512 × AMD Instinct MI355X 288GB HBM3e

Tested system

Processor: AMD EPYC 9575F
Graphics: AMD Instinct MI355X 288GB HBM3e
Accelerator count: 512
Nodes: 64

Recorded results

Only the same benchmark, version, workload, scenario and unit share a row. Missing results are not zero. System results include the full submitted hardware and software configuration.

MLPerf Inference / gpt-oss-120bOffline · v6.1 · Tokens/s

512 × AMD Instinct MI355X 288GB HBM3e

5,749,440^* Tokens/s

Accuracy target / result: exact_match: 83.706
Weight precision: mxfp4
Division: closed
System type: datacenter
Availability: available
Cores per processor: 64
Processors per node: 2
Nodes: 64
Total accelerators: 512
Software stack: vLLM 0.22.1 (ROCm 7.2.2), PyTorch 2.10
Operating system: Ubuntu 24.04 (node amdgpu driver 6.14.x; container ROCm 7.2.2 userspace)

MLPerf Inference / gpt-oss-120bServer · v6.1 · Tokens/s

512 × AMD Instinct MI355X 288GB HBM3e

5,392,930^* Tokens/s

Accuracy target / result: exact_match: 83.706
Weight precision: mxfp4
Division: closed
System type: datacenter
Availability: available
Cores per processor: 64
Processors per node: 2
Nodes: 64
Total accelerators: 512
Software stack: vLLM 0.22.1 (ROCm 7.2.2), PyTorch 2.10
Operating system: Ubuntu 24.04 (node amdgpu driver 6.14.x; container ROCm 7.2.2 userspace)

Processing & platform

Processor: AMD EPYC 9575F
Graphics: AMD Instinct MI355X 288GB HBM3e

Connectivity & software

Operating system: Ubuntu 24.04 (node amdgpu driver 6.14.x; container ROCm 7.2.2 userspace)

System configuration

Reported host core count: 64
Processors per node: 2
Accelerator count: 512
Nodes: 64
Software stack: vLLM 0.22.1 (ROCm 7.2.2), PyTorch 2.10
Submission division: closed

* Provisional data