Cadre

Inference Platform Economics — Fireworks, Together, Baseten, Modal, Replicate, Anyscale

The 2026 inference market is no longer GPU time rental. It bifurcates into custom silicon (Groq, Cerebras, SambaNova), GPU platforms (Baseten, Together, Fireworks, Modal), and API-first marketplaces (Replicate, DeepInfra). Fireworks raised price $1/hr per GPU on May 1, 2026, and $4B valuation on 10T+ tokens/day tells you the volume-driven model works. Baseten closed $300M Series E at $5B in January 2026. The competitive positioning rule is simple: Fireworks optimizes latency, Together optimizes catalog breadth, Baseten optimizes enterprise polish, Modal optimizes Python-native DX, Replicate optimizes multimodal reach, Anyscale optimizes distributed Python. This lesson gives you a matrix you can hand a founder.

Learn 1 hr Python (stdlib, toy per-call economics comparator)

Prerequisites: Phase 17 · 01 (Managed LLM Platforms), Phase 17 · 04 (vLLM Serving Internals)

#Learning Objectives

Name the three market segments (custom silicon, GPU platforms, API-first) and map each vendor to a segment.
Explain why the "per-token" API pricing model compresses toward the serving engine's cost curve, not the hardware's.
Compute effective cost per request across at least three vendors and explain when per-minute (Baseten, Modal) beats per-token.
Identify which platform is the right default for a given workload (serverless bursty, steady high-throughput, fine-tuned variants, multimodal).

#Learning Objectives

Keep going. The rest of this lesson is one step away.