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DeepSeek vs Luminal
DeepSeek ships MIT-licensed models at very low first-party prices. Luminal compiles open models into faster code for your own GPUs.
By The Subconscious Team · Updated
DeepSeek vs Luminal: key differences
DeepSeek offers V4.1 Flash and V4 Pro on its own API with 1M context and off-peak discounts, and releases weights under MIT. Its hosted API stores data in China, which stops many enterprises. Luminal is not a model lab. Its compiler turns a model into fused native kernels ahead of time for serverless serving in early access or under an on-prem license.
For teams that cannot use DeepSeek's API, self-hosting the MIT weights is the usual answer, and that is where an engine like Luminal could fit. Luminal reports 36K tokens per second on GPT-OSS 120B over 8 H100s; it has not published DeepSeek numbers. Choose DeepSeek's API for the lowest price, Luminal for control.
What DeepSeek and Luminal do
DeepSeek
DeepSeek is the Chinese lab whose open-weight models reset price expectations for the whole market. Its API now serves two models, both with 1M context and 384K max output. V4.1 Flash shipped September 10, 2026 with built-in image understanding at $0.30 in and $1.20 out at peak. V4 Pro, generally available since August 13, costs $1.32 in and $3.96 out at peak. Cache hits cost a few cents per million or less, and the weights ship on Hugging Face under an MIT license.
Example models: DeepSeek V4.1 Flash, DeepSeek V4 Pro
Full DeepSeek 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 DeepSeek or Luminal?
DeepSeek vs Luminal at a glance
| Attribute | DeepSeek | Luminal |
|---|---|---|
| Model access | Open weights (MIT) | Bring your own weights |
| Flagship models | DeepSeek V4.1 Flash, V4 Pro | No public catalog |
| Speed | ~35 tok/s on V4 Pro | 36K tok/s on GPT-OSS 120B, 8xH100 (vendor) |
| Price | Off-peak hours at half price | Pay per use; rates not published |
| Customization | Open weights to fine-tune | Compiles any PyTorch or HF model |
| Deployment | First-party API, Hugging Face weights | Serverless (early access), on-prem license |
| Long context | 1M, 384K max output | Unknown |
Frequently asked questions
What is the difference between DeepSeek and Luminal?
DeepSeek ships MIT-licensed models at very low first-party prices. Luminal compiles open models into faster code for your own GPUs.
When should I choose DeepSeek over Luminal?
Very low first-party prices; 1M context on V4 models; MIT-licensed weights.
When should I choose Luminal over DeepSeek?
Keeping open-weight inference off China-hosted APIs; On-prem deployments with custom kernel work and SLAs; Maximum throughput per GPU on a self-chosen model.
Is DeepSeek or Luminal cheaper?
DeepSeek: Off-peak hours at half price. 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.