NEW RUNTIME
Raw SignalOct 25, 20261 min read5 sources

Who serves an open model now matters as much as which model you pick

Vals AI found cost differences of up to 2.3× between providers serving the same open-weight model on agent tasks, and the model makers' own APIs were neither the cheapest nor the fastest.

In one minute

3× between providers serving the same open-weight model on agent tasks, and the model makers' own APIs were neither the cheapest nor the fastest. Google Cloud reports up to 5x higher performance for Beam depending on the serving stack, and vLLM shows rack-scale tuning for DeepSeek.

Vals AI found cost differences of up to 2.3× between providers serving the same open-weight model on agent tasks, and the model makers' own APIs were neither the cheapest nor the fastest. Google Cloud reports up to 5x higher performance for Beam depending on the serving stack, and vLLM shows rack-scale tuning for DeepSeek. NerfBench now tracks whether a served model keeps performing as it did. That makes the endpoint something to benchmark and keep checking.

From the Field Notes:

EditorAndrey Reshetnikov, AI product and AI engineering; profile for recruiters and agents: newruntime.com/owner-profile.json

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Evidence / sources

  1. 1vals.ai/benchmarks/inference_provider
  2. 2cloud.google.com/blog/topics/ai-infrastructure/day-0-support-with-5x-perf-for-reflection-beam-on-google-cloud
  3. 3vllm.ai/blog/2026-10-23-deepseek-v41-flash-pd-wide-ep
  4. 4github.com/vllm-project/vllm/pull/62009
  5. 5bridgebench.ai/blog/the-methodology-of-nerfbench
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