DeepSeek V4.1 Flash GGUF for DwarfStar

Calibrated weights for the Metal implementation in DwarfStar, developed on the ds4.1flash branch. These are not interchangeable with DeepSeek V4 Flash weights or its DSpark drafter.

The language GGUFs each include 188.83 GiB of native FP8 Engram tables. DwarfStar reads the needed rows directly from disk; it never makes the whole table resident. Keep the GGUF on a fast local SSD. The main-weight sizes above do not include context or runtime buffers.

Download and Run

From a DwarfStar checkout with V4.1 support:

./download_model.sh ds41f-q2
./ds4 -m gguf/DeepSeek-V4.1-Flash-Q2.gguf --ssd-streaming --ctx 32768

Use SSD streaming on a single 128 GB Mac. Q2 also fits resident tensor parallelism across two 128 GB Macs with RDMA, or full residency on a larger Mac. Q4 needs SSD streaming on smaller Macs; the resident target is a 512 GB Mac. It does not fit resident TP across two 128 GB Macs.

./download_model.sh ds41f-q4
./download_model.sh ds41f-vision

Q4 exceeds Hugging Face's single-file limit, so it is stored in two binary parts. The downloader joins them into DeepSeek-V4.1-Flash-Q4.gguf, verifies the complete file and removes the temporary parts. Allow another 37 GiB of free disk space while joining. Rerun the command after an interruption. The individual parts are not runnable GGUFs.

For images, add --vision gguf/DeepSeek-V4.1-Flash-Vision.gguf to the language model command. The same model and memory options work with ds4-agent and ds4-server.

Quantization

Q2 uses IQ2_XXS routed gate/up experts and Q2_K down experts. Q4 uses Q4_K for all routed experts. Both retain Q8 attention projections, shared experts and output, with F16/F32 tensors elsewhere and unchanged native Engram data. They use the same 8,192-token activation imatrix, not a requantization of one GGUF into the other.

Source: deepseek-ai/DeepSeek-V4.1-Flash at df42c109f1defefcbfcedbe7d905718a12266e40. The separate encoder comes from the same checkpoint. See the included upstream MIT license.