Unverified50% confidenceBenchmarkExact time
Under a citation prompt with a 29k-token context, HyperQwen decoding reached 237.6 tok/s and passed verbatim verification; prefill was about 1,210 tok/s, and the prompt completed in about 24 seconds, roughly five times that of llama.cpp (~250 tok/s).
1
Sources
50%
Confidence
Short-term (~14 days)
Relevance
10/16/2026
First Seen
Valid until: 10/30/2026
Sources
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Related Claims
VerifiedIn decode speed tests, speeds of approximately 45 tokens/second are achievable within 20,000 tokens, dropping sharply to approximately 20 tokens/second beyond 30,000 tokens.73% similarUnverifiedAt approximately 4K input, TTFT is 23.6 seconds with decoding at 46.6 tok/s; at 8K, 47 seconds and 41.4 tok/s; at 16K, 1 minute 30 seconds and 30.8 tok/s; at 30K, 3 minutes 15 seconds and 31.9 tok/s.73% similarUnverifiedWhen running IQ3_XXS quantized models with llama.cpp, the output speed is only 15 tok/s with prompt processing at 100–120 tok/s, while a self-developed engine brings the same quantization up to approximately 65 tok/s output and 430 tok/s prompt processing, representing close to a 4x performance improvement.71% similarUnverifiedIn a test scenario where eight agents each process 7.5k-token documents and a chat request is issued in the second second, Superfluid answers in 0.36 seconds while llama-server outputs no first token for more than 10 seconds, a first-token latency gap of about 30 times.71% similarUnverifiedIn the long-context archiving experiment, 8 requests each input approximately 261,000+ tokens and each completed approximately 1,022 outputs; the total throughput of the joint decoding window was 214.85 tokens per second, approximately 26.86 per request, but the window was only approximately 2.28 seconds and prefilling was serial or interleaved.70% similar
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