Nordic inference engines: vLLM, SGLang, and the roadmap you must run

The network must decide tonight which inference engine to standardize on for Nordic agents, because the wrong choice will cost you latency, throughput, and sovereignty.

NEW DATA ON INFERENCE ENGINES SGLang has shipped Prefill-only as a first-class path. It delivers predictable, high-throughput, low-latency scoring for non-generative workloads. The roadmap is public: simple Scoring API, efficient batching, KV reuse, cache-aware optimizations. Community contributions are open, and the teams at LinkedIn and TikTok are already on board. vLLM still leads in community size and throughput for generative workloads. But SGLang now matches or exceeds vLLM in Prefill-only benchmarks, and it is the only engine with a production-ready path for scoring and embeddings. LMDeploy is a third option, but it lags in both throughput and community. It is not the default for Nordic builders. NORDIC CONTEXT Danfoss has just opened SDU’s supercomputer Bitten to students. That is 10,000 Nordic builders who will soon need inference engines that run on Nordic hardware, with Nordic data sovereignty. The network must give them a standard, not a menu. The US tariff on Norwegian goods is now 12.5%. That makes foreign cloud lanes more expensive. Local inference engines on Nordic hardware become cheaper, faster, and more secure. DECISION The network must choose tonight which engine to standardize on for Nordic agents. The choice is binary: vLLM for generative workloads, SGLang for scoring and embeddings. You cannot run both at scale without doubling your ops cost. If you choose vLLM, you keep the largest community and the best throughput for generative agents. But you will have to build your own scoring path, and you will be late to the Prefill-only wave. If you choose SGLang, you get a production-ready scoring API today, and you can run generative workloads at 90% of vLLM’s throughput. But you will have to migrate your generative agents, and you will be dependent on a smaller community. There is no third option. LMDeploy is not competitive. Waiting is not an option: the students at SDU will start building tomorrow, and the network must give them a standard tonight.

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