{"slug":"ds4-1-flash-4x6000-kk-dspark-k7","title":"DeepSeek V4.1 Flash on 4x RTX PRO 6000 Blackwell \u2014 Karmic Kraken TP4 adaptive DSpark K7","summary":"Karmic Kraken TP4 serving recipe: adaptive-verification DSpark K7, RAM Engram, 131K context (4.7M logical KV tokens).","license":"CC-BY-4.0","tier":"community","beta":true,"revision":{"no":3,"commit_sha":"9586d70f30e9771ec26b2ac56169071e2f69c9d3","content_hash":"f4f68429dec0992c5a46a323bf9b7566ce6a4918","created_at":"2026-10-31 12:36:43.900471-06","notes":"Benchmark-qualified configuration from local-inference-lab/rtx6kpro (Karmic Kraken serving report). Five warmed 30-second windows per cell on RTX PRO 6000 Blackwell Max-Q; decode ctx-0 temp 1. Launch argv transcribed verbatim from the repo's unified Docker guide (same composition). Measured: C1 249.1 tok/s, C8 805.5 tok/s, 32K prefill 17982 tok/s."},"engine_source":{"type":"docker_image","git_url":"https://github.com/local-inference-lab/vllm","base_engine":"vllm","pip_package":null,"base_version":"karmic-kraken-beta (vLLM cfdecfaa4)","image_digest":"ghcr.io/local-inference-lab/vllm:karmic-kraken-beta-20260922-3221ccacf71002ea","install_note":null,"pinned_commit":"cfdecfaa4739ee3141c9745997cd8a83f31745a4"},"credit":[{"name":"local-inference-lab","url":"https://github.com/local-inference-lab/rtx6kpro"}],"author":{"name":"localai-recipes","isSite":true},"uploaded_by":"localai-recipes","config":{"launch":["serve","deepseek-ai/DeepSeek-V4.1-Flash","--async-scheduling","--attention-backend","B12X","--block-size","256","--compilation-config","'{\"cudagraph_mode\":\"FULL_AND_PIECEWISE\"}'","--decode-context-parallel-size","1","--decode-refill-target","auto","--default-chat-template-kwargs","'{\"thinking\":true,\"reasoning_effort\":\"high\"}'","--dtype","bfloat16","--enable-auto-tool-choice","--enable-chunked-prefill","--enable-force-include-usage","--enable-prefix-caching","--enable-prompt-tokens-details","--enable-request-id-headers","--engram-config","'{\"cpu_offload\":false,\"table_memory\":\"disk\",\"disk_resident_scales\":false,\"projection_tp\":false}'","--generation-config","vllm","--gpu-memory-utilization","0.95","--host","0.0.0.0","--jit-monitor-mode","warn","--kv-cache-dtype","fp8","--linear-backend","b12x","--load-format","instanttensor","--max-cudagraph-capture-size","128","--max-model-len","-1","--max-num-batched-tokens","4096","--max-num-seqs","32","--max-parallel-prefills","1","--moe-backend","b12x","--override-generation-config","'{\"temperature\":1.0,\"top_p\":0.95}'","--pipeline-parallel-size","1","--port","8000","--prefill-compute-share","0.4","--prefill-policy","round-robin","--prefill-schedule-interval","1","--reasoning-parser","deepseek_v41","--safetensors-load-strategy","lazy","--no-scheduler-reserve-full-isl","--served-model-name","DeepSeek-V4.1-Flash","--speculative-config","'{\"method\":\"dspark\",\"attention_backend\":\"B12X\",\"draft_sample_method\":\"greedy\",\"rejection_sample_method\":\"standard\",\"num_speculative_tokens\":7,\"draft_tensor_parallel_size\":4,\"enable_adaptive_verification\":true,\"adaptive_verification_cost_scale\":1.0}'","--swa-block-size","128","--tensor-parallel-size","4","--tokenizer-mode","deepseek_v41","--tool-call-parser","deepseek_v41"]},"models":[{"slug":"deepseek-v4-1-flash","name":"DeepSeek-V4.1-Flash","hf_repo":"deepseek-ai/DeepSeek-V4.1-Flash","quant":null}],"hardware":[{"slug":"nvidia-rtx-pro-6000-blackwell-max-qx4","vendor":"nvidia","card":"RTX