare the whole workload](https://www.aguasto.com/insights/dedicated-and-shared-inference-economics) - [Distributed inference reliability begins with the failure boundary](https://www.aguasto.com/learn/distributed-inference-reliability) - [Core Scientific: reading contracted, energized and billed capacity](https://www.aguasto.com/research/cases/core-scientific-capacity-disclosures) - [Why Modular AI Infrastructure Matters Now](https://www.aguasto.com/research/why-modular-ai-infrastructure-matters-now) - [Official LinkedIn](https://www.linkedin.com/company/aguasto) This is a generated representation of the public HTML page. 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