DeepSeek V4

DeepSeek V4 vs GPT-5.4 vs Claude 4.6 vs Gemini 3.1 Pro: 2026 AI Model Showdown

Head-to-head comparison of 2026's frontier AI models. The now-released DeepSeek V4 hits 80.6% SWE-bench, ships a 1M context, and is MIT open-source at ~5-30x lower cost than GPT-5.4, Claude 4.6, and Gemini 3.1 Pro.

Benchmarks
DeepSeek Research Team2026-04-2710 min read
#DeepSeek V4#GPT-5.4#Claude 4.6#Gemini 3.1#AI Comparison#Benchmarks

DeepSeek V4 vs GPT-5.4 vs Claude 4.6 vs Gemini 3.1 Pro: 2026 AI Model Showdown

April 2026 marks a watershed moment in AI. Four frontier models are now competing head-to-head: OpenAI's GPT-5.4, Anthropic's Claude 4.6, Google's Gemini 3.1 Pro, and the newly released DeepSeek V4 — which launched and open-sourced (MIT license) on April 24, 2026. Each brings distinct strengths, but DeepSeek V4's combination of top-tier coding performance, open weights, a 1M-token context, and radically lower pricing positions it as the most disruptive entry in the field.

This article provides a comprehensive, data-driven comparison across every dimension that matters for developers, enterprises, and researchers.

Release Timeline

ModelRelease DateDeveloperStatus
Claude 4.6 (Opus)February 5, 2026AnthropicAvailable
Gemini 3.1 ProFebruary 19, 2026Google DeepMindAvailable
GPT-5.4March 5, 2026OpenAIAvailable
DeepSeek V4April 24, 2026DeepSeekReleased (open-source)

The competitive landscape has intensified dramatically. Within a roughly ten-week window, all four major AI labs have shipped their flagship models — and DeepSeek V4 is the only one that arrived fully open-source.

Benchmark Comparison

SWE-bench: Real-World Software Engineering

SWE-bench measures a model's ability to solve real GitHub issues from popular open-source repositories — the gold standard for evaluating practical coding capability.

ModelSWE-bench ScoreNotes
DeepSeek V480.6%Highest among open models, tied with Gemini 3.1 Pro
Claude 4.680.8%Closed-source leader
Gemini 3.1 Pro80.6%Tied with V4
GPT-5.477.2%Solid but trailing

DeepSeek V4 posts a measured 80.6% on SWE-bench Verified — the highest score of any open-source model and tied with Gemini 3.1 Pro at the frontier. Crucially, it reaches this top tier while being the only model you can download and self-host.

Multi-Benchmark Overview

BenchmarkDeepSeek V4 (measured)GPT-5.4Claude 4.6Gemini 3.1 Pro
SWE-bench Verified80.6%77.2%80.8%80.6%
MMLU-Pro87.5%92.3%91.5%90.8%
GSM8K92.6%93.8%92.1%91.5%
LiveCodeBench93.593.591.890.2
GPQA Diamond90.1%72.1%71.5%69.8%
Codeforces3206

DeepSeek V4's measured results put it solidly at the frontier on coding and reasoning (LiveCodeBench 93.5, Codeforces 3206, GPQA Diamond 90.1%), with competitive scores across the board.

Pricing Comparison

This is where DeepSeek V4 creates the most significant disruption. V4 ships in two variants, and the pricing below reflects the long-term rates after a 75% cut.

API Pricing (per million tokens)

ModelInput PriceOutput Price
DeepSeek V4-Flash$0.14$0.28
DeepSeek V4-Pro$0.435$0.87
Gemini 3.1 Pro$2.00$12.00
GPT-5.4$2.50$15.00
Claude 4.6 (Opus)$5.00$25.00

Monthly Cost Estimate (10M tokens/day workload)

ModelMonthly CostAnnual Savings vs. V4-Pro
DeepSeek V4-Pro~$130Baseline
Gemini 3.1 Pro$2,100~$23,640
GPT-5.4$2,625~$29,940
Claude 4.6$4,500~$52,440

For a typical enterprise processing 10 million tokens daily, switching from Claude 4.6 to DeepSeek V4-Pro would save over $52,000 per year — with comparable performance on most tasks. Across the lineup, V4 lands roughly 5-30x cheaper than the closed-source frontier, and even cheaper on the V4-Flash tier.

Context Window Comparison

ModelContext WindowTechnology
DeepSeek V41M tokensHybrid attention (CSA + HCA)
GPT-5.41.05M tokensStandard attention
Claude 4.61M tokensStandard attention
Gemini 3.1 Pro1M tokensStandard attention

All four models offer roughly 1-million-token context windows, but DeepSeek V4's hybrid attention architecture — combining Compressed Sparse Attention (CSA) and Heavily Compressed Attention (HCA) — makes that context dramatically cheaper to run.

What This Means in Practice

  • Standard attention (GPT-5.4 / Claude 4.6 / Gemini 3.1): Processing 1M tokens grows costly and slow as context expands.
  • DeepSeek V4: At 1M context, per-token compute is roughly 27% of V3.2 and KV-cache memory is about 10% of V3.2. That efficiency is what lets V4 offer frontier-length context at a fraction of the cost.

Capability Focus

CapabilityDeepSeek V4GPT-5.4Claude 4.6Gemini 3.1 Pro
Text GenerationYesYesYesYes
Code / Agentic CodingYes (strength)YesYesYes
Math / ReasoningYes (strength)YesYesYes
Ultra-long ContextYes (1M, low cost)YesLimitedYes
Image UnderstandingLimitedYesYesYes
Video UnderstandingNoYesNoYes

DeepSeek V4 is positioned around text, code, and reasoning — its headline strengths are agentic coding, a 1M-token context, CSA+HCA efficiency, full open weights, and rock-bottom pricing. For image generation, video understanding, and other broad multimodal work, GPT-5.4 and Gemini 3.1 Pro remain the more complete choices.

