Unsloth Dynamic 2.0 achieves superior accuracy & outperforms other leading quants.
DeepSeek-V4-Flash-0731 is the official release of DeepSeek-V4-Flash, superseding the preview version, with substantially enhanced agentic capabilities. It has the same model structure as DeepSeek-V4-Flash-DSpark, i.e. it comes with a speculative decoding module attached.
DeepSeek-V4-Flash-0731 outperforms DeepSeek-V4-Pro (Preview) on benchmarks listed below despite its far smaller activated parameter count, and is broadly competitive with the strongest proprietary models available.
| Benchmark | DeepSeek-V4-Flash-0731 | DeepSeek-V4-Flash (Preview) | DeepSeek-V4-Pro (Preview) | GLM-5.2 | Opus-4.8 |
|---|---|---|---|---|---|
| Terminal Bench 2.1 | 82.7 | 61.8 | 72.1 | 81.0 | 85.0 |
| NL2Repo | 54.2 | 39.4 | 38.5 | 48.9 | 69.7 |
| Cybergym | 76.7 | 38.7 | 52.7 | - | 83.1 |
| DeepSWE | 54.4 | 7.3 | 12.8 | 46.2 | 58.0 |
| Toolathlon-Verified | 70.3 | 49.7 | 55.9 | 59.9 | 76.2 |
| Agents' Last Exam | 25.2 | 15.8 | 16.5 | 23.8 | 25.7 |
| AutomationBench Public | 25.1 | 10.8 | 12.8 | 12.9 | 27.2 |
| DSBench-FullStack † | 68.7 | 37.0 | 41.8 | 61.8 | 71.6 |
| DSBench-Hard † | 59.6 | 25.8 | 31.1 | 54.5 | 71.7 |
Notes:
max reasoning effort level with temperature = 1.0, top_p = 0.95.This repository and the model weights are licensed under the MIT License.
@misc{deepseekai2026deepseekv4,
title={DeepSeek-V4: Towards Highly Efficient Million-Token Context Intelligence},
author={DeepSeek-AI},
year={2026},
}
UD-IQ1_S/DeepSeek-V4-Flash-0731-UD-IQ1_S-00002-of-00003.gguf 49 GBUD-IQ1_S/DeepSeek-V4-Flash-0731-UD-IQ1_S-00003-of-00003.gguf 33 GBUD-IQ1_S/DeepSeek-V4-Flash-0731-UD-IQ1_S-00001-of-00003.gguf 5 MBUD-IQ1_M/DeepSeek-V4-Flash-0731-UD-IQ1_M-00002-of-00003.gguf 49 GBUD-IQ1_M/DeepSeek-V4-Flash-0731-UD-IQ1_M-00003-of-00003.gguf 37 GBUD-IQ1_M/DeepSeek-V4-Flash-0731-UD-IQ1_M-00001-of-00003.gguf 5 MBUD-IQ2_XXS/DeepSeek-V4-Flash-0731-UD-IQ2_XXS-00002-of-00003.gguf 50 GBUD-IQ2_XXS/DeepSeek-V4-Flash-0731-UD-IQ2_XXS-00003-of-00003.gguf 41 GBUD-IQ2_XXS/DeepSeek-V4-Flash-0731-UD-IQ2_XXS-00001-of-00003.gguf 5 MBUD-IQ2_M/DeepSeek-V4-Flash-0731-UD-IQ2_M-00002-of-00003.gguf 50 GBUD-IQ2_M/DeepSeek-V4-Flash-0731-UD-IQ2_M-00003-of-00003.gguf 41 GBUD-IQ2_M/DeepSeek-V4-Flash-0731-UD-IQ2_M-00001-of-00003.gguf 5 MBUD-Q2_K_XL/DeepSeek-V4-Flash-0731-UD-Q2_K_XL-00002-of-00003.gguf 49 GBUD-Q2_K_XL/DeepSeek-V4-Flash-0731-UD-Q2_K_XL-00003-of-00003.gguf 47 GBUD-Q2_K_XL/DeepSeek-V4-Flash-0731-UD-Q2_K_XL-00001-of-00003.gguf 5 MBUD-IQ3_XXS/DeepSeek-V4-Flash-0731-UD-IQ3_XXS-00002-of-00004.gguf 50 GBUD-IQ3_XXS/DeepSeek-V4-Flash-0731-UD-IQ3_XXS-00003-of-00004.gguf 49 GBUD-IQ3_XXS/DeepSeek-V4-Flash-0731-UD-IQ3_XXS-00004-of-00004.gguf 5.0 GBUD-IQ3_XXS/DeepSeek-V4-Flash-0731-UD-IQ3_XXS-00001-of-00004.gguf 5 MBUD-IQ3_S/DeepSeek-V4-Flash-0731-UD-IQ3_S-00003-of-00004.gguf 50 GBUD-IQ3_S/DeepSeek-V4-Flash-0731-UD-IQ3_S-00002-of-00004.gguf 49 GBUD-IQ3_S/DeepSeek-V4-Flash-0731-UD-IQ3_S-00004-of-00004.gguf 17 GBUD-IQ3_S/DeepSeek-V4-Flash-0731-UD-IQ3_S-00001-of-00004.gguf 5 MBUD-Q3_K_M/DeepSeek-V4-Flash-0731-UD-Q3_K_M-00003-of-00004.gguf 50 