DeepSeek V4 Pro vs DeepSeek V3.2Benchmark Comparison 2026

Objective comparison based on public benchmarks updated weekly: Intelligence Index, GPQA Diamond, Chatbot Arena ELO, pricing and speed.

Overall winner (2026)

DeepSeek V4 Pro

5 of 8 criteria won

DeepSeek

DeepSeek V4 Pro

Winner

ELO Arena

1458

Intelligence Index

44.3

Coding Index

70.0

5 criteria won

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DeepSeek

DeepSeek V3.2

ELO Arena

1425

Intelligence Index

24.7

Coding Index

75.7

3 criteria won

View full profile

Detailed Comparison

CritérioDeepSeek V4 ProDeepSeek V3.2
Chatbot Arena ELO14581425
Intelligence Index (AA)44.324.7
Coding Index (AA)70.075.7
GPQA Diamond91.0%75.0%
Input price ($/1M tok)$0.43$0.28
Output price ($/1M tok)$0.87$0.42
Context window1.0M tokens164K tokens
Speed (tokens/s)65 tok/s

✓ = winner in this criterion • Source: Artificial Analysis, LMArena, official APIs • Updated weekly

Technical Specifications

DeepSeek V4 Pro

Company
DeepSeek
Context window
1.0M tokens
Input ($/1M tok)
$0.43
Output ($/1M tok)
$0.87
Speed
65 tok/s
Release
Apr 2026
Multimodal
No
Open Source
Yes
Official website
Visit

DeepSeek V3.2

Company
DeepSeek
Context window
164K tokens
Input ($/1M tok)
$0.28
Output ($/1M tok)
$0.42
0
Release
Dec 2025
Multimodal
No
Open Source
Yes
Official website
Visit

When to use DeepSeek V4 Pro vs DeepSeek V3.2?

Choosing between DeepSeek V4 Pro and DeepSeek V3.2 depends on your use case, budget and technical requirements. Below, a practical guide based on benchmark data and each model's specifications.

Use DeepSeek V4 Pro when:

DeepSeek · Text · Open Source

  • High-volume token projects — at $0.435/1M input tokens, the cost per call is low enough for production use at scale
  • Self-hosted projects with privacy requirements — ideal for sensitive data that cannot leave your own infrastructure
  • Long document analysis — 1.0M tokens context window allows processing books, legal databases and extensive logs
  • AI agents with tool calling — workflow automation, external API integration and data pipelines
View full DeepSeek V4 Pro profile

Use DeepSeek V3.2 when:

DeepSeek · Text · Open Source

  • Complex reasoning, math and advanced programming — reasoning models are optimized for problems requiring multiple logical steps
  • High-volume token projects — at $0.28/1M input tokens, the cost per call is low enough for production use at scale
  • Self-hosted projects with privacy requirements — ideal for sensitive data that cannot leave your own infrastructure
  • Long document analysis — 164K tokens context window allows processing books, legal databases and extensive logs
  • AI agents with tool calling — workflow automation, external API integration and data pipelines
View full DeepSeek V3.2 profile
SWEN Verdict: DeepSeek V4 Pro wins in more objective criteria in this comparison (5 vs 3). For most use cases, DeepSeek V4 Pro offers better aggregate performance — but DeepSeek V3.2 may be preferable if your project prioritizes complex reasoning, math and advanced programming.

Frequently Asked Questions

DeepSeek V4 Pro or DeepSeek V3.2: which is better?

DeepSeek V4 Pro wins in 5 of 8 criteria analyzed. Check the full table to choose based on your use case.

Where does this benchmark data come from?

Data is aggregated from Artificial Analysis (Intelligence Index, Coding Index) and Chatbot Arena/LMArena (ELO). Pricing and specs come from official APIs. Updated weekly.

What is the Intelligence Index?

The Intelligence Index is an aggregate score from Artificial Analysis that combines multiple academic benchmarks (MMLU, GPQA, LiveBench, etc.) into a single rating. The higher the score, the more capable the model is at reasoning tasks.

Is DeepSeek V4 Pro cheaper than DeepSeek V3.2?

No. DeepSeek V3.2 is cheaper: $0.28/1M input tokens vs $0.435/1M tokens for DeepSeek V4 Pro — a 55% difference. For high-volume projects, DeepSeek V3.2 can reduce costs substantially.

DeepSeek V4 Pro or DeepSeek V3.2: which has a larger context window?

DeepSeek V4 Pro has the larger context window: 1.0M tokens vs 164K tokens. For long document analysis, extensive transcripts or full codebases, the larger context window is a decisive criterion.

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