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