DeepSeek V4 Pro

DeepSeek V4 Pro is a 1600B-parameter model you reach through an API, with 49B parameters active per token — too large to self-host, so this page covers what it does, how to access it, and what to run locally instead.

PARAMETERS

1600B (49B active)

FORMAT

API

RUNS LOCALLY

BEST FOR

Frontier reasoning, Coding

You don'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 (0.6 GB per billion parameters, our standard Q4 rule). Access is through the hosted API.

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).

Strong local alternatives

Qwen3 235B A22B

235B — runs on one machine

Qwen3.5 122B-A10B Instruct

122B — runs on one machine

DeepSeek-R1 671B

671B — runs on one machine

More DeepSeek models

DeepSeek-R1 Distill Qwen 7B DeepSeek-R1 Distill Qwen 14B DeepSeek-R1 Distill Llama 70B DeepSeek V4 Flash 0731 DeepSeek-R1 671B DeepSeek-V3 DeepSeek-V3-0324 DeepSeek-R1

Frequently asked questions

Can I run DeepSeek V4 Pro locally?

Not realistically. DeepSeek V4 Pro is a 1600B-parameter model (49B active); a Q4-class build would need roughly 960 GB — beyond any consumer machine. The hosted API or a smaller open model is the practical path.

How do I access DeepSeek V4 Pro?

Through the vendor-hosted API. See the official source 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). It runs on a single high-memory Mac or GPU; see its page 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).