frank-small: two wide unquantized contexts (2 x 200,704) on the 3090
Frank's order, two messages: "extend the max context of frank-small to 200700 per individual stream without further quantization", then "reduce it to 2 streams for a total of 401400-ish tokens, set ubatch to 1k", then "unquantize the KV if we have extra space". CTX_SIZE 540672 -> 401408 with PARALLEL 3 -> 2 gives n_ctx_slot 200,704: above the 200,700 the harness compacts at, so a full-length request lands in one stream instead of a 400 exceed_context_size_error. The pool must divide evenly across slots and stay 256-aligned for the FA path, which is why it is 401,408 and not 401,400. CACHE_TYPE_V q8_0 -> f16: the freed third slot is exactly what pays for unquantized values (24.5 -> 32 KiB/token), and the budget lands back in the 2-3 GiB band Frank set on 2026-10-02 instead of leaving ~6 GiB of the card idle. The asymmetric-KV contract that created this endpoint is spent with it; both --cache-type flags stay explicit. --batch-size/--ubatch-size are now passed (2048/1024). The endpoint had never passed either, so it ran on engine defaults nobody wrote down. Franksdank-Runbook: serverAppConfigs-docs/LLM/frank-small-llama-mimo-q5km.md
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# frank-small — llama.cpp (master, CUDA sm_86) serving
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# bartowski/MiMo-V2.6-Distill-Qwen-9B-GGUF:Q5_K_M on the RTX 3090, :7771.
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#
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# 2026-10-02 (Frank): THREE contexts, vision on, and a hard instruction to
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# leave 2-3 GiB of the card free. Both new demands cost memory, so the per-slot
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# window shrinks — see the budget below.
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# 2026-10-03 (Frank): TWO streams instead of three, each one WIDE — 200,704
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# tokens per conversation, above the 200,700 the harness compacts at — and the
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# KV cache is now FULLY UNQUANTIZED (f16 K, f16 V). The two moves are the same
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# move: llama.cpp divides --ctx-size across --parallel slots, so the slot given
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# up is exactly the VRAM that pays for unquantized V. No further quantization
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# anywhere on this endpoint.
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#
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# Two measurements on this card, this runtime, price the terms:
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# Three measurements on this card, this runtime, price the terms:
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# 2 x 262,144, no projector: 20,190 MiB used / 4,386 free
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# KV = 524,288 tok x 24.5 KiB = 12,800 MiB => non-KV (weights 6,557 +
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# DeltaNet state ~25/slot + compute buffers + CUDA graphs) = 7,390 MiB
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# 3 x 196,608, projector on: 22,972 MiB used / 1,153 free
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# KV = 14,113 MiB => non-KV WITH the vision tower = 8,859 MiB
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# The tower costs ~1.4 GiB, not the ~1.0 its file size suggested, so 196,608
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# per slot left only 1.1 GiB free — outside the band. The pool therefore is
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# 3 x 180,224 = 540,672 tokens: KV ~12,936 + non-KV 8,859 = ~21,800 MiB predicted.
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# MEASURED at this shape: 21,684 MiB used / 2,441 MiB free — inside the band, and
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# the number the bats budget gate reproduces (it prices non-KV at 9 GiB).
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# 3 x 180,224, projector on: 21,684 MiB used / 2,441 free (the 2026-10-02
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# shape) => non-KV = 8,748 MiB
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# Two slots give back one DeltaNet state (~25 MiB). Priced at f16 K+V
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# (32 KiB/token) this pool is 12,544 MiB, so the prediction is
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# 12,544 + ~8,800 = ~20.9 GiB used, ~3.1 GiB free — the band the 2026-10-02
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# shape hit, bought with precision instead of a slot. The 1024 ubatch
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# re-prices the compute buffers upward, so MEASURE after any change: if the
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# boot lands under 2 GiB free, step the pool down in 12,288-token
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# (384 MiB at this rate) increments.
