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Ornith-1.0-35B-GGUF-NVFP4
Frosty40/Ornith-1.0-35B-GGUF-NVFP4
Ornith-1.0-35B-GGUF-NVFP4 is a text generation model from Frosty40. 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.
<p align="center" <img src="ornith-banner.jpeg" alt="Ornith-1.0-35B — GGUF / NVFP4" width="640" </p
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Repo size
42.1 GB
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.gguf21 GB · 100%
At a glance
- Task
- Text Generation
- Library
- gguf
- License
- mit
- Access
- Public
- Created
- Jun 26, 2026
- Updated
- Jul 2, 2026
- SHA
- 23c5fa71
Try a prompt
Base models
Model card
From the Hugging Face model README
<p align="center">
<img src="ornith-banner.jpeg" alt="Ornith-1.0-35B — GGUF / NVFP4" width="640">
</p>
Ornith-1.0-35B — GGUF / NVFP4
Status: R&D. data release — no claims.
GGUF NVFP4 (W4A4) build of deepreinforce-ai/Ornith-1.0-35B
(qwen3_5_moe, 35B MoE), converted from the
sakamakismile/Ornith-1.0-35B-NVFP4
compressed-tensors checkpoint for llama.cpp. Text-only (the source vision tower is not included).
- File:
ornith-1.0-35b-GGUF_NVFP4.gguf— 21.0 GB (21,046,365,120bytes) - SHA256:
d9ab37f61fedc3d75bac7516baf45da383fbd9bc4ff1cf240962ca1bc31b3177 - Tensors: 1593 (NVFP4 390, F32 1161, F16 2) · 40 layers · 256 experts (8 active) · hybrid linear/full attention
Runtime
Requires a llama.cpp build with qwen35moe architecture + NVFP4 support (not in mainline as of this release).
Tested binary: b1-1ec44d1, Linux aarch64, CUDA sm_121, NVIDIA GB10.
llama-cli -m ornith-1.0-35b-GGUF_NVFP4.gguf --jinja --reasoning-budget 0 -ngl 999 -p "..."
Benchmarks (this GGUF, GB10)
Accuracy
| Benchmark | Score | n | Method |
|---|---|---|---|
| GSM8K | 97.0% | 200 | generative, chat, thinking-off, exact-match |
| HellaSwag | 82.1% | 1000 | loglikelihood |
| Winogrande | 71.6% | 1000 | loglikelihood |
| ARC-Challenge | 49.2% | 299 | loglikelihood, multiple-choice |
| MMLU | 41.1% | 2000 | 0-shot loglikelihood, multiple-choice |
| TruthfulQA-MC1 | 35.7% | 817 | loglikelihood, multiple-choice |
| Wikitext-2 | PPL 6.36 | 100 chunks | -c 2048 |
MC/loglikelihood via llama-perplexity; GSM8K via llama-server (--reasoning-budget 0). 0-shot, no few-shot priming.
Throughput / concurrency (llama-batched-bench, 512-tok prompt + 256-tok gen)
| Agents | Prompt t/s | Agg gen t/s | Per-agent gen t/s | Total t/s | 256-tok reply (s) |
|---|---|---|---|---|---|
| 1 | 2333 | 69.0 | 69.0 | 195 | 3.7 |
| 8 | 2372 | 206.5 | 25.8 | 528 | 9.9 |
| 16 | 2356 | 225.7 | 14.1 | 568 | 18.1 |
| 32 | 2353 | 277.1 | 8.7 | 673 | 29.6 |
| 64 | 2351 | 326.3 | 5.1 | 766 | 50.2 |
| 96 | 2356 | 342.6 | 3.6 | 796 | 71.7 |
| 128 | 2353 | 350.6 | 2.7 | 810 | 93.5 |
| 192 | 2358 | 361.5 | 1.9 | 830 | 136.0 |
| 256 | 2356 | 372.3 | 1.5 | 849 | 176.0 |
Generation saturates ~370 t/s; 256 agents ran without OOM (~40 GB used). Compute-bound, not memory-bound.
Raw logs + CSVs: benchmarks/.
Conversion
convert_hf_to_gguf.py --outtype f16 --fuse-gate-up-exps --no-mtp (llama.cpp qwen35moe converter).
Source safetensors SHA256 ec25ada854768610c7b841889b2a1b9f06163eda798a296401be87d0a2613cdd.
Credits
- Base model: DeepReinforce — deepreinforce-ai/Ornith-1.0-35B (MIT)
- NVFP4 quantization: sakamakismile/Ornith-1.0-35B-NVFP4 (
llm-compressor,compressed-tensors) - Architecture: Qwen3.5-MoE (Qwen / Alibaba)
- GGUF format + runtime: llama.cpp / ggml
License
MIT, inherited from the base model. This repository adds only the GGUF/NVFP4 weights, conversion metadata, and benchmark data.
- Task
- Text Generation
- Library
- gguf
- License
- mit
- Languages
- en, zh, ja, fr
- Created
- Jun 26, 2026
- Updated
- Jul 2, 2026