DeepSeek V4 Pro
DeepSeek V4 Pro publishes its weights, but at 1600B parameters (49B active per token) no consumer machine holds the checkpoint. This page covers the access paths that work and the open models that actually run locally.
Why you can't run DeepSeek V4 Pro locally
At 1600B parameters (49B active per token), a Q4-class build of DeepSeek V4 Pro would need roughly 960 GB — beyond any consumer machine. That figure is arithmetic, not opinion: 0.6 GB per billion parameters is the standard Q4 rule we apply across the whole catalog. The weights themselves are public (official source linked below); capacity, not licensing, is the wall.
What works instead: the hosted API. For most workloads, the open models below deliver the same job on hardware that fits under a desk.
Apr 24, 2026. 1.6T total, 49B active MoE. MIT license. Not realistically runnable on consumer Mac. API $0.87 per 1M output tokens (DeepSeek pricing page, Jul 2026).
What to run locally instead of DeepSeek V4 Pro
More DeepSeek models
Frequently asked questions
Can I run DeepSeek V4 Pro locally?
Not on hardware you can buy. The weights are public, but DeepSeek V4 Pro is a 1600B-parameter model (49B active), and a Q4-class build would need roughly 960 GB — beyond any consumer machine. Until the ecosystem ships a smaller official build, the API or a smaller open model is the practical path.
How do I access DeepSeek V4 Pro?
Through the vendor's hosted API. The official source is linked on this page.
What is the best local alternative to DeepSeek V4 Pro?
Qwen3 235B A22B is the strongest local model we track (235B, from 192 GB machines), with Qwen3.5 122B-A10B Instruct close behind. Both run on a single high-memory Mac or GPU — see their pages for exact hardware.
Cite this page
ModelFit: DeepSeek V4 Pro — specs, memory math and hardware verdicts. https://modelfit.io/models/deepseek-v4-pro/ (dataset updated 2026-09-03, CC BY 4.0).