DeepSeek V4 Pro 0423

Facts

Released

2026-04-22 the day the repository was first published on Hugging Face Hugging Face, read 2026-09-24

Licence

mit the licence the model card declares Hugging Face, read 2026-09-24

Open weights

Yes the weights are published in this Hugging Face repository Hugging Face, read 2026-09-24

Parameters

1.60 trillion counted from the safetensors weight files Hugging Face, read 2026-09-24

Active parameters

75.6 billion estimate estimated from the expert counts and sizes in the configuration model configuration, read 2026-09-24

Knowledge cutoff

Unknown

Context window

• 1,048,576 tokens the maximum position embeddings in the model configuration model configuration, read 2026-09-24
• 1,048,576 tokens the context length OpenRouter lists OpenRouter, read 2026-09-24

Longest output

• 384,000 tokens the largest output OpenRouter's first provider allows OpenRouter, read 2026-09-24

Tool calling

• Yes OpenRouter lists tools among the supported parameters OpenRouter, read 2026-09-24

Structured output

• Yes OpenRouter lists structured outputs among the supported parameters OpenRouter, read 2026-09-24

Reasoning controls

• Yes OpenRouter lists reasoning controls, with the efforts xhigh, high OpenRouter, read 2026-09-24

Inputs and outputs

text in, text out Hugging Face, read 2026-09-24

Good for

• Reasoning: OpenRouter lists reasoning controls for it OpenRouter, read 2026-09-24

Prices

Run it on your own hardware

Weights are the sizes of the files a source lists, or an estimate from the parameter count where none does. Memory is an estimate: weights plus KV cache plus 512 MiB and 5 percent of the weights for runtime buffers. Check it against your hardware.

Start it with a local runtime

• Ollama

  ollama run hf.co/teamblobfish/DeepSeek-V4-Pro-GGUF:Q4_K_M

• LM Studio

  lms get teamblobfish/DeepSeek-V4-Pro-GGUF
  lms server start

• llama.cpp server

  llama-server -hf teamblobfish/DeepSeek-V4-Pro-GGUF:Q4_K_M --jinja

• vLLM

  vllm serve deepseek-ai/DeepSeek-V4-Pro

• SGLang

  sglang serve --model-path deepseek-ai/DeepSeek-V4-Pro --port 30000

Use it from your harness

Set up for Abacus with the model deepseek-ai/DeepSeek-V4-Pro. Each endpoint page has the same setup for its own address.

{
  "$schema": "https://opencode.ai/config.json",
  "provider": {
    "abacus": {
      "npm": "@ai-sdk/openai-compatible",
      "name": "Abacus",
      "options": {
        "baseURL": "https://routellm.abacus.ai/v1",
        "apiKey": "{env:ABACUS_API_KEY}"
      },
      "models": {
        "deepseek-ai/DeepSeek-V4-Pro": {
          "name": "DeepSeek V4 Pro 0423",
          "limit": {
            "context": 1048576,
            "output": 384000
          }
        }
      }
    }
  }
}

{
  "providers": {
    "abacus": {
      "baseUrl": "https://routellm.abacus.ai/v1",
      "api": "openai-completions",
      "apiKey": "$ABACUS_API_KEY",
      "models": [
        {
          "id": "deepseek-ai/DeepSeek-V4-Pro"
        }
      ]
    }
  }
}

Other ways to reach it

• ai&, model deepseek-ai/deepseek-v4-pro
• Baseten, model deepseek-ai/DeepSeek-V4-Pro
• DeepInfra, model deepseek-ai/DeepSeek-V4-Pro
• GMI Cloud, model deepseek-ai/DeepSeek-V4-Pro
• Hugging Face, model deepseek-ai/DeepSeek-V4-Pro
• Nebius Token Factory, model deepseek-ai/DeepSeek-V4-Pro
• Nvidia, model deepseek-ai/deepseek-v4-pro
• Pioneer, model deepseek-ai/DeepSeek-V4-Pro
• SiliconFlow, model deepseek-ai/DeepSeek-V4-Pro
• SiliconFlow (China), model deepseek-ai/DeepSeek-V4-Pro
• Together AI, model deepseek-ai/DeepSeek-V4-Pro

Published results

These are results other people published. Baltor did not run them and does not rank models by them.

• Results the maker published on the model card published by deepseek-ai Hugging Face, read 2026-09-24
• Artificial Analysis Intelligence Index: 30.4 published by Artificial Analysis OpenRouter, read 2026-09-24
• Artificial Analysis Coding Index: 59.4 published by Artificial Analysis OpenRouter, read 2026-09-24
• Artificial Analysis Agentic Index: 26.3 published by Artificial Analysis OpenRouter, read 2026-09-24