{"meta":{"count":5,"page":1,"pages":1,"per_page":12,"applied":{"engine":null,"model":"deepseek-v4-1-flash","quant":null,"storage":null,"hardware":null,"generation":null,"task":null,"tier":null,"tags":[],"vram":null,"search":null,"sort":"updated","featured":false},"origin":"https://localairecipes.com","openapi":"/openapi.json","updated_at":"2026-10-31T02:38:31+00:00"},"recipes":[{"slug":"deepseek-v4-1-flash-on-4x-dgx-spark-tuned-tp4-sglang-dspark","title":"DeepSeek-V4.1-Flash on 4x DGX Spark \u2014 tuned TP4 SGLang/DSpark","summary":"","tier":"community","beta":false,"generation":"blackwell","decode_tok_s":89.7000000000000028421709430404007434844970703125,"prefill_tok_s":5650,"updated_at":"2026-10-29 21:32:23.622356-06","commit_sha":"ddf188add74be5de70f13f6f71735ec18a87c83c","content_hash":"647b167cbdd40dfd95cbaabc81e8624e929d847d","votes":0,"credit":[{"name":"knapcio (TP4 profile, v2.1-v2.3 production stack, release gates)","url":"https://github.com/knapcio/DeepSeek-V4.1-Flash-4x-DGX-Spark-TP4"},{"name":"MiaAI-Lab (upstream: launcher, Engram store, b12x routing, memory model)","url":"https://github.com/MiaAI-Lab/DeepSeek-v4.1-Flash-DGX-Sparks"},{"name":"0xSero (original 4x RTX PRO 6000 recipe skeleton boot.py derives from)","url":"https://github.com/sybil-solutions/deepseek-v4.1-flash-4x-rtx-pro-6000"},{"name":"kpham-sgl (sglang#39187 bounded dense-indexer prefill transient, backported as adapter/indexer_chunked*.py)","url":"https://github.com/sgl-project/sglang/pull/39187"},{"name":"BBuf + dsv4.1 branch contributors (#39370, #39646, #39648, #39653 decode kernel work in the canary images)","url":"https://github.com/sgl-project/sglang"},{"name":"rhys101 (SG17 RoCEnante overlay + SG18 prefill TP split from DeepSeek-V4.1-Flash-vLLM-DGX-Spark-8)","url":"https://github.com/rhys101/DeepSeek-V4.1-Flash-vLLM-DGX-Spark-8"},{"name":"local-inference-lab \u2014 Luke Alonso & Jason (b12x: RoCEnante one-shot RDMA all-reduce + fused MoE kernels)","url":"https://github.com/local-inference-lab/b12x"},{"name":"FujitsuPolycom + sparkring contributors (switchless-ring opposite-node paths, path-aware RoCEnante)","url":"https://github.com/FujitsuPolycom/sparkring"},{"name":"Saolence (#1/#2/#4/#5/#6: ring as opt-in switch, NCCL/build fixes, first-deployer review)","url":"https://github.com/knapcio/DeepSeek-V4.1-Flash-4x-DGX-Spark-TP4/pull/4"},{"name":"rsync/rchmagos (#8: RoCEnante on the switchless ring, DSV41_ROCE_RING + scripts/ring_mesh/)","url":"https://github.com/knapcio/DeepSeek-V4.1-Flash-4x-DGX-Spark-TP4/pull/8"}],"uploaded_by":"localai-recipes","measured":null,"links":{"self":"/api/v1/recipes/deepseek-v4-1-flash-on-4x-dgx-spark-tuned-tp4-sglang-dspark.json","alternate":"/r/deepseek-v4-1-flash-on-4x-dgx-spark-tuned-tp4-sglang-dspark"}},{"slug":"deepseek-v4-1-flash-exl3-3bpw-tc-moe-on-4x-cmp-170hx-tp4","title":"DeepSeek-V4.1-Flash EXL3 3bpw TC-MoE on 4x CMP 170HX TP4 (original checkpoint)","summary":"DeepSeek-V4.1-Flash (ORIGINAL deepseek-ai/DeepSeek-V4.1-Flash checkpoint, quantized by Mia-AiLab as EXL3 3.02bpw \u2014 NOT the 2026-10-17 '1017' re-release, which has its own sibling recipe) served EXL3 3bpw tensor-parallel 4 on four CMP 170HX cards (sm_80, 140 W, HBM locked 1728 MHz) in a 2x Xeon E5-2689 v4 Broadwell host, PCIe Gen2 x16, no NVLink, using Morrowmake's tensor-core MoE kernels + host-staged all-reduce