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Key Highlights

  • Two models launched: deepseek-v4-pro (1.6T total / 49B active) and deepseek-v4-flash (284B total / 13B active), both MoE
  • 1M context: Full 1,000,000-token context across the family, powered by a new Hybrid Attention architecture + DSA sparse attention
  • Open-source SOTA: V4-Pro is the current best open-source model on Agentic Coding; scores 80.6 on SWE-Verified, matching Claude (80.8) and Gemini (80.6)
  • Tunable thinking: Supports reasoning_effort parameter (high / max); official guidance recommends max for complex agent scenarios
  • Dual API compatibility: Works with both the OpenAI ChatCompletions and Anthropic endpoints
  • Friendly pricing: Flash at $0.14 in / $0.28 out per 1M tokens; Pro at $1.74 in / $3.48 out — same as official
  • Recharge bonus: Stackable with API易 recharge promotions for an effective ~15% discount off the official list price
The version currently live on API易 is the Aliyun official relay channel. Release date: 2026-04-24 (official preview). Source: DeepSeek docs at api-docs.deepseek.com/zh-cn/news/news260424.

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Background

A full year after DeepSeek-R1 shook the industry, DeepSeek returned on April 24, 2026 with its V4 preview release — launching a performance flagship V4-Pro and a speed/cost-optimized V4-Flash simultaneously. The headline technical advance in V4 is the Hybrid Attention Architecture: attention is compressed along the token dimension and combined with DSA sparse attention, making long-context inference both efficient and accurate. Paired with a 1M-token context window, this generation is purpose-built for agents and long-horizon reasoning. DeepSeek is candid about its positioning versus closed frontier models: V4-Pro trails only Gemini-Pro-3.1 on world knowledge, and the overall gap with GPT-5.4 / Gemini-Pro-3.1 is “about 3 to 6 months” — the strongest catch-up yet from the open-source camp.

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Deep Dive

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The Two New Models

deepseek-v4-pro

Performance flagship1.6T total params / 49B active, MoE, 1M context. For complex agents, coding, math, STEM, and competitive-grade code. Agentic Coding is open-source SOTA.

deepseek-v4-flash

Speed + economy284B total / 13B active, MoE, 1M context. For high-throughput, latency-sensitive, cost-conscious workloads like chat, text ops, and batch tasks.

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Benchmark Highlights

Based on official and third-party evaluations:
DimensionDeepSeek-V4-ProCompetitor reference
SWE-Verified (real software engineering)80.6Claude 80.8 / Gemini 80.6
Agentic CodingOpen-source SOTAApproaches Claude Opus 4.5
World knowledgeOpen-source leaderOnly behind Gemini-Pro-3.1
Math / STEM / Competition codeBeats every public open-source model—
Overall gap vs. GPT-5.4 / Gemini-Pro-3.1~3-6 months—
In DeepSeek’s internal evaluation, V4-Pro-Max (max reasoning_effort) beats Claude Sonnet 4.5 on agent tasks and approaches Claude Opus 4.5.

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Architecture & Specs

Hybrid Attention Architecture

  • Token-level compression: A new attention mechanism compresses along the token axis, drastically lowering long-context inference cost
  • DSA sparse attention: Combined with sparse attention for better long-range dependency modeling
  • MoE experts: V4-Pro activates ~3% (49B/1.6T); V4-Flash activates ~4.6% (13B/284B)
  • 1M context: Full 1,000,000 tokens across the family — ideal for agents, repo-scale code, and long documents

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Thinking Modes & reasoning_effort

V4 supports both non-thinking and thinking modes. In thinking mode, reasoning_effort is tunable:
  • high: standard deep reasoning, for most complex tasks
  • max: maximum reasoning budget, officially recommended for complex agent scenarios
For complex agent tasks (long tool-use chains, repo-scale refactors, etc.), DeepSeek explicitly recommends thinking mode + reasoning_effort=max. Expect higher completion rates at the cost of more output tokens and latency.

