---
license: apache-2.0
tags:
- eagle3
- speculative-decoding
- pearl
- llama-3.1
---

# Pearl EAGLE3.1 R2C best head (2026-06-19)

Selected head: **R2C_t7_g115**.

Selection rule: best overall 8×H100 serving throughput, ranked by aggregate best-K req/s across per-GPU concurrency C=1/4/16 and prompt-length buckets. K4/K5 vs K3 was diagnostic only; the selected checkpoint is the one with the best overall serving result.

Final rank by aggregate best-K req/s:

1. R2C — 11.0288
2. D — 11.0108
3. I75 — 11.0029
4. R4B — 10.9846
5. R3B — 10.9305

Full run artifacts, training states, logs, benchmark outputs, and selection manifests were archived to:

`s3://pearl-eagle31-artifacts-507286591552-us-east-2/eagle31-final-r2c-20260619T1318Z`

The PR branch was also updated with the multi-replica benchmark used for final evaluation:

`feat/real-prompt-eagle-mining-bench` @ `85861376 feat: add multi-replica EAGLE benchmark`

This HF repo contains the selected head files needed for serving/eval (`model.safetensors`, `config.json`, `config.py`, `val_metrics.json`) plus selection metadata. Optimizer/scheduler training state is in the S3 archive, not this model repo.