Pruning - GoKawiil

Cerebras adds Qwen 3.8 27B model to public API at ~1500 tokens/sec

Cerebras has added the 27-billion-parameter Qwen 3.8 model to its public API endpoints, offering inference speeds of roughly 1500 tokens per second. The model supports 64k context on free tier and 128k on paid tier, and is available under Cerebras's free trial and pay-as-you-go pricing, subject to rate limits.

inference-docs.cerebras.ai · 2026-09-03

Baseten explains how inference engineers trade off latency, throughput and cost for LLMs

A technical breakdown describes the 'efficient frontier' concept in LLM inference, distinguishing techniques that shift performance along a fixed tradeoff curve—like sacrificing latency for throughput or intelligence for speed—from techniques that expand the frontier itself, creating more overall efficiency. Examples cited include quantization, distillation, pruning, and reasoning-level adjustments, applied in the context of running large agentic coding models such as GLM-5.3 or Kimi K3 with KV cache reuse.

baseten.co · 2026-09-01