ported onto this checkpoint: K3 on every served layer with a split K2 down-projection, row-rule hybrid (coop rows 1-42, moe_out_v2 43-64, moe_out_prefill 65-2048), one shared 540.4 MiB MoE workspace per GPU, zero-register-spill served kernels. Measured by the author: 178.3 tok/s structured decode c1, 587 tok/s across 8 users, median TTFT 8.37 s from 2K through 255K context (10.9 s at 255,424) against the same host's optimized graphs+coop+NCCL stack at 172.7 / 456 / 10.15 s; needles 9/9 through 256K; KV pool 616,916 tokens.","tier":"community","beta":false,"generation":"ampere","decode_tok_s":149.19999999999998863131622783839702606201171875,"prefill_tok_s":1486,"updated_at":"2026-10-29 21:32:23.373585-06","commit_sha":"dc2dbe7cce66fb0f4d3dfad6b6765ed3c4ea8f74","content_hash":"5640bd33a3ca7d6a71e5a4804e0ec780e0c34fb1","votes":0,"credit":[{"name":"CurtisAccelerate","url":"https://github.com/CurtisAccelerate"},{"name":"Morrowmake","url":"https://github.com/Morrowmake/vllm-cmp170hx"},{"name":"turboderp-org/exllamav3 - EXL3 codec @ d3739fd3 (MIT; Copyright (c) 2025 Turboderp)","url":"https://github.com/turboderp-org/exllamav3"}],"uploaded_by":"localai-recipes","measured":null,"links":{"self":"/api/v1/recipes/deepseek-v4-1-flash-exl3-3bpw-tc-moe-on-4x-cmp-170hx-tp4.json","alternate":"/r/deepseek-v4-1-flash-exl3-3bpw-tc-moe-on-4x-cmp-170hx-tp4"}},{"slug":"deepseek-v4-1-flash-sm80-deepinfer-kernel-port-6x-a100-dspark-k5","title":"DeepSeek-V4.1-Flash SM80 DeepInfer kernel port 6x CMP 170HX DSpark K5","summary":"DeepSeek-V4.1-Flash served on six 64 GB SM80 GPUs (GA100 die, owner-classified 170HX) with HalfVulpes' Deepinfer-SM80 patch set: a 30-file vLLM V1 overlay porting DeepSeek's DeepInfer kernel architecture (SM100 tcgen05/TMEM) to Ampere mma.sync tensor cores - unified 512-dim SM80 sparse-MLA decode/prefill kernels with bitshift UE8M0 scale decoding, a bit-exact single-CTA Triton TopK+SWA combiner (22.17x), direct-store KV-cache gather (7.64x @48K), SM80-aligned TileLang mHC routing (2.89x), and YOCO L20-L39 ragged indexer-metadata reuse (19 redundant kernel chains eliminated per chunk). TP2 x PP3 (14/14/12) + DSpark K=5 + 1M context, 4.65M-token GPU-resident KV. Author-measured: 64K cold prefill 4,507 tok/s (+24.2% vs baseline vLLM SM80), 64K TTFT 10.7 s (-18.9%), c1 DSpark decode 160.8 tok/s code / 188.8 tok/s 16K+ long-gen, c4 170.5 aggregate. Microbenchmarks bit-exact (0 diff) or within BF16 noise. Topology guide: PP6 = 2.1x slower single-stream; TP2+TP4 asymmetric hurts Marlin tiles.","tier":"community","beta":false,"generation":"ampere","decode_tok_s":160.80000000000001136868377216160297393798828125,"prefill_tok_s":4506.8000000000001818989403545856475830078125,"updated_at":"2026-10-28 15:48:17.404025-06","commit_sha":"ced28259b90a43ec103ecd450b68455a56d2808d","content_hash":"e00265eca8b84734c2c7de2b67d558b0d702d25e","votes":0,"credit":[{"name":"HalfVulpes (Deepinfer-SM80 port + measurements)","url":"https://github.com/HalfVulpes/Deepinfer-SM80"},{"name":"DeepSeek-AI (DeepInfer engine architecture + DeepSeek-V4.1-Flash checkpoint)","url":"https://github.com/deepseek-ai/DeepInfer"},{"name":"vLLM project (V1 engine + TPxPP runtime)","url":"https://github.com/vllm-project/vllm"},{"name":"TileLang + OpenAI Triton (SM80 kernel synthesis)","url":"https://github.com/tile-ai/tilelang"},{"name":"FlashInfer + IST-DASLab Marlin (sparse-MLA + MXFP4/W4A16 Ampere GEMM primitives)","url":"https://github.com/flashinfer-ai/flashinfer"}],"uploaded_by":"localai-recipes","measured":null,"links":{"self":"/api/v1/recipes/deepseek-v4-1-flash-sm80-deepinfer-kernel-port-6x-a100-dspark-k5.json","alternate":"/r/deepseek-v4-1-flash-sm80-deepinfer-kernel-port-6x-a100-dspark-k5"}},{"slug":"ds4-1-flash-4x6000-jj-dspark-k7","title":"DeepSeek V4.1 Flash on 4x RTX PRO 6000 Blackwell \\x{2014} TP4 DSpark K7","summary":"Community image TP4 serving recipe: adaptive DSpark K7, RAM Engram ngram tables, 131K context cap. Saved numbers from the KK comparison.","tier":"community","beta":false,"generation":"blackwell","decode_tok_s":230.599999999999994315658113919198513031005859375,"prefill_tok_s":17503,"updated_at":"2026-10-20 21:54:52.540452-06","commit_sha":"218c00c639d52ad29638628a64740ea90069ffe1","content_hash":"77484355ac2ebdc80317b43b37868302df70cf22","votes":0,"credit":[{"name":"local-inference-lab","url":"https://github.com/local-inference-lab/rtx6kpro"}],"uploaded_by":"localai-recipes","measured":null,"links":{"self":"/api/v1/recipes/ds4-1-flash-4x6000-jj-dspark-k7.json","alternate":"/r/ds4-1-flash-4x6000-jj-dspark-k7"}},{"slug":"deepseek-v4-1-flash-764b-on-4x-cmp-170hx-pp4-shadow-kv-exl3-2bpw","title":"DeepSeek-V4.1-Flash (764B) on 4x CMP 170HX \u2014 PP4, shadow KV, EXL3 2bpw, DSpark K5, 512k ctx, native vision (kaka86mm)","summary":"Four-card Ampere recipe for full DeepSeek-V4.1-Flash (764B, native vision) on 4x CMP 170HX (sm80, Gen2 x4, no P2P \u2014 256 GB VRAM can't hold 510 GB, so: EXL3 2bpw + fp8 KV): PP4 x TP1 partition 10,10,11,9 (rank3 = 9 layers + drafter), shadow KV via dsv41reap-pp overlay (54 files), EXL3 2bpw pack \u2014 engram tables kept FP8 at 203 GB, pinned 189 GiB host RAM (quantizing destroys retrieval), DSpark n=5 (conf=0; truncation is -30% here; ngram is a 7.6 tok/s disaster), 524k ctx, fp8_ds_mla KV, 5.9M-token pool, native ViT, GLOO_SOCKET_IFNAME=lo \u2014 the 09-28 one-line fix for PP gloo via docker bridge (535 ms/send) that collapsed long-context decode. Measured by the author (09-28 v37): decode 60.7 @32K / 58.3 @128K / 54.7 @524K tok/s (slope -10% vs -37% pre-fix), cold prefill 2,771 @32K to 4,061 tok/s @524K (flat), decode-only C8 200.6 / C24 252.1, quality 7/7 + vision 2/2. Patches: img_ids PP relay, engram sm80 fp8, cand-key fix, exl3 shim.","tier":"community","beta":false,"generation":"ampere","decode_tok_s":57.5,"prefill_tok_s":0,"updated_at":"2026-10-20 15:34:08.130558-06","commit_sha":"363a35de531734dabec247825b6103dc00425670","content_hash":"49f43cc59d2bfe7c33b889b5fdc5129673136cc3","votes":0,"credit":[{"name":"kaka86mm","url":"https://github.com/kaka86mm/dsv41-flash-pp4-170hx"},{"name":"zebgop-ops (dsv41reap-pp shadow KV overlay)","url":"https://github.com/zebgop-ops/dsv41reap-pp"},{"name":"vcruz305 (vllm-exl3 plugin)","url":"https://github.com/vcruz305/vllm-exl3"},{"name":"turboderp-org (exllamav3)","url":"https://github.com/turboderp-org/exllamav3"},{"name":"wtdcode (vllm-backport)","url":"https://github.com/wtdcode/vllm-backport"}],"uploaded_by":"localai-recipes","measured":null,"links":{"self":"/api/v1/recipes/deepseek-v4-1-flash-764b-on-4x-cmp-170hx-pp4-shadow-kv-exl3-2bpw.json","alternate":"/r/deepseek-v4-1-flash-764b-on-4x-cmp-170hx-pp4-shadow-kv-exl3-2bpw"}}]}