DeepReinforce
Ornith 1.0 35B A3B
最先端
231.3Kダウンロード348いいねJun 2026公開日262K トークンコンテキストMITライセンス72 優秀品質
Ornith 1.0 35B A3B (35.099998474121094B parameters) requires approximately 23.2 GB of VRAM with Q4_K_M quantization. As a Mixture of Experts model with 3B active parameters, it uses less memory than its total parameter count suggests. For the best balance of quality and speed, we recommend hardware with at least 27 GB of VRAM.
はじめに
— コピー&ペーストでローカル実行Copy-paste commands to run Ornith 1.0 35B A3B on your machine.
Run
docker run --rm -it ghcr.io/ggerganov/llama.cpp:full \
--hf-repo "deepreinforce-ai/Ornith-1.0-35B" \
--hf-file "Ornith-1.0-35B-Q4_K_M.gguf" \
-c 4096 -ngl 99Quick specs
Parameters35.1B (3B active)
Architecturemoe (MoE)
Context262K tokens
Modalitytext
Min RAM13.7 GB
Rec. RAM21.4 GB (Q4_K_M)
LicenseMIT
FamilyOrnith
✓ Code✓ Reasoning
About this model
- •Self-improving agentic RL: jointly refines solution generation and reasoning scaffolds.
- •35B MoE with only ~3B activated per token — the lightweight member of the Ornith family.
- •Hybrid linear-attention + full-attention (1-in-4 layers) for reduced KV-cache cost.
- •262K context, tuned for single-GPU agentic coding.
おすすめ
最適なハードウェア
Ornith 1.0 35B A3Bのおすすめ
このモデルを実行
量子化オプション
量子化レベル別VRAM推定値
No hardware detected — fit column shows raw VRAM estimates
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 13.7 GB | Low | — |
Q3_K_S | 3 | 17.2 GB | Low | — |
NVFP4 | 4 | 19.7 GB | Medium | — |
Q4_K_M | 4 | 21.4 GB | Medium | — |
Q5_K_M | 5 | 25.3 GB | High | — |
Q6_K | 6 | 28.8 GB | High | — |
Q8_0 | 8 | 37.6 GB | Very High | — |
F16 | 16 | 72.0 GB | Maximum | — |
ハードウェア互換性
全ハードウェアの適合度推定
Computing compatibility...
メモリ内訳
Reference: RTX 2060 6GB
Weights21.4 GB
KV Cache0.3 GB
Runtime0.9 GB
Headroom0.6 GB
よくある質問
FAQ — Ornith 1.0 35B A3B
関連項目