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FAN-MADE V4 GUIDE|NOT AFFILIATED WITH DEEPSEEK

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The complete, step-by-step tutorial directory for DeepSeek V4 Flash. Learn how to access official APIs, optimize costs, and connect LLMs to your apps — simplified for everyone. An independent fan-made resource, not run by DeepSeek.

OFFICIAL PRICE
$0.14 / 1M Input Tokens
MODEL SIZE
284B Total Params
CONTEXT
1M Tokens
DIFFICULTY
Beginner Friendly
Live Tracker|DeepSeek Harness
Updated Aug 16, 2026

DeepSeek Harness Developer Preview

DeepSeek's official agent framework — open source since Aug 13, 2026. The “Model + Harness = Agent” runtime where every capability is a plugin: models, tools, sandboxes, and even the agent loop itself. Model-agnostic, MIT-licensed, and directly positioned against Claude Code.

RELEASED
v0.1 Developer Preview

Shipped Aug 13, 2026 — source code open on the same day

OPEN SOURCE
MIT License

127K GitHub stars in 3 days · github.com/deepseek-ai/deepseek-harness

PLUGIN-FIRST
616 Community Plugins

Everything is a plugin — models, tools, sandboxes, even the agent loop

4 RUNTIME MODES
Standard · Code · Minimal · Creator

From full coding agent to two-tool benchmark mode — pick in config

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FEATURED GUIDES & TUTORIALS

34 ARTICLES
01
Model Guide9 MIN READ

What Is DeepSeek V4.1 Flash? The 552B MoE, Explained

The Sept 10, 2026 release: a 552B MoE with native vision, 8B/16B asymmetric activation, a 1M context, and an 890-byte-per-token KV cache.

02
Pricing7 MIN READ

DeepSeek V4.1 Flash Pricing: $0.003 Cache Hits & Peak Rates

$0.003 per 1M cached input tokens off-peak, $0.15 uncached, $0.60 output. Peak/off-peak table, cache math, and how it compares to GPT and Claude.

03
Benchmarks6 MIN READ

DeepSeek V4.1 Flash Benchmarks: Full Official Table

Every official score: Terminal-Bench 2.1 90.6, DeepSWE 74.2, CyberGym 88.1, plus the multi-scaffold table and the effort-cost caveat.

04
API Setup7 MIN READ

DeepSeek V4.1 Flash API Setup: Base URL, Model ID & Migration

Set model to deepseek-flash, keep your base URL, and migrate from old names. Includes a first curl call and reasoning-effort parameters.

05
Vision7 MIN READ

DeepSeek V4.1 Flash Vision: Native Multimodal Images

Native image understanding via a 32-layer DeepSeek-ViT: MMMU-Pro 56.5, DocVQA 95.6, and visual-agent scores, replacing V4-Flash-Vision-Exp.

06
Reasoning7 MIN READ

DeepSeek V4.1 Flash Reasoning Effort: The 1-100 Dial Explained

A continuous 1-100 effort scale, not just low/high/max. How the setting trades 2.5x output tokens for accuracy, and how to pick a level.

07
Migration7 MIN READ

DeepSeek Model Names & Retired IDs: The 2026 Alias Reference

Every DeepSeek model id, alias, and retirement status in one table — so a rerouted or deprecated name never breaks production.

08
Comparison9 MIN READ

DeepSeek V4.1 Flash vs V4 Flash: 552B, CED & the 94% Jump

The 94% backbone jump from 284B to 552B, the move from 13B to 8B/16B activation, a 4x smaller KV cache, and what it means for migration.

09
Comparison8 MIN READ

DeepSeek V4.1 Flash vs Claude Opus 5: DeepSWE & the Cost Gap

DeepSWE 74.2 vs 74.0 and CyberGym 88.1 vs none — but Opus 5 wins the harder Terminal-Bench 3.0/4.0. Open weights at a fraction of the price.

10
Comparison7 MIN READ

DeepSeek V4.1 Flash vs Kimi K3: The Open-Weight Duel

Two open-weight rivals compared: V4.1 Flash leads on agent and coding tests, Kimi K3 leads GPQA and HLE. Pricing and cache rates compared.