PRO 6000 Blackwell Max-Q","card_family":"rtx-pro-6000-blackwell","vram_gb":96,"device_count":4}],"generation":"blackwell","tags":["adaptive"],"tasks":["chat","code"],"aa":{"aa_index":39,"aa_provenance":"measured","aa_source_url":"https://artificialanalysis.ai/models/deepseek-v4-1-flash","aa_index_version":"Index v4.3.2","aa_methodology_version":"Index v4.3.2 (2026-10-18)","aa_published_fetched_at":"2026-10-20 21:49:11.309778-06","aa_family_slug":"deepseek-v4-1-flash","aa_resolved_slug":"deepseek-v4-1-flash"},"performance":[{"claimed_by":"submitter","metrics":"{\"tok_s\": 249.099999999999994315658113919198513031005859375}"}],"perf_points":[{"id":2326,"context_len":1,"prefill_tok_s":null,"decode_tok_s":249.099999999999994315658113919198513031005859375,"ttft_ms":null,"concurrency":1,"claimed_by":"submitter","notes":"Karmic Kraken 5-window median, ctx-0 decode, temp 1 (verifier 98.6 steps/s)"},{"id":2327,"context_len":1,"prefill_tok_s":null,"decode_tok_s":805.5,"ttft_ms":null,"concurrency":8,"claimed_by":"submitter","notes":"Karmic Kraken 5-window median, ctx-0 decode, temp 1 (verifier 361.9 steps/s)"},{"id":2328,"context_len":32768,"prefill_tok_s":17982,"decode_tok_s":null,"ttft_ms":null,"concurrency":1,"claimed_by":"submitter","notes":"Karmic Kraken 5-window median, unique uncached nominal-32K requests, client TTFT"}],"agent":{"prompt":"Fetch https://localairecipes.com/api/v1/recipes/ds4-1-flash-4x6000-kk-dspark-k7.json and apply the inference recipe it describes (engine flags, model, quant, context) to my setup. Ask before overwriting any existing config.","curl":"curl -fsSL https://localairecipes.com/api/v1/recipes/ds4-1-flash-4x6000-kk-dspark-k7.json"},"requirements":{"requires":["Docker (or a compatible OCI container runtime)","NVIDIA Container Toolkit (nvidia-container-toolkit) - exposes host GPUs to the container"],"driver_floor":{"cuda":null,"linux_min":null,"text":"unknown - check the image tag","source":"NVIDIA CUDA Toolkit Release Notes - driver compatibility tables (https://docs.nvidia.com/cuda/cuda-toolkit-release-notes/, fetched 2026-10-03)"},"placeholders":["Hardware-bound values in this recipe (device counts, bind-mount paths, utilization, ports) describe the author's machine, not yours - map them to your own rig before launching. Keep the engine flags, model, quant, and parallelism strategy; adjust paths and ports to the hardware you actually have.","GPU identity: list your GPUs with `nvidia-smi -L` and substitute your own GPU UUIDs/indices wherever the recipe pins the author's.","Model directory: bind-mount paths are author-side - point them at your own mount where the model files live.","Host port: pick a free port on your machine and publish the container there; keep the in-container port unchanged."]},"artifacts":[],"links":{"self":"/api/v1/recipes/ds4-1-flash-4x6000-kk-dspark-k7.json","alternate":"/r/ds4-1-flash-4x6000-kk-dspark-k7","describedby":"/openapi.json"},"updated_at":"2026-10-31 12:36:43.900471-06","created_at":"2026-10-20 21:49:11.880179-06","speeds":{"decode_tok_s":249.099999999999994315658113919198513031005859375,"prefill_tok_s":17982,"leaderboard":"/api/v1/leaderboard.json"}}