One signal

An open-source benchmark project reports that DeepSeek’s DSpark speculative decoding reached up to 2.25× the token-generation speed of plain decoding on an AMD Radeon RX 7900 GRE. The tests use llama.cpp and include Vulkan and ROCm backends.

The project says text quality was maintained, and describes its results as reproducible batch-size-one benchmarks on consumer hardware. It also examines draft lengths, confidence cut-offs and prompt-processing costs. That gives local-inference builders a useful test case beyond datacentre hardware. The headline gain is the project’s reported maximum, not a guarantee that every model or setup will see the same speed-up.

Discuss: For local-model benchmarks, should reproducibility and realistic hardware matter more than chasing the largest headline speed-up?

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