11
Upcoming8 MIN READ

DeepSeek V4.1 Pro: What We Know So Far

DeepSeek's next flagship has no release date. What the CED family implies, why V4-Pro traffic routes to Flash until it ships, and how to track it.

12
Local Setup8 MIN READ

Run DeepSeek V4.1 Flash Locally: VRAM, vLLM & Quantization

Download the MIT weights and serve them with vLLM: a 511 GB checkpoint, a 614 GB VRAM floor, GB200/H200 layouts, and DSpark.

13
Coding Agents6 MIN READ

DeepSeek V4.1 Flash for Coding Agents: OpenCode, Claude Code & Harness

Official setup for Claude Code, OpenCode, and OpenClaw, plus the DeepSeek Harness minimal mode used for the official agent benchmarks.

14
Technical7 MIN READ

DeepSeek V4.1 Flash KV Cache: 890 Bytes per Token Explained

How V4.1 Flash stores its KV cache in 890 bytes per token: CED projection, CSA2 layer modes, FP4 KV, SWA Bounded Replay, and the 72-hour cache.

15
Release7 MIN READ

DeepSeek V4 Pro Retired: Why It Routes to V4.1 Flash

From Sept 14, 2026, every deepseek-v4-pro request routes to V4.1 Flash at Flash rates. The timeline, official reasons, and developer pushback.

16
Model Guide8 MIN READ

What Is DeepSeek V4 Flash? Full Guide to the 0731 Release

A 284B-parameter open-weight MoE with 1M context. What the July 31, 2026 official release actually changed versus the preview.

17
API Integration7 MIN READ

DeepSeek V4 Flash API Setup: Base URL, Models & Your First Call

Step-by-step: create an API key, set the base URL, and make your first call with curl, Python, or Node.js.

18
Cost Optimization8 MIN READ

DeepSeek V4 Flash Pricing: Token Costs & How to Save (Aug 2026)

Official token pricing ($0.14 / $0.28 per 1M), the ~98% context-cache discount, and real savings vs GPT-5.5 and Claude.

19
Benchmarks7 MIN READ

DeepSeek V4 Flash Benchmarks: Agentic & Coding Scores in 2026

All nine official agentic benchmarks, the +645% DeepSWE jump, and how V4 Flash stacks up against GLM-5.2 and Opus-4.8.

20
Coding Agents7 MIN READ

Use DeepSeek V4 Flash with OpenCode: Step-by-Step

Connect the open-source OpenCode agent to DeepSeek V4 Flash in minutes with the official /connect deepseek flow.

21
Cursor & IDE8 MIN READ

DeepSeek V4 Flash in Cursor, Claude Code & Codex: Setup Guide

Configure DeepSeek V4 Flash in Cursor, Claude Code (ANTHROPIC_BASE_URL), and Codex with the official one-click script.

22
OpenRouter8 MIN READ

DeepSeek V4 Flash on OpenRouter: Setup, Pricing & BYOK

Two model slugs, third-party pricing, BYOK setup, and when to route through OpenRouter instead of the official API.

23
Model Size9 MIN READ

DeepSeek V4 Flash Model Size: Params, VRAM & What It Means

284B total / 13B active explained, weight sizes in FP4/FP8/BF16, and what GPU you actually need to run it.

24
Local Deployment7 MIN READ

Download DeepSeek V4 Flash from HuggingFace & Run It Locally

Download the MIT-licensed DeepSeek-V4-Flash-0731 weights from HuggingFace and serve them with vLLM.

25
V4 Pro9 MIN READ

DeepSeek V4 Pro: GA Release, Pricing & Benchmarks (0813)

1.6T-parameter flagship still in preview. Specs, official pricing, self-reported benchmarks, and the expected release window.

26
Beginner Guide8 MIN READ

Why DeepSeek V4 Is the Best Cheap AI Right Now: A Beginner Guide

Don't know model names? Here's why DeepSeek V4 is the best cheap AI to start with — plain-English, with honest limitations.

27
OpenCode Go8 MIN READ

OpenCode Go: The $5/Month Subscription That Unlocks DeepSeek V4

The $5/month subscription that unlocks DeepSeek V4 Flash and Pro — roughly 158K Flash requests a month for $10.

