Introducing Ship Beta
thesean.ai · 1,888 words · saved by 1 readers
Reducing LLM Costs 50% Using Best-Execution for Intelligence
Ship is an endpoint that provides output indistinguishable from the model you're already using, at half the price. Just replace model="<original>" with model="ship-like/<original>", and all requests will be 50% less expensive. We take the risk that any individual request costs us more to execute. This allows you to either (A) reduce costs on existing workflows or (B) increase quality by using more intelligence with the same budget. We achieve this by doing inference-time optimization with two guarantees: capability equivalence and behavioral equivalence. Capability equivalence means that…
saved by
related reading
- Kimi-K2.5 Inference Benchmark - Luminalluminal.com
- Introducing System One Models & Jev - TypeSafe AI Blogtypesafe.ai
- Transformer Inference Arithmetic | kipply's blogkipp.ly
- Noam Brown on X: "Implications of Large-Scale Test-Time Compute" / Xx.com
- LLM Inference Performance Engineering: Best Practices | Databricks Blogdatabricks.com
- Shipping at Inference-Speed | Peter Steinbergersteipete.me
- Patterns for Building LLM-based Systems & Productseugeneyan.com
- Spending Inference Time - Kevin Lukevinlu.ai
- Efficient LLM inferencefinbarrtimbers.substack.com
- Sail Researchsailresearch.com
- Sail Researchsailresearch.com
- What We’ve Learned From A Year of Building with LLMs – Applied LLMsapplied-llms.org