Qwen3.8 Flash Next on 1x 8 GB (ElectroHobo 3 bpw)
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| Reported 1 x 8 GB | |
| Quant | AutoRound mixed 2/3-bit (klee100, 2.998 effective bpw, 47 GiB on card) plus halt95's FP8 n-gram table in host RAM |
|---|---|
| Engine | Morrowmake/vllm-cmp170hx image with patch files mounted read-only recipe 0.2.1; engine 18305948ac |
| Topology | single card |
| Context | 262,144 |
| Decode | 296.4 tok/s |
| Prefill | 4243 tok/s |
| VRAM per card | 64 GiB, --gpu-memory-utilization 0.95 (fixed) |
| Power cap | 180 W |
| Driver | 580 or newer (measured on 610.57.04) |
| Unlock build | cmpunlocker (64 GiB, 74 SMs) |
| Flags | --tensor-parallel-size 1 --kv-cache-dtype bfloat16 --engram-config cpu_offload --max-num-seqs 48 --max-num-batched-tokens 3460 --block-size 912 cudagraph FULL_AND_PIECEWISE; DFlash 2 schedule [[1,2,7],[3,4,5],[5,48,3]] |
| Tested | @nathang6866 on 2026-10-23 |
| Source | link |
| Confirmations | None yet. |
Qwen3.8-Flash-Next on one 64 GB card with the full 262,144-token context. It joins klee100's mixed 2/3-bit AutoRound
checkpoint (47 GiB on the card) with halt95's FP8 n-gram table held in host RAM, or since 0.2.0 in a disk file read
through HMM, and serves up to 48 requests. It is the one-card sibling of
Qwen3.8 Flash Next on 2x 8 GB (ElectroHobo W4A16 TP2) and shares its engine, patches and table. Mountains called it
the fastest Qwen Next on a single card he had seen (quality and quant not yet checked). Infobox numbers are one user on
code.
Source: repo github.com/ElectroHobo/qwen38-flash-next-3bpw-1x-cmp170hx-recipe by ElectroHobo on GitHub, posted by @nathang6866, 2026-10-24
Source: @mountains1605, 2026-10-27
Prerequisites
- One CMP 170HX exposing 64 GiB at PCIe Gen2 x16 (Driver unlock, 8 GB card). Cards without the x16 mod are untested: n-gram rows cross PCIe every step.
- 96 GB of host RAM with the table in RAM (much less with the table on disk, which needs the open kernel modules with HMM and 48 GiB of disk).
- Linux, driver 580 or newer, Docker with the NVIDIA Container Toolkit, about 100 GiB free on one filesystem.
- Author's host: 2x Xeon E5-2697A v4 (Broadwell), 204 GiB RAM.
Source: repo github.com/ElectroHobo/qwen38-flash-next-3bpw-1x-cmp170hx-recipe by ElectroHobo on GitHub, posted by @nathang6866, 2026-10-24
Steps
git clone https://github.com/ElectroHobo/qwen38-flash-next-3bpw-1x-cmp170hx-recipe
cd qwen38-flash-next-3bpw-1x-cmp170hx-recipe
./start.sh # pull the engine image, fetch and build the model, start, wait for /health
- Checkpoint: klee100/Qwen3.8-Flash-Next-AutoRound-3bpw-MTP at
ce0e0b94(routed experts 3-bit g128 on layers 0-11 and 36-47, 2-bit g64 on 12-35; attention 8-bit; MTP head 4/8-bit) without its 95 GiB BF16 table shard, joined by hard links with the FP8 table shards of halt95/Qwen3.8-Flash-Next-W4A16-Merlin atcec53e9f. About 97 GiB downloaded instead of 255;MODELS_DIRmust be one filesystem. - Drafter incoai/Qwen3.8-Flash-Next-DFlash2 at
a22a1744, 7 drafts for 1 to 2 requests, 5 for 3 to 4, 3 beyond.SPEC_MODE=mtpuses the checkpoint's MTP head with 3 drafts. - Serve settings:
--tensor-parallel-size 1 --dtype bfloat16 --kv-cache-dtype bfloat16 --mamba-ssm-cache-dtype bfloat16 --attention-config '{"indexer_kv_dtype":"bf16"}' --engram-config '{"cpu_offload":true}' --max-model-len 262144 --gpu-memory-utilization 0.95 --max-num-seqs 48 --max-num-batched-tokens 3460 --prefix-match-unit 16 --block-size 912 --compilation-config '{"cudagraph_mode":"FULL_AND_PIECEWISE"}'; envVLLM_GDN_RECOVER=1 VLLM_USE_BREAKABLE_CUDAGRAPH=1 VLLM_QWEN4_QSA_TOPK_CANONICAL=1 VLLM_THIN_GEMM=1 VLLM_THIN_GEMM_GLUON=1 NCCL_P2P_DISABLE=1. - The first start compiles for about 12 minutes; the checkpoint loads in about 4 minutes from SSD and 31 minutes from a USB disk (set
READY_TIMEOUT=7200). API at 127.0.0.1:8000, modelqwen3.8-flash-next, no key unlessAPI_KEYis set.
