Model passport
DeepSeek: DeepSeek V3
deepseek-chat-v3- Open weights
- 684.5B params
- 163,840 context
- Released 2024-12-26(curated)
How to run it
Run it yourself
Repositorydeepseek-ai/DeepSeek-V3
Parameters684.5B
ArchitectureDeepseekV3ForCausalLM
Transformers
from transformers import AutoModelForCausalLM, AutoTokenizer
model_id = "deepseek-ai/DeepSeek-V3"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(model_id)Ollama
We don't sync Ollama tags, so we won't print a command we can't verify — a wrong one would pull the wrong model. Search the Ollama library →
Unsloth fine-tuning recipes are model-specific and we don't derive them here. Unsloth docs →
Use it hosted
API model ID
deepseek/deepseek-chatContext length163,840 tokens
Max output16,384 tokens
Input price$0.32 per 1M tokens
Output price$0.89 per 1M tokens
Example request
curl https://openrouter.ai/api/v1/chat/completions \
-H "Authorization: Bearer $OPENROUTER_API_KEY" \
-H "Content-Type: application/json" \
-d '{"model":"deepseek/deepseek-chat","messages":[{"role":"user","content":"Hello"}]}'Identifiers, limits and prices are synced from the upstream source shown above. Any field we haven't synced is left out entirely rather than guessed.
No benchmark we track has published a result for this model yet, so there is no score card — only the run guide above. It will appear here once any board we ingest scores it.