Open Source vs. Closed Source

AspectDeepSeek V4GPT-5.4Claude 4.6Gemini 3.1 Pro
Open SourceYes (MIT)NoNoNo
Model WeightsPublicClosedClosedClosed
Local DeploymentYesNoNoNo
Fine-tuningUnrestrictedLimited APILimited APILimited API
Data PrivacyFull controlCloud-onlyCloud-onlyCloud-only
Vendor Lock-inNoneHighHighHigh

DeepSeek V4 is the only frontier-class model that ships fully open-source — MIT license, weights published on Hugging Face. This has profound implications:

  • Data Sovereignty: Enterprises in regulated industries (finance, healthcare, government) can run V4 entirely on-premises, ensuring no data leaves their infrastructure.
  • Customization: Fine-tune V4 for specific domains without API limitations.
  • Cost Control: No per-token fees when running on your own hardware.
  • Transparency: Full model inspection for safety, bias, and compliance auditing.

Architecture & Local Deployment

DeepSeek V4 uses a Mixture-of-Experts design and ships in two variants:

  • DeepSeek-V4-Pro: 1.6T total parameters, 49B active — for high-end reasoning and agentic coding.
  • DeepSeek-V4-Flash: 284B total parameters, 13B active — for faster, lower-cost workloads.

Its open weights enable local deployment — something impossible with GPT-5.4, Claude 4.6, or Gemini 3.1 Pro.

Hardware Requirements (Estimated, V4-Pro)

ConfigurationGPU SetupUse Case
Full Precision (FP16)Multi-node H100 clusterResearch, maximum quality
Mixed Precision (FP8)8x H100 80GBProduction, recommended
Quantized (INT4)4x H100 80GBCost-optimized deployment
Flash variant (FP8)2x H100 80GBSmaller, lower-latency serving

For comparison, the closed-source alternatives are API-only:

  • GPT-5.4: $2.50-$15.00/M tokens
  • Claude 4.6: $5.00-$25.00/M tokens
  • Gemini 3.1 Pro: $2.00-$12.00/M tokens

Unique Strengths of Each Model

DeepSeek V4

  • Best Value: ~5-30x cheaper than competitors with frontier-level performance
  • Open Source: Full MIT license, local deployment
  • Agentic Coding: 80.6% SWE-bench Verified — highest among open models, tied with Gemini 3.1 Pro
  • CSA+HCA Efficiency: 1M context at ~27% compute and ~10% KV-cache memory vs. V3.2
  • Chinese Language: Superior performance on Chinese NLP tasks

GPT-5.4

  • Ecosystem: Most mature plugin and integration ecosystem
  • Brand Trust: Widely adopted across enterprise and consumer markets
  • Multimodal Polish: Well-integrated image generation via DALL-E 4
  • Agent Capabilities: Strong function calling and tool use

Claude 4.6

  • SWE-bench Leader: Highest score (80.8%) on real-world coding tasks
  • Safety: Industry-leading alignment and safety guardrails
  • Long-form Writing: Exceptional quality for extended text generation
  • Instruction Following: Best-in-class adherence to complex instructions

Gemini 3.1 Pro

  • Native Multimodal: Best-integrated cross-modal capabilities
  • Video Understanding: Strongest video analysis of any model
  • Google Integration: Deep ties to Google Cloud, Search, and Workspace
  • Competitive Pricing: Most affordable among closed-source options

Which Model Should You Choose?

Choose DeepSeek V4 if:

  • Cost efficiency is a primary concern
  • You need open-source flexibility or local deployment
  • Agentic coding and repository-level tasks are core (80.6% SWE-bench)
  • Data privacy and sovereignty are requirements
  • You process extremely long contexts regularly

Choose GPT-5.4 if:

  • You need the broadest ecosystem of integrations and plugins
  • Brand recognition and enterprise trust matter
  • You rely heavily on image generation capabilities
  • You need the most mature agent/function-calling framework

Choose Claude 4.6 if:

  • Safety and alignment are top priorities
  • You need the best long-form writing quality
  • Complex instruction following is critical

Choose Gemini 3.1 Pro if:

  • Video understanding is a core requirement
  • You are deeply integrated with Google Cloud
  • You want competitive pricing among closed-source options
  • Native multimodal capabilities matter most

Recommended Hybrid Strategy

For organizations with diverse AI needs, a multi-model approach often delivers the best results:

Task CategoryRecommended ModelReasoning
High-volume API callsDeepSeek V4~5-30x cost savings
Code generation/debuggingDeepSeek V4 or Claude 4.6Top SWE-bench scores
Image generationGPT-5.4 or Gemini 3.1Best visual output
Video analysisGemini 3.1 ProNative video support
Sensitive data processingDeepSeek V4 (local)On-premises deployment
Chinese contentDeepSeek V4Superior Chinese NLP

Conclusion

The 2026 frontier AI landscape offers more choice and competition than ever before. While GPT-5.4, Claude 4.6, and Gemini 3.1 Pro each excel in specific areas, DeepSeek V4 stands out as the most versatile option — matching frontier coding performance (80.6% SWE-bench, tied with Gemini 3.1 Pro) while being open-source and roughly 5-30x more affordable.

For the majority of use cases, DeepSeek V4 represents the best combination of performance, price, and flexibility available in 2026.


Sources

Last updated: April 27, 2026

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