Source: repo github.com/ElectroHobo/qwen38-flash-next-3bpw-1x-cmp170hx-recipe by ElectroHobo on GitHub, posted by @nathang6866, 2026-10-24
Measured numbers
Fresh clone 2026-10-23, 180 W, PCIe Gen2 x16, 74 SMs, MiaAI-Lab protocol. Tok/s structured / code / prose:
- 1 user 197.8 / 296.4 / 135.5; 8 users 799.5 / 791.3 / 586.4 total; 48 users 1,384 total (MTP 1,403).
- Cold prefill 4,243 tok/s; KV pool 292,784 tokens; code editing 371 tok/s.
- HumanEval 161/164 and GSM8K (first 200) 195/200 with thinking on.
- DFlash 2 is 53% faster on code for one user; MTP catches up from about 16 to 24 users.
- Table on disk (0.2.0): the server holds about 6 GiB instead of a 48 GiB pinned table; a whole container capped at 14 GiB still did 723.7 / 758.9 / 468.1 tok/s at 8 users; cold prefill drops from 4,255 to 3,376 tok/s.
- The card is power-bound at 180 W, sitting at 1,275 to 1,425 MHz during decode.
Source: repo github.com/ElectroHobo/qwen38-flash-next-3bpw-1x-cmp170hx-recipe by ElectroHobo on GitHub, posted by @nathang6866, 2026-10-24
Source: @nathang6866, 2026-10-24
Known issues
- AutoRound loading bugs the mounted patches fix: per-layer expert bits were applied only to classes named
fusedmoe(load failed with "The size of tensor a (40) must match the size of tensor b (60)"); the MTP layer index mismatch (mtp.layers.0in the config,mtp.layers.48in the engine); the engine refused an AutoRound checkpoint's n-gram table. A chunked copy-on-write fixes an OOM incopy_kv_cache_blocks_inplaceunder 32-request prefix-cache bursts in MTP mode. - Half the layers' routed experts are 2-bit; quality is scored only on HumanEval and GSM8K.
- Community recipe, not endorsed by Morrowmake, klee100 or halt95; patches are pinned to engine commit 18305948ac.
Source: repo github.com/ElectroHobo/qwen38-flash-next-3bpw-1x-cmp170hx-recipe by ElectroHobo on GitHub, posted by @nathang6866, 2026-10-24
Related
- Other single-card Qwen3.8 Flash Next recipe: Qwen3.8 Flash Next on 1x 8 GB (iIIusi0n SSD PLE).
- Dense alternative on one card: Qwen3.8 27B on 1x 8 GB (W4A16 vLLM).
- Engines, Quantization on the 170HX, Benchmarks.
Sources
- Repo: ElectroHobo/qwen38-flash-next-3bpw-1x-cmp170hx-recipe (MIT; engine Apache-2.0; checkpoints Qwen Community License 1.0). Releases 0.1.0 (2026-10-24), 0.2.0 and 0.2.1 (2026-10-28).