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#
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# KV arithmetic: attention KV exists only in the 8 full-attention layers
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# (4 KV heads x 256 head_dim). K f16 = 16 KiB/token, V q8_0 = 8.5 KiB/token
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# (34 B per 32-element block) => 24.5 KiB/token, so 12,288 tokens (=4096/slot)
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# is one 293 MiB step — that is the ladder to walk if this moves again. The
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# native 262,144 per slot is NOT reachable three times: 3 x 262,144 x
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# 24.5 KiB = 18.4 GiB of KV before anything else is loaded.
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# (4 KV heads x 256 head_dim x 2 B) = 16 KiB/token for K and the same again for
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# V => 32 KiB/token, so 12,288 tokens (= 6144/slot) is one 384 MiB step — that
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# is the ladder to walk if this moves again. Two native windows (2 x 262,144)
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# are NOT reachable with full-precision V: 524,288 x 32 KiB = 16.1 GiB of KV
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# against a card with ~15.7 GiB of KV room once weights, the vision tower, the
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# DeltaNet states and the graphs are loaded. 200,704 per stream is what full
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# precision buys; q8_0 on V would buy 262,144 instead.
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#
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# Why V stays q8_0 and K stays f16: full-precision V would add 8 KiB/token —
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# +4.5 GiB on this pool — which is what pushes the card past its 24 GiB. K is
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# the tensor the asymmetric-KV contract exists to protect.
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# The asymmetric-KV contract this endpoint was created for (Frank, 2026-10-01
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# night: f16 K + q8_0 V) is now spent — it existed to make a third slot fit,
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# and the third slot is gone. The flags stay explicit so the choice is visible
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# in the argv either way.
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LLAMA_BIN=/home/dank/GitPackages/llama-master/build-cuda/bin/llama-server
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MODEL_FILE=/home/dank/models/MiMo-Q5KM/MiMo-V2.6-Distill-Qwen-9B-Q5_K_M.gguf
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@@ -41,20 +51,28 @@ ALIAS=frank-small
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BIND_ADDR=0.0.0.0
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LISTEN_PORT=7771
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# Three independent conversations. llama.cpp divides --ctx-size across
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# Two independent conversations. llama.cpp divides --ctx-size across
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# --parallel slots (n_ctx_slot = CTX_SIZE/PARALLEL), and a mamba-hybrid model
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# cannot use unified KV, so each slot gets its own cache and its own window.
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# 180,224 per slot is BELOW the native 262,144, and that is the cost of the
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# third slot: a longer single prompt needs compaction instead of one shot.
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# Consequence worth knowing: frank-primary's compaction trigger is 183,501
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# tokens, which no longer fits a frank-small slot — see the runbook's
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# "three slots vs compaction" note.
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CTX_SIZE=540672
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PARALLEL=3
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# 200,704 per slot is BELOW the native 262,144 — the price of paying for the
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# window in full precision — and ABOVE the harness's compaction trigger, which
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# is the point: a full-length request now lands in one stream instead of a 400
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# exceed_context_size_error. Cost of the third slot going away: a third
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# concurrent request queues behind a released slot instead of running.
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CTX_SIZE=401408
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PARALLEL=2
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# The KV contract (Frank, 2026-10-01 night): unquantized K, q8_0 V.
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# q8_0 on V is only served by the flash-attention path; the serve script
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# pins --flash-attn on and must never lose it.
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# Compute-buffer geometry. This endpoint passed neither flag until 2026-10-03,
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# so it ran on llama.cpp's own defaults (2048/512); the fleet now asks for a
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# 1024 ubatch on this shape. Both are tunables because the pair is a
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# measurement, not a law: on the 27B sibling 512 was the prefill peak and every
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# step up cost GiB of compute buffer for no speed.
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BATCH_SIZE=2048
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UBATCH_SIZE=1024
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# The KV contract (Frank, 2026-10-03): unquantized K AND V. --flash-attn stays
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# pinned on in the serve script — it is what made the q8_0-V path cheap and it
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# remains the fast path for f16 KV.
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CACHE_TYPE_K=f16
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CACHE_TYPE_V=q8_0
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CACHE_TYPE_V=f16
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NGL=99
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