vs
DeepInfra vs Luminal
DeepInfra wins on price across 150+ open models. Luminal wins on engine speed for a model you bring, with an open-source compiler.
By The Subconscious Team · Updated
DeepInfra vs Luminal: key differences
DeepInfra is the price reference for open models, from $0.02 per million tokens on small ones, with 150+ models and no minimums. Part of that comes from heavy quantization, such as FP4 DeepSeek V4 Pro capped at 66K context. Luminal sells no catalog. It compiles your model into fused native GPU kernels ahead of time and serves it serverless in early access or on-prem under license.
DeepInfra is the answer when you want a popular model cheap today. Luminal is the answer when you run a specific model at volume and want more tokens per GPU without changing precision; it reports 36K tokens per second on GPT-OSS 120B over 8 H100s, versus 26K for vLLM. Luminal has no public price list yet.
What DeepInfra and Luminal do
DeepInfra
DeepInfra is the price floor for open-model inference. Developers treat it as the reference point for what a token should cost, with small models like Llama 3.1 8B at $0.02 per million and DeepSeek V4 Flash at $0.14 in and $0.28 out. The catalog covers 150+ open models across text, image and speech behind a fully OpenAI-compatible API. There are no minimums, setup fees or contracts on the shared API.
Example models: DeepSeek V4 Flash, Llama 3.1 8B
Full DeepInfra 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 DeepInfra or Luminal?
DeepInfra
Choose DeepInfra for
- Lowest per-token prices on popular open models
- A large catalog with no contracts
- Fast intake of new releases
Luminal
Choose Luminal for
- Maximum throughput per GPU on a self-chosen model
- Serving custom or fine-tuned architectures off any catalog
- On-prem deployments with custom kernel work and SLAs
DeepInfra vs Luminal at a glance
| Attribute | DeepInfra | Luminal |
|---|---|---|
| Model access | Open weights | Bring your own weights |
| Flagship models | DeepSeek V4 Flash, Llama 3.1 8B | No public catalog |
| Speed | ~33 tok/s on DeepSeek V4 Pro (FP4) | 36K tok/s on GPT-OSS 120B, 8xH100 (vendor) |
| Price | From $0.02 per 1M | Pay per use; rates not published |
| Customization | No managed fine-tuning | Compiles any PyTorch or HF model |
| Deployment | Shared API, no contracts | Serverless (early access), on-prem license |
| Long context | 66K on FP4 DeepSeek V4 Pro | Unknown |
Frequently asked questions
What is the difference between DeepInfra and Luminal?
DeepInfra wins on price across 150+ open models. Luminal wins on engine speed for a model you bring, with an open-source compiler.
When should I choose DeepInfra over Luminal?
Lowest per-token prices on popular open models; A large catalog with no contracts; Fast intake of new releases.
When should I choose Luminal over DeepInfra?
Maximum throughput per GPU on a self-chosen model; Serving custom or fine-tuned architectures off any catalog; On-prem deployments with custom kernel work and SLAs.
Is DeepInfra or Luminal cheaper?
DeepInfra: From $0.02 per 1M. 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.