Qwen3.8 27B › NVIDIA RTX 3090 Ti

Qwen3.8 27B on the NVIDIA RTX 3090 Ti

Qwen3.8 27B runs at about 41.6 tokens/s on the NVIDIA RTX 3090 Ti (measured, Q4_K_M, CUDA, single-stream llama-server decode).

Best measured: 41.6 tokens/s generation (Q4_K_M, CUDA). The source gives no prompt-processing figure.

For comparison, our size-scaling estimate for this combination is 38.5 tok/s.

Every run

QuantBackendGenerate tok/sPrompt tok/sTestBuild / by / notesSource
Q4_K_MCUDA 41.2–decode, llama-server, MTP off Baseline (spec-off) column of a paired MTP A/B: llama-server single stream (--parallel 1), probe.py median, not llama-bench. 256K context. File size 17,106,775,008 bytes as stated by the source.qwen38-mtp community table (GitHub)
Q4_K_MCUDA 41.2–decode, llama-server, MTP off Baseline (spec-off) column of a paired MTP A/B: llama-server single stream (--parallel 1), probe.py median, not llama-bench. 256K context. File size 17,106,775,008 bytes as stated by the source.qwen38-mtp community table (GitHub)

tg128 = generating 128 tokens; pp512 = reading a 512-token prompt (llama-bench). LocalScore averages several prompt and output lengths, so its numbers run lower than tg128. "decode, llama-server" = single-stream generation speed measured against a running llama-server (no speculative decoding).

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