DeepSeek V2.5 236B
DeepSeek V2.5 — merged V2 chat + Coder. Pre-V3 baseline; 21B active MoE.
Overview
DeepSeek V2.5 — merged V2 chat + Coder. Pre-V3 baseline; 21B active MoE.
Family & lineage
How this model relates to others in its lineage. Family members share architecture and training-data roots; parent / children edges record direct distillation or fine-tune relationships.
Strengths
- Multi-head latent attention
- 21B active MoE
Weaknesses
- V3 / V4 supersede for new deployments
Quantization variants
Each quantization trades model quality for file size and VRAM. Q4_K_M is the most popular starting point.
| Quantization | File size | VRAM required |
|---|---|---|
| Q4_K_M | 134.0 GB | 160 GB |
Get the model
HuggingFace
Original weights
Source repository — direct quantization required.
Hardware that runs this
Cards with enough VRAM for at least one quantization of DeepSeek V2.5 236B.
Models worth comparing
Same parameter band, plus what's one tier above and below — so you can decide what actually fits your hardware.
Frequently asked
What's the minimum VRAM to run DeepSeek V2.5 236B?
Can I use DeepSeek V2.5 236B commercially?
What's the context length of DeepSeek V2.5 236B?
Source: huggingface.co/deepseek-ai/DeepSeek-V2.5
Reviewed by RunLocalAI Editorial. See our editorial policy for how we research and verify model claims.
Related — keep moving
Verify DeepSeek V2.5 236B runs on your specific hardware before committing money.