Post

Muse Spark’s Official Four-GPU Reference Uses GB300, TP4 and EP4

Muse Spark Open’s official four-device self-managed reference uses SGLang across four GB300 GPUs. The published command sets tensor parallelism 4 and expert parallelism 4 for the NVFP4 checkpoint. Using NVIDIA’s documented 288GB B300 memory tier for the GB300 platform, the four-device pool totals 1,152GB—452GB above Meta’s stated 700GB minimum.

The four-device reference

EvidenceValueInterpretation
Official listed NVFP4 safetensors533.011GBStored checkpoint size, not peak runtime memory
Meta’s stated NVFP4 minimum700GBPublished memory boundary
4×B300 288GB tier1,152GB nominal452GB above the stated minimum
Published parallelismTP4 + EP4All four devices participate in both dimensions

Why the GB300/B300 wording needs care

The launch article says the NVFP4 reference runs across “four GB300 GPUs.” NVIDIA describes GB300 systems as platforms built around B300 GPUs and documents a 288GB-per-GPU tier. HighVRAM preserves the article’s wording while using the documented B300 memory figure. Operators should record the exact system SKU and runtime-visible memory rather than treating the platform label as a complete specification.

The command is the useful evidence

The official SGLang recipe names the NVFP4 checkpoint, modelopt_fp4 quantization, the flashinfer_trtllm mixture-of-experts backend, --tp-size 4 and --ep-size 4. That is stronger evidence than adding four GPU capacities and assuming the software will follow.

It does not publish a universal speed, power, context, reliability or concurrency result. Reproduction still depends on system topology, firmware, drivers, CUDA, integration version, placement, context, modality and serving load.

Why this is not the same as four B200s

Four B200 GPUs total 720GB and clear the 700GB minimum by 20GB, but no reviewed official source validates that four-device B200 configuration. Four GB300-class devices are explicitly named in the SGLang reference and have much more nominal memory headroom. The distinction is published deployment evidence—not merely 1,152GB versus 720GB.

Use the complete reference analysis

The complete four-GB300 guide includes the exact SGLang parameters, naming disclosure, path comparison and nine-step reproduction checklist.

Sources

Checked October 25, 2026. Nominal capacity is not a performance benchmark. The reference applies to the named SGLang configuration and hardware class.