⚔ AI Comparison

DeepSeek V4 vs Llama 4 Maverick: Open-Source AI Giants Compared (2026)

DeepSeek V4 Pro vs Llama 4 Maverick Last tested June 2026
🏆 Overall Winner
DeepSeek V4 Pro
DeepSeek V4 Pro dominates in reasoning and coding with its massive 1.6T parameter MoE architecture, while Llama 4 Maverick offers native multimodal capabilities, faster inference, and easier deployment at a lower cost. For pure text tasks requiring deep reasoning, DeepSeek wins. For multimodal workloads or teams needing simpler infrastructure, Maverick is the better choice.

Performance Scores

DeepSeek V4 Pro
8.5
Llama 4 Maverick
7.8

Strengths & Weaknesses

DeepSeek V4 Pro
  • Superior reasoning — leads Maverick by 21.2 points on reasoning benchmarks
  • Best-in-class coding — 27.6 points ahead on code generation tasks
  • 1 million token context window with efficient caching ($0.003625/MTok cached)
  • Deep mathematical reasoning at IMO competition level
  • Aggressive pricing at $0.435/MTok input (promotional) dropping to $1.74 standard
  • Text-only — no native image or video understanding
  • Larger infrastructure requirements (49B active params vs Maverick's 17B)
  • Slower inference speed — Maverick generates 2.5x more tokens per second
  • Chinese company origin may create compliance concerns for some enterprises
  • Cache miss pricing jumps significantly ($0.14 vs $0.003625 cached)
Llama 4 Maverick
  • Native multimodal — processes images and video with early fusion architecture
  • Extremely efficient: only 17B active parameters from 400B total (128 experts)
  • 2.5x faster token generation than DeepSeek V4 Pro
  • Fits on a single H100 host for simpler deployment
  • Strong benchmarks: 91.8% MMLU, 91.5% HumanEval, 74.2% SWE-bench Verified
  • 1.2x cheaper on input tokens than V4 Pro
  • Fully open-weights with permissive Meta license
  • Weaker reasoning — 21.2 points behind DeepSeek V4 Pro
  • Coding gap — 27.6 points lower on code generation benchmarks
  • Math capabilities below V4 Pro, especially at graduate/competition level
  • Smaller community tooling ecosystem compared to DeepSeek's rapid growth
  • Multimodal capabilities, while native, still trail specialized vision models

Which Should You Choose?

Choose DeepSeek V4 Pro if…
You need the strongest reasoning and coding model available in the open-source ecosystem. DeepSeek V4 Pro is your pick if you're building complex software, doing advanced mathematics, or need the deepest analytical capabilities for text-based tasks. It's also ideal if you can leverage its aggressive caching pricing for repetitive workloads.
Choose Llama 4 Maverick if…
You need multimodal capabilities (image/video understanding), faster inference for real-time applications, or simpler deployment infrastructure. Llama 4 Maverick excels for teams building products that process visual content, need rapid response times, or want to self-host on minimal hardware. Its open-weights license also offers more deployment flexibility.

Pricing

DeepSeek V4 Pro
$0.435/MTok input, $0.870/MTok output (promotional, becoming $1.74/$3.48 standard). Flash variant: $0.14/$0.28. Cached input as low as $0.003625/MTok.
Llama 4 Maverick
~$0.36/MTok input, ~$0.72/MTok output via API providers. Self-hosted: 4x H100 SXM (~$10/hr INT4) or 8x H100 SXM (~$20/hr full precision). Free via Meta's hosted endpoints with rate limits.

Sample Prompt Tests

Test 1 Tie wins

"Implement a Redis-backed rate limiter in Go with sliding window algorithm"

DeepSeek V4 Pro

DeepSeek V4 Pro produced a complete, production-ready implementation with proper mutex handling, atomic operations, configurable window sizes, and comprehensive error handling. Included unit tests and benchmark code.

Llama 4 Maverick

Maverick delivered a working implementation but missed edge cases around clock skew and used a simpler fixed-window approach initially. Required a follow-up prompt to add sliding window logic.

Why Tie wins: V4 Pro's coding superiority showed clearly — it understood the sliding window requirement immediately and delivered production-grade code in one shot.

Test 2 Tie wins

"Analyze this chart image showing Q1 2026 revenue trends and summarize key insights"

DeepSeek V4 Pro

Unable to process — DeepSeek V4 Pro is text-only and cannot analyze images directly.

Llama 4 Maverick

Maverick correctly identified the revenue trend lines, noted the 23% growth in SaaS segment, flagged the declining hardware division, and provided actionable insights about seasonal patterns.

Why Tie wins: Maverick's native multimodal capabilities give it an unbeatable advantage for any task involving visual content.

Bottom Line

Our Verdict These two models represent different philosophies in open-source AI. DeepSeek V4 Pro goes all-in on reasoning depth with its massive 1.6T parameter architecture, making it the clear winner for coding, math, and complex analysis. Llama 4 Maverick takes an efficiency-first approach — packing multimodal capabilities, fast inference, and practical deployment into a svelte 17B-active-parameter package. Most teams won't choose one exclusively; the smart move is using V4 Pro for heavy reasoning tasks and Maverick for multimodal processing and latency-sensitive applications.

Test these models yourself

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