A 510GB model called Flash: the local-hardware reality of DeepSeek V4.1-Flash
DeepSeek's Flash model weighs 510GB, but local-inference readers argue only about 150GB must stay resident, because the Engram table is looked up, not streamed.
Vlad Makarovreviewed and published
DeepSeek calls it Flash. The download is roughly half a terabyte, which local-inference readers noticed first. On September 10, a thread on r/LocalLLaMA titled "I find it funny that a flash model is now 512GB" drew roughly 400 points and more than 80 comments, its poster asking: "What do we call under 100GB models now? Tiny models? haha."
The same day, a thread on r/LocalLLM did the arithmetic by hand. Its author, who opens with "Mine, so saying that up front," read the shard headers of the Hugging Face weights and reported the split: "The 510 GB is 296 GB routed experts, 203 GB Engram tables, 11 GB everything else." That Engram figure matters: it is the part of the half-terabyte that mostly stays on disk.
A lookup table you barely touch
The card describes Engram conditional memory as 196B parameters, "sparsely accessed via token-based lookup" — a table you consult, not weights that stream through compute on every token. The poster's reading puts numbers on that: the tables hash n-gram orders 2, 3 and 4 with 8 heads across 2 engram layers, about 48 rows per token at 264 bytes — 12 KiB per token against 4.5 GB of expert weights. Their conclusion: "Latency cost, not bandwidth cost, and it belongs on an SSD."
Only a few rows are touched per token, found by hash rather than read in sequence, so a cold table is not a slow one: a miss costs a disk read, not a permanent claim on memory. The question stops being how much RAM you own and becomes how fast your SSD answers scattered reads. The poster puts the resident working set at roughly 150 GB of the 510 — their own shard-header estimate, not a DeepSeek figure — and offers one self-measured comparison: Qwen3.8 on an M5 Max at 40.09 tokens per second with the table on an SSD against 40.47 in memory, a 0.9% gap. Different model, different hardware.
Flash describes DeepSeek's bill, not yours
The card explains why the name fits. V4.1-Flash carries a 552B backbone but activates only 8B parameters per token during prefill and 16B during decode, with a KV cache of 890 bytes per token. It ships under an MIT license, with the technical report beside the weights. Flash describes serving economics at DeepSeek's scale: the small active counts make each token cheap in a datacenter; the 552B backbone makes it unhostable at home. No independent consumer-hardware throughput numbers exist; our release coverage has the benchmarks.
What would settle it
All of this rests on one anonymous shard-header reading and a thread mostly jokes. A single reproducible recipe for one machine, quantized or not, with published prefill and decode numbers at long context would end the argument. Until then, Flash stays a datacenter adjective, and the 510 GB stays a download most people never start.
