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GMI Cloud vs Luminal
GMI Cloud owns its GPUs and offers APAC data residency with 100+ models. Luminal compiles models into faster code for any GPU.
By The Subconscious Team · Updated
GMI Cloud vs Luminal: key differences
GMI Cloud runs owned hardware with shared, autoscaling and reserved GPUs, 100+ models and APAC data residency, at prices like $0.07 in and $0.40 out on GLM-4.7-Flash. Luminal is a compiler: it turns a model you bring into fused native kernels ahead of time and serves it on early-access endpoints or licensed on-prem.
GMI fits teams that need capacity or residency in Asia. Luminal fits teams that want more throughput per GPU, with a reported 36K tokens per second on GPT-OSS 120B over 8 H100s. Its open-source compiler could run on GMI's reserved GPUs.
What GMI Cloud and Luminal do
GMI Cloud
GMI Cloud is a vertically integrated GPU cloud and inference platform that owns its NVIDIA hardware. It runs Tier-4 data centers in Silicon Valley, Colorado, Taiwan, Thailand and Malaysia, and as an NVIDIA Cloud Partner it gets priority access to H100, H200 and B200 supply. The company pivoted from crypto mining into AI, which gave it experience standing up high-density power and cooling fast. An $82M Series A came from Headline, Wistron and Thai energy group Banpu.
Example models: GLM-4.7-Flash, Google Veo
Full GMI Cloud profileLuminal
Luminal builds an inference compiler. Where vLLM and SGLang interpret a model at runtime, Luminal compiles it ahead of time into native kernels for GPUs and ASICs. Models get lowered to a small graph of 15 primitive ops, and the compiler searches over fusion, tiling, memory and scheduling choices instead of relying on hand-written rules, which it says can find optimizations like Flash Attention on its own. The compiler is open source in Rust under Apache 2.0 or MIT, runs on CUDA and Metal with ROCm on the roadmap, and works as a torch.compile backend.
Example models: GPT-OSS 120B, Llama 3 8B
Full Luminal profileShould you choose GMI Cloud or Luminal?
GMI Cloud vs Luminal at a glance
| Attribute | GMI Cloud | Luminal |
|---|---|---|
| Model access | Open and third-party models | Bring your own weights |
| Flagship models | GLM-4.7-Flash, Google Veo | No public catalog |
| Speed | Near bare-metal performance | 36K tok/s on GPT-OSS 120B, 8xH100 (vendor) |
| Price | $0.07 in, $0.40 out (GLM-4.7-Flash) | Pay per use; rates not published |
| Customization | Unknown | Compiles any PyTorch or HF model |
| Deployment | Shared, autoscaling, reserved GPUs | Serverless (early access), on-prem license |
| Long context | Varies by model | Unknown |
Frequently asked questions
What is the difference between GMI Cloud and Luminal?
GMI Cloud owns its GPUs and offers APAC data residency with 100+ models. Luminal compiles models into faster code for any GPU.
When should I choose GMI Cloud over Luminal?
APAC data residency; Reserved GPUs on owned hardware; Media and LLM models in one catalog.
When should I choose Luminal over GMI Cloud?
Maximum throughput per GPU on a self-chosen model; On-prem deployments with custom kernel work and SLAs; An open-source engine teams can run on their own hardware.
Is GMI Cloud or Luminal cheaper?
GMI Cloud: $0.07 in, $0.40 out (GLM-4.7-Flash). Luminal: Pay per use; rates not published. The cheaper choice depends on the model and workload.
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If your agents run past 200K tokens, compare both against Subconscious. Our inference stack treats a long-horizon trace as the primary workload, so speed, cost, and accuracy hold up deep into the trace.