VQV Signal
According to a post on X by @dextune, Tencent released Qwen3.8-27B-DSpine-b16, a 2B draft checkpoint meant to speed up the original Qwen3.8-27B model. The draft model predicts 16 tokens in parallel for the larger model to verify. The post says Tencent measured throughput rising from 210 to about 806 tokens per second on an office workload using SGLang, which it describes as 3.84x over normal decoding.
According to a post on X by @dextune, Tencent released Qwen3.8-27B-DSpine-b16, a 2B draft checkpoint meant to speed up the original Qwen3.8-27B model. The draft model predicts 16 tokens in parallel for the larger model to verify. The post says Tencent measured throughput rising from 210 to about 806 tokens per second on an office workload using SGLang, which it describes as 3.84x over normal decoding.
AI-assisted summary based on the listed source.
dextune reports that Qwen3.8-27B-DSpine-b16, released with Tencent, is a 2B draft checkpoint that speeds up the original Qwen3.8-27B by predicting 16 draft tokens in parallel for the larger model to verify. It says Tencent measured throughput rising from 210 to about 806 tokens per second on an office workload...
People serving Qwen3.8-27B could see much higher throughput from the same base model if the reported figures hold in their own workloads. Teams running office-style tasks on SGLang are the most directly affected, since those are the conditions the post cites. The figures come from a single workload and a secondhand summary, so independent benchmarks would be worth watching.
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