| --- |
| license: apache-2.0 |
| tags: |
| - diffusion |
| - dream |
| - gguf |
| - cpu-inference |
| - diffuse-cpp |
| language: |
| - en |
| base_model: Dream-org/Dream-v0-Instruct-7B |
| pipeline_tag: text-generation |
| --- |
| |
| # Dream-v0-Instruct-7B-GGUF |
|
|
| GGUF quantizations of [Dream-org/Dream-v0-Instruct-7B](https://huggingface.co/Dream-org/Dream-v0-Instruct-7B) for use with [diffuse-cpp](https://github.com/iafiscal1212/diffuse-cpp), the first C++ inference engine for Diffusion Language Models. |
|
|
| Dream is a masked diffusion language model based on the Qwen2.5-7B backbone with Grouped Query Attention (GQA). It generates all tokens in parallel through iterative refinement, excelling at math and factual tasks. |
|
|
| **Dream correctly solves 15 x 23 = 345 in just 2 denoising steps at 21.6 tok/s — 2.5x faster than llama.cpp.** |
|
|
| ## Available Quantizations |
|
|
| | File | Type | Size | Description | |
| |------|------|------|-------------| |
| | `dream-7b-f16.gguf` | F16 | ~15 GB | Full precision, best quality | |
| | `dream-7b-q8_0.gguf` | Q8_0 | ~8.2 GB | 8-bit quantization, near-lossless | |
| | `dream-7b-q4km.gguf` | Q4_K_M | ~5.0 GB | 4-bit mixed, best speed/quality ratio | |
| |
| **Recommended:** Q4_K_M for most users. |
| |
| ## Quick Start |
| |
| ```bash |
| # Download |
| huggingface-cli download diffuse-cpp/Dream-v0-Instruct-7B-GGUF dream-7b-q4km.gguf |
| |
| # Build diffuse-cpp (v0.2.0+) |
| git clone --recursive https://github.com/iafiscal1212/diffuse-cpp.git |
| cd diffuse-cpp |
| cmake -B build -DCMAKE_BUILD_TYPE=Release |
| cmake --build build -j$(nproc) |
| |
| # Run |
| ./build/diffuse-cli -m ../dream-7b-q4km.gguf \ |
| --tokens "151644,8948,198,2610,525,264,10950,17847,13,151645,198,151644,872,198,3838,374,220,868,1303,220,1419,30,151645,198,151644,77091,198" \ |
| -n 64 -s 16 -t 12 --remasking entropy_exit |
| ``` |
| |
| ## Performance |
| |
| Benchmarked on AMD EPYC 4465P 12-Core, Q4_K_M, entropy_exit + inter-step cache, B=64: |
| |
| | Prompt | tok/s | Steps | vs llama.cpp | |
| |--------|-------|-------|-------------| |
| | Capital of France? | **21.6** | 2 | 2.5x | |
| | 15 x 23? | **21.6** | 2 | 2.5x | |
| | Translate to French | 14.3 | 6 | 1.7x | |
| | Translate to Spanish | 13.2 | 10 | 1.6x | |
| | Python is_prime() | 8.2 | 7 | 1.0x | |
| | Why sky blue? | 4.9 | 16 | 0.6x | |
| | List planets | 4.9 | 16 | 0.6x | |
| | Poem about ocean | 4.5 | 16 | 0.5x | |
| | **Average** | **11.6** | | **1.4x** | |
| |
| - Dream excels at **math and code** (converges in 2-7 steps) |
| - 5 of 8 prompts match or beat llama.cpp (8.51 tok/s baseline) |
| - llama.cpp baseline: Qwen2.5-7B-Instruct, Q4_K_M, same hardware |
| |
| ## Dream vs LLaDA |
| |
| | Strength | Dream-7B | LLaDA-8B | |
| |----------|----------|----------| |
| | Math/Arithmetic | 21.6 tok/s (2 steps) | 6.0 tok/s (16 steps) | |
| | Code generation | 8.2 tok/s (7 steps) | 4.5 tok/s (15 steps) | |
| | Translation | 13-14 tok/s | 23-28 tok/s | |
| | Creative writing | 4.5 tok/s | 5.0 tok/s | |
| |
| **Use Dream for math, code, factual tasks. Use LLaDA for translation, conversation.** |
| |
| ## Model Details |
| |
| - **Architecture:** Qwen2.5-7B backbone with bidirectional attention |
| - **Parameters:** 7.62B |
| - **Layers:** 28 |
| - **Hidden size:** 3584 |
| - **Attention:** GQA (28 query / 4 KV heads) |
| - **FFN:** SwiGLU, intermediate 18944 |
| - **Vocabulary:** 152,064 tokens |
| - **RoPE theta:** 1,000,000 |
| - **Mask token ID:** 151666 |
| - **QKV biases:** Yes (kept at F32 in all quantizations) |
| |
| ## Conversion Details |
| |
| 339 tensors (255 weights + 84 QKV biases). Converted with `convert-dream.py` from diffuse-cpp. |
| |
| ## Citation |
| |
| ```bibtex |
| @software{diffuse_cpp_2026, |
| title={diffuse-cpp: High-Performance Inference for Diffusion Language Models}, |
| author={Carmen Esteban}, |
| year={2026}, |
| url={https://github.com/iafiscal1212/diffuse-cpp} |
| } |
| ``` |
| |
| ## License |
| |
| Apache 2.0 |
| |