GBUD-Q3_K_M/DeepSeek-V4-Flash-0731-UD-Q3_K_M-00002-of-00004.gguf 49 GBUD-Q3_K_M/DeepSeek-V4-Flash-0731-UD-Q3_K_M-00004-of-00004.gguf 29 GBUD-Q3_K_M/DeepSeek-V4-Flash-0731-UD-Q3_K_M-00001-of-00004.gguf 5 MBUD-IQ4_NL/DeepSeek-V4-Flash-0731-UD-IQ4_NL-00003-of-00004.gguf 50 GBUD-IQ4_NL/DeepSeek-V4-Flash-0731-UD-IQ4_NL-00002-of-00004.gguf 49 GBUD-IQ4_NL/DeepSeek-V4-Flash-0731-UD-IQ4_NL-00004-of-00004.gguf 38 GBUD-IQ4_NL/DeepSeek-V4-Flash-0731-UD-IQ4_NL-00001-of-00004.gguf 5 MBUD-IQ4_XS/DeepSeek-V4-Flash-0731-UD-IQ4_XS-00003-of-00004.gguf 50 GBUD-IQ4_XS/DeepSeek-V4-Flash-0731-UD-IQ4_XS-00002-of-00004.gguf 49 GBUD-IQ4_XS/DeepSeek-V4-Flash-0731-UD-IQ4_XS-00004-of-00004.gguf 38 GBUD-IQ4_XS/DeepSeek-V4-Flash-0731-UD-IQ4_XS-00001-of-00004.gguf 5 MBUD-Q4_K_XL/DeepSeek-V4-Flash-0731-UD-Q4_K_XL-00004-of-00005.gguf 50 GBUD-Q4_K_XL/DeepSeek-V4-Flash-0731-UD-Q4_K_XL-00003-of-00005.gguf 49 GBUD-Q4_K_XL/DeepSeek-V4-Flash-0731-UD-Q4_K_XL-00002-of-00005.gguf 49 GB 7.2 GBUD-Q8_K_XL/DeepSeek-V4-Flash-0731-UD-Q8_K_XL-00003-of-00005.gguf 50 GBUD-Q8_K_XL/DeepSeek-V4-Flash-0731-UD-Q8_K_XL-00004-of-00005.gguf 49 GBUD-Q8_K_XL/DeepSeek-V4-Flash-0731-UD-Q8_K_XL-00002-of-00005.gguf 49 GBUD-Q8_K_XL/DeepSeek-V4-Flash-0731-UD-Q8_K_XL-00005-of-00005.gguf 13 GBUD-Q8_K_XL/DeepSeek-V4-Flash-0731-UD-Q8_K_XL-00001-of-00005.gguf 5 MBUD-Q3_K_XL/DeepSeek-V4-Flash-0731-UD-Q3_K_XL-00003-of-00004.ggufUD-Q3_K_XL/DeepSeek-V4-Flash-0731-UD-Q3_K_XL-00002-of-00004.gguf 49 GBUD-Q3_K_XL/DeepSeek-V4-Flash-0731-UD-Q3_K_XL-00004-of-00004.gguf 29 GBUD-Q3_K_XL/DeepSeek-V4-Flash-0731-UD-Q3_K_XL-00001-of-00004.gguf 5 MBUD-Q4_K_XL/DeepSeek-V4-Flash-0731-UD-Q4_K_XL-00005-of-00005.ggufUD-Q4_K_XL/DeepSeek-V4-Flash-0731-UD-Q4_K_XL-00001-of-00005.gguf 5 MBCUDA_VISIBLE_DEVICES=0,1,2,3 GGML_CUDA_P2P=1 DSV4_CONSTANT_SHAPE=1 DSV4_SPARSE_FA=1 DSV4_FA_UNION=1 DSV4_IDX_SKIP=1 DSV4_MOE_TILE=1 DSV4_MOE_RESIDENT=1 DSV4_GLU_FUSE=1 DSV4_MOE_FUSE=1 DSV4_DECODE_FUSED_IDX=1 DSV4_DECODE_RADIX_TOPK=1 DSV4_PREFILL_RADIX_TOPK=1 DSV4_MMVQ_SMALLK=1 DSV4_STABLE_TOPO=1 GGML_GALLOC_STICKY=1 DSV4_PREFILL_GRAPHS=1 DSV4_AGENT_CKPT_TAIL=1 llama-server -m DeepSeek-V4-Flash-0731-UD-IQ2_M-00001-of-00003.gguf -ngl 999 -ts 1,1,0.95,1.05 --split-mode layer --flash-attn on --no-repack --ctx-size 131072 --batch-size 8192 --ubatch-size 384 --ctx-checkpoints 1 -t 8 --parallel 1 --jinja --reasoning-budget 1024 --reasoning-budget-message 'Okay, that is enough thinking. Let me get to work.'在 LocalMaxxing 上查看测试
llama-server --model DeepSeek-V4-Flash-0731-UD-Q4_K_XL-00001-of-00005.gguf --alias deepseek-v4-flash-0731-ud-q4-k-xl --host 0.0.0.0 --port 18081 --ctx-size 262144 --parallel 1 --device CUDA0,CUDA1,CUDA2,CUDA3,CUDA4,CUDA5,CUDA6 --split-mode layer --tensor-split 7,6,6,6,6,6,7 --n-gpu-layers all --n-cpu-moe 1 --flash-attn on --cache-type-k q8_0 --cache-type-v q8_0 --batch-size 256 --ubatch-size 256 --threads 24 --threads-batch 48 --temp 1.0 --top-p 0.95 --cache-prompt --cache-ram 2048 --reasoning on --reasoning-format deepseek --jinja在 LocalMaxxing 上查看测试
# Remote endpoint: http://127.0.0.1:8080 servedModel: DeepSeek-V4-Flash-1bit在 LocalMaxxing 上查看测试
来自 LocalMaxxing 的 7 次社区测试(3 种配置)的中位数。
自己运行:配置指南