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DeepSeek-V4-Flash-180B-GGUF
0xSero/DeepSeek-V4-Flash-180B-GGUF
DeepSeek-V4-Flash-180B-GGUF is a text generation model from 0xSero. Use it when you need the model to write or continue text. It is set up for gguf. The card lists the license as mit.
[!TIP] Support this work → · X · GitHub · REAP paper · Cerebras REAP
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Repo size
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.gguf57.5 GB · 100%
At a glance
- Task
- Text Generation
- Library
- gguf
- License
- mit
- Access
- Public
- Created
- May 28, 2026
- Updated
- May 30, 2026
- SHA
- 58ff4b0d
Try a prompt
Base models
Model card
From the Hugging Face model README
[!TIP] Support this work → · X · GitHub · REAP paper · Cerebras REAP
DeepSeek-V4-Flash-180B-GGUF
GGUF quantization of 0xSero/DeepSeek-V4-Flash-180B.
At a glance
| Base model | 0xSero/DeepSeek-V4-Flash-180B |
| Format | GGUF |
| Total params | 180B |
| Active / token | — |
| Experts / layer | — |
| Layers | — |
| Hidden size | — |
| Context | — |
| On-disk size | 164 GB |
Which variant should I pick?
| Variant | Format | Link |
|---|---|---|
DeepSeek-V4-Flash-162B | BF16 | link |
DeepSeek-V4-Flash-162B-GGUF | GGUF | link |
DeepSeek-V4-Flash-180B | BF16 | link |
DeepSeek-V4-Flash-180B-GGUF (this) | GGUF | link |
DeepSeek-V4-Flash-213B | BF16 | link |
This repository contains DS4/DwarfStar GGUF conversions of DeepSeek-V4-Flash-Spark.
The GGUFs point back to the original Spark Hugging Face model:
- Original Spark model: https://huggingface.co/0xSero/DeepSeek-V4-Flash-180B
- Conversion source checkpoint: https://huggingface.co/0xSero/DeepSeek-V4-Flash-180B-codex-K160-REAP
- Runtime/converter repo: https://github.com/antirez/ds4
- Spark deployment repo: https://github.com/0xSero/deepseek-spark
Files
| File | Size | SHA256 |
|---|---|---|
DeepSeek-V4-Flash-Spark-Q2-REAP-ds4.gguf | 53.52 GiB | dae2ed196e8ad87d6667d3fa04f65d78302ea4f148ed0ee0f3ff0b829d1f9c5d |
Quantization
Q2-REAP-ds4: compact DS4 profile usingIQ2_XXSrouted gate/up experts,Q2_Krouted down experts, andQ8_0shared/output/attention projections.
These are DS4/DwarfStar-specific GGUF files for DeepSeek-V4 Flash REAP checkpoints. They are not generic llama.cpp files unless your runtime supports the same DeepSeek-V4 Flash tensor layout and DS4 metadata.
Validation
Validation summaries are uploaded in this repo under:
validation/20260528T160633Z/SUMMARY.mdvalidation/20260528T160633Z/summary.json
The Spark Q2 GGUF completed the DS4 context sweep through 200000 context on one DGX Spark:
| Context | Prefill tok/s | Decode tok/s | KV bytes |
|---|---|---|---|
| 2,048 | 360.26 | 13.63 | 52,184,460 |
| 4,096 | 357.05 | 13.74 | 80,373,132 |
| 8,192 | 360.20 | 13.56 | 136,750,476 |
| 16,384 | 348.30 | 13.31 | 249,505,164 |
| 32,768 | 333.74 | 12.59 | 475,014,540 |
| 65,536 | 306.45 | 11.79 | 926,033,292 |
| 131,072 | 267.63 | 10.29 | 1,828,070,796 |
| 200,000 | 214.11 | 9.25 | 2,776,775,308 |
The corrected 200K API probe used 182,633 prompt tokens and returned the visible marker SPARK-CTX-200000-OMEGA:
| Prompt tokens | TTFT seconds | Prefill tok/s | Decode tok/s | Passed core |
|---|---|---|---|---|
| 182,633 | 668.53 | 273.19 | 10.61 | true |
Terminal-Bench 2.0 evidence is included in the validation summary: one real gpt2-codegolf trial completed without harness errors after enabling amd64 binfmt on the ARM64 Spark host.
This repo publishes the validated Q2 long-context profile only.
License & citation
License inherited from the base model.
@misc{lasby2025reap,
title = {REAP the Experts: Why Pruning Prevails for One-Shot MoE Compression},
author = {Mike Lasby and Ivan Lazarevich and Nish Sinnadurai and Sean Lie and Yani Ioannou and Vithursan Thangarasa},
year = {2025}, eprint = {2510.13999}, archivePrefix = {arXiv}
}
Sponsors
Made possible by NVIDIA · TNG Technology · Lambda · Prime Intellect · Hot Aisle.
- Task
- Text Generation
- Library
- gguf
- License
- mit
- Created
- May 28, 2026
- Updated
- May 30, 2026