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Nebius vs Luminal
Nebius is a European AI cloud with managed inference and raw GPUs. Luminal is a compiler that runs models faster on whichever GPUs you pick.
By The Subconscious Team · Updated
Nebius vs Luminal: key differences
Nebius offers Token Factory for 60+ open models from $0.06 per million input tokens, dedicated endpoints, uploaded fine-tunes and raw GPUs, all on one European account. Luminal sells the engine layer: its compiler emits native GPU kernels ahead of time for models you bring, served on early-access endpoints or licensed on-prem.
They can combine: a team renting Nebius GPUs could run Luminal's open-source compiler or license it on top. On its own, Nebius is the pick for a broad managed catalog and EU hosting. Luminal is the pick for maximum throughput on one model, with a reported 36K tokens per second on GPT-OSS 120B across 8 H100s.
What Nebius and Luminal do
Nebius
Nebius is an Amsterdam-headquartered AI cloud and the strongest European alternative to the US hyperscalers. It sells raw NVIDIA GPU compute, from H100s at $2.15 an hour preemptible up to GB300 NVL72 racks, and it has begun adding Vera Rubin. Hyperscale buyers back it: a Microsoft capacity deal worth about $17.4B in September 2025, then a Meta agreement worth up to about $27B in March 2026.
Example models: DeepSeek V3, GPT-OSS
Full Nebius 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 Nebius or Luminal?
Nebius vs Luminal at a glance
| Attribute | Nebius | Luminal |
|---|---|---|
| Model access | Open weights, 60+ models | Bring your own weights |
| Flagship models | DeepSeek, Qwen, GLM, Kimi, GPT-OSS | No public catalog |
| Speed | Among top hosts on throughput | 36K tok/s on GPT-OSS 120B, 8xH100 (vendor) |
| Price | From $0.06 per 1M input | Pay per use; rates not published |
| Customization | Serve uploaded fine-tunes | Compiles any PyTorch or HF model |
| Deployment | Token Factory, dedicated, raw GPUs | Serverless (early access), on-prem license |
| Long context | Varies by model | Unknown |
Frequently asked questions
What is the difference between Nebius and Luminal?
Nebius is a European AI cloud with managed inference and raw GPUs. Luminal is a compiler that runs models faster on whichever GPUs you pick.
When should I choose Nebius over Luminal?
Managed open models plus raw GPUs on one account; European hosting; Serving uploaded fine-tunes.
When should I choose Luminal over Nebius?
A faster engine on rented or owned GPUs; On-prem deployments with custom kernel work and SLAs; Maximum throughput per GPU on a self-chosen model.
Is Nebius or Luminal cheaper?
Nebius: From $0.06 per 1M input. Luminal: Pay per use; rates not published. The cheaper choice depends on the model and workload.
Related comparisons
Running long-horizon agents?
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.