Speculative decoding: performance varies by model
An article published on June 3, 2026 compares DFlash and MTP with vLLM and llama.cpp on math, coding, and chat tasks. Results vary by model and workload.
Source: Benchmarks de speculative decoding: DFlash vs. MTP no Qwen3.6 (kaitchup.substack.com). Text prepared with AI from this source.
What happened and what to do
Published on June 3, 2026, the article compares DFlash and MTP with vLLM and llama.cpp on math, coding, and chat tasks. On Qwen3.6 27B, DFlash reaches up to 4× speedup; on Qwen3.6 35B A3B, MTP usually performs better. The results indicate that the choice depends on the model and workload.
For a company, the practical response is to test these options on its own workloads before adopting a configuration. Wendelmaques can structure an evaluation on the company's infrastructure, measure performance and costs by task, and present the findings in a dashboard to support a decision.
How the consultancy can help
Wendelmaques can diagnose the opportunity, define a comparison plan using the company's models and workloads, and implement evaluation and monitoring on its own infrastructure. Operations and scope are defined in a proposal.
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Send a short description of the models, workloads, and infrastructure involved to receive a scoped proposal.
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