Prime Inference tops Nemotron cache rankings

Cache efficiency is becoming a decisive advantage for agentic inference, where long prompts are repeatedly sent and sticker prices can be misleading. Prime Inference’s result is compelling, though developers should validate it against their own traffic patterns and latency requirements.

• –A 96.9% hit rate makes repeated long-context workloads dramatically cheaper.
• –Effective pricing matters more than advertised input rates for coding and agent sessions.
• –Prime Intellect’s OpenAI-compatible inference stack is aimed at serving open and custom models in production. [Prime Intellect](https://www.primeintellect.one/)
• –Cache performance is workload-dependent, so teams should compare hit rate, throughput, latency, and reliability together.
• –Nemotron 3.5 Super VL’s long-context, multimodal design makes it especially sensitive to caching efficiency.