28
Claude Code8 MIN READ

Connect Claude Code & Claude Desktop to DeepSeek V4 with CC Switch

Point Claude Code & Claude Desktop at DeepSeek V4 using CC Switch — official env vars, Desktop dev mode, and Linux setup.

29
Upcoming8 MIN READ

DeepSeek Harness: Release, Install & Plugin Guide

DeepSeek's official agent framework is unreleased but every benchmark was measured on it. Everything we know so far.

30
Technical8 MIN READ

DeepSeek V4 Technical Report Explained: Architecture & Benchmarks

A guided tour of the DeepSeek V4 paper — CSA+HCA attention, Muon, 27% of V3.2's FLOPs, and how to read the model cards.

31
Harness9 MIN READ

Why a Native Harness Makes AI Agents Dramatically Better

Why 'Model + Harness = Agent' — the context management, tool loops, and self-correction that turn a raw model into a real agent.

32
Cost Hacks10 MIN READ

Reasonix: The DeepSeek Harness That Hits 99%+ Cache Rates

Reasonix hits 99%+ DeepSeek cache rates — 435M input tokens for $1.38 instead of $61. How the cache-first loop saves ~98%.

33
Hermes9 MIN READ

Hermes Best Setup: DeepSeek V4 Flash 0731 + MiMo V2.5 (Vision)

The community-verified best pairing for Hermes: DeepSeek V4 Flash 0731 as the text brain + MiMo V2.5 for vision.

34
Comparisons9 MIN READ

DeepSeek V4 vs GPT-5.6 Luna: Which Is Better After the Price Cut?

DeepSeek V4 Flash vs the price-cut GPT-5.6 Luna: AI Intelligence Index 50 vs 51, but 60% lower cost per task. Who wins by scenario.

QUICK INTEGRATION CODE SNIPPET

PYTHON 3.10+
quickstart.py
import os
from openai import OpenAI

# 100% OpenAI SDK compatible - just change the base_url
client = OpenAI(
    api_key=os.environ.get("DEEPSEEK_API_KEY"),
    base_url="https://api.deepseek.com"
)

response = client.chat.completions.create(
    model="deepseek-v4-flash",
    messages=[
        {"role": "system", "content": "You are a helpful coding assistant."},
        {"role": "user", "content": "What is the best practice to integrate DeepSeek V4?"}
    ],
    stream=True
)

for chunk in response:
    print(chunk.choices[0].delta.content or "", end="")
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FREQUENTLY ASKED QUESTIONS

QUICK ANSWERS

Is DeepSeek V4 Flash open source?

Yes. DeepSeek released the V4 Flash weights (284B total / 13B active, 1M context) under the MIT license on Hugging Face on July 31, 2026. You can download them for free or call them through the official API.

Download the weights

How much does DeepSeek V4 Flash cost?

The official API charges $0.14 per 1M input tokens and $0.28 per 1M output tokens, with a roughly 98% discount on context-cache hits ($0.0028 / 1M). That makes it dramatically cheaper than GPT-5.5 or Claude for most workloads.

Full pricing guide

Does DeepSeek V4 Flash support image input?

No — V4 Flash is text-only. For image support, community setups pair it with Xiaomi MiMo V2.5 in the vision slot, which bills at the same $0.14 / $0.28 per 1M rate.

Vision setup guide

What base URL do I use for the DeepSeek API?

Use https://api.deepseek.com. It is OpenAI-compatible (the /v1 prefix is optional), and DeepSeek also exposes an Anthropic-compatible endpoint at https://api.deepseek.com/anthropic for Claude Code and similar tools.

API setup guide

Can I run DeepSeek V4 Flash on my own hardware?

Yes, though it is heavy. The FP4/FP8 weights are about 160 GB, so you realistically need a multi-GPU setup (two RTX 3090s or better) or a large unified-memory machine. The official vLLM recipe is the recommended path.

VRAM & model size

Is this site run by DeepSeek?

No. DeepSeek V4 Guide is an independent, fan-made resource. We are not affiliated with or endorsed by DeepSeek. Always check status.deepseek.com and the official docs for production-critical information.

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