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In Practice

Agents & tool use

V4-Pro-Max is the strongest open-source agent base today — great for Claude Code, Cline, and custom agent pipelines

Repo-scale coding

SWE-Verified 80.6 + 1M context: load a mid-to-large repo in a single call

Long-document analysis

Reports, legal docs, papers — 1M context + compressed attention keep costs friendly

High-throughput economy

V4-Flash at $0.14 / 1M tokens input: ideal for support bots, classification, translation

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Quickstart (OpenAI-compatible)

from openai import OpenAI

client = OpenAI(
    api_key="sk-your-apiyi-key",
    base_url="https://api.apiyi.com/v1"
)

# Flagship: V4-Pro at max reasoning effort for complex agents
resp = client.chat.completions.create(
    model="deepseek-v4-pro",
    messages=[
        {"role": "system", "content": "You are a senior full-stack engineer."},
        {"role": "user", "content": "Implement a circuit-breaker retry strategy for login in the existing repo."}
    ],
    extra_body={"reasoning_effort": "max"}
)
print(resp.choices[0].message.content)

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Economy Mode (Flash)

# High-throughput economy: V4-Flash, non-thinking by default, lowest latency
resp = client.chat.completions.create(
    model="deepseek-v4-flash",
    messages=[{"role": "user", "content": "Translate the following English text to Chinese: ..."}]
)

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Anthropic Endpoint

import anthropic

client = anthropic.Anthropic(
    api_key="sk-your-apiyi-key",
    base_url="https://api.apiyi.com"
)

msg = client.messages.create(
    model="deepseek-v4-pro",
    max_tokens=4096,
    messages=[{"role": "user", "content": "Design a rate-limiting scheme for a distributed queue."}]
)
print(msg.content[0].text)

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Best Practices

  • Model choice: Default to Flash; switch to Pro for agents / complex code / reasoning-heavy tasks
  • Thinking effort: Disable thinking for simple tasks; use reasoning_effort=max for heavy agent work
  • Long context: 1M is great, but input tokens are billed — pre-filter before feeding
  • Streaming: Thinking mode may emit many intermediate tokens — stream on the client for better UX

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Pricing & Availability

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Price Sheet (USD / 1M tokens)

ModelBillingPrompt (input)Completion (output)Prompt multiplierCompletion multiplier
deepseek-v4-flashPay-as-you-go - Chat$0.1400$0.28000.072.0000
deepseek-v4-proPay-as-you-go - Chat$1.7400$3.48000.872.0000
API易’s list price exactly matches DeepSeek’s official pricing — no markup. The channel is currently Aliyun official relay, with stability on par with direct-to-official access.

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Stack With Recharge Promotions

Recharge promotions bring effective cost down to roughly 85% of official. See:

Recharge Promotions

View the latest recharge bonus tiers — larger top-ups earn higher bonus ratios

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Summary & Recommendations

DeepSeek V4 is the strongest submission from the open-source camp in the past year:
  • ✅ Best open-source agent / coding model: V4-Pro is now the most capable open agent base — Claude-Sonnet-class performance at a fraction of the cost
  • ✅ Best cost-performance for long docs: Flash at $0.14 / 1M tokens input + 1M context is arguably the price-performance ceiling for long-doc workloads
  • ✅ Frictionless migration: OpenAI + Anthropic dual-endpoint support — change base_url and model, keep the rest
Recommended migration path:
  1. A/B your existing DeepSeek-V3 / R1 traffic onto V4-Flash
  2. Upgrade agent / coding tasks to V4-Pro with reasoning_effort=max
  3. Stack API易 recharge bonuses to cut another ~15% off the cost
Sources & dates
  • DeepSeek official: api-docs.deepseek.com/zh-cn/news/news260424
  • Third-party reports & reviews: simonwillison.net/2026/Apr/24/deepseek-v4/, thenextweb.com, felloai.com/deepseek-v4/, techxplore.com, digitalapplied.com
  • Data retrieved: 2026-04-24