Gate 1
Workload baseline
Freeze model, weights, code, inputs, resolution, frame rate, chunking, concurrency, traffic, warmup, encoding, GPU topology, latency, stalls, failures, quality, and cost.
Matched accelerator pilot
HeyGen Avatar IV TPU Deployment Readiness
Describe the actual model and stream, GPU baseline, TPU mesh, memory, sharding, collectives, compiler, kernels, quality corpus, traffic, latency, reliability, Region, quota, cost, canary, and rollback. Generate a matched pilot rather than borrowing HeyGen's benchmark.
Four deployment gates
Gate 2
TPU and compiler fit
Measure HBM, activations, mesh, sharding, collectives, supported operators, fallbacks, host transfers, compilation, recompiles, kernels, layouts, flags, quotas, and capacity.
Gate 3
Output acceptance
Require identical hashes where numerical order should remain stable, and a predefined similarity band plus blind frame review for intentional numerical changes.
Gate 4
Production outcome
Compare accepted-video latency, stalls, throughput, utilization, reliability, full cost, privacy, artifact promotion, observability, incident ownership, canary, and rollback.
Decide on accepted output
Proceed to canary
The matched TPU build passes output, stream deadline, reliability, capacity, operational, privacy, and full-cost thresholds with rollback proven.
Continue optimization
Correctness is stable, but traces show a bounded collective, kernel, layout, compiler, stage, utilization, or cost gap with a testable next lever.
Keep the GPU path
Quality, capacity, reliability, engineering cost, workload variability, or end-to-end economics do not justify migration for the measured workload.
Minimum matched run
Run the same frozen corpus and traffic shape on both builds. Compare p50, p95 and p99 chunk time, stalls, throughput, utilization, errors, retries, recompiles, quality acceptance, operational evidence, and full cost per accepted video minute.
Read the architecture and migration guides
Avatar IV on Google Cloud TPUUnderstand the eight-chip Trillium pipeline, 1.86x boundary, sharding, kernels, compiler contracts, and quality gates.GPU vs. TPU migration checklistTurn the engineering record into baseline, trace, quality, production, canary, and rollback gates.
Official facts checked August 15, 2026. Recheck Google Cloud hardware, compiler, quota, pricing, Region, and HeyGen workload documentation.
Frequently Asked Questions
It converts the workload, GPU baseline, TPU topology, compiler, quality, streaming, reliability, cost, and rollback evidence you provide into a pilot checklist. It does not access HeyGen or Google Cloud.
No. It compares the optimized TPU build with HeyGen's first working TPU version. The source separately reports comparable performance to its 8xH100 production setup for this pipeline.
No. Treat it as a workload-specific hypothesis. Use your Region, price, utilization, compilation, retries, engineering, storage, network, quality acceptance, and cost per accepted video minute.
Reject or escalate it when output falls outside the predefined identical or bounded-difference quality gate, or when end-to-end stalls, reliability, capacity, operations, or full cost fail.