fix: remove virtual allocation from DeepSeek key takeaways#83
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Pull request overview
Updates the DeepSeek-V4-Flash benchmark “Key takeaways” in the README to remove misleading virtual GPU allocation numbers and replace them with a clearer, plain-language explanation tied to KV-cache compression and SSD streaming.
Changes:
- Removes the “33% lower GPU allocation (40.6 GB vs 60.5 GB)” claim from the DeepSeek key takeaways.
- Adds a plain-language explanation for the long-context speedup (KV-cache compression reducing SSD streaming pressure).
- Simplifies the “Peak physical RAM” takeaway to avoid referencing “GPU InUse”.
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| **Key takeaways:** | ||
| - 🏆 **SSD + TurboQuant dominates at long context** — 4.16 tok/s at 40K vs 0.32 tok/s for plain SSD Stream (**13× faster**), with 33% lower GPU allocation (40.6 GB vs 60.5 GB). | ||
| - 🏆 **SSD + TurboQuant dominates at long context** — 4.16 tok/s at 40K vs 0.32 tok/s for plain SSD Stream (**13× faster**). TurboQuant compresses the KV cache so far fewer layers need to stream from SSD per token. | ||
| - At 512-token context all configurations perform similarly (~4.4–4.8 tok/s); TurboQuant's advantage is KV-cache compression at long context. |
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In this Key takeaways section, the terminology is inconsistent between “KV cache” (line 91) and “KV-cache” (line 92). Please standardize the phrasing (pick one form) within the section for readability/searchability.
Suggested change
| - At 512-token context all configurations perform similarly (~4.4–4.8 tok/s); TurboQuant's advantage is KV-cache compression at long context. | |
| - At 512-token context all configurations perform similarly (~4.4–4.8 tok/s); TurboQuant's advantage is KV cache compression at long context. |
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Removes '33% lower GPU allocation (40.6 GB vs 60.5 GB)' — virtual numbers that are misleading. Explains the speed difference in plain language instead.