Qwen3-8B-Thinking-speculator.eagle3

Model Overview

• Verifier: Qwen3-8B
• Speculative Decoding Algorithm: EAGLE-3
• Model Architecture: Eagle3Speculator
• Release Date: 3/12/2026
• Version: 1.0
• Model Developers: RedHat

This is a speculator model designed for use with Qwen3-8B, based on the EAGLE-3 speculative decoding algorithm. It was trained using the speculators library on a combination of the Magpie-Align/Magpie-Pro-300K-Filtered and the HuggingFaceH4/ultrachat_200k datasets. The model was trained with thinking enabled. This model should be used with the Qwen3-8B chat template, specifically through the /chat/completions endpoint.

Use with vLLM

vllm serve Qwen/Qwen3-8B \
  -tp 1 \
  --speculative-config '{
    "model": "RedHatAI/Qwen3-8B-Thinking-speculator.eagle3",
    "num_speculative_tokens": 5,
    "method": "eagle3"
  }'

Configuration

• Model: Qwen3-8B-Thinking-speculator.eagle3
• temperature: 0.0
• backend: vLLM chat_completions
• rate-type: throughput
• max-seconds per run: 300
• hardware: 8× GPU (tensor parallel 8)
• Benchmark data: RedHatAI/speculator_benchmarks
• vLLM serve: --no-enable-prefix-caching, --max-num-seqs 64, --enforce-eager

Command

GUIDELLM__PREFERRED_ROUTE="chat_completions" \
GUIDELLM__MAX_CONCURRENCY=128 \
guidellm benchmark \
  --target "http://localhost:8000/v1" \
  --data "RedHatAI/speculator_benchmarks" \
  --data-args '{"data_files": "HumanEval.jsonl"}' \
  --rate-type throughput \
  --max-seconds 300 \
  --backend-args '{"extra_body": {"chat_completions": {"temperature": 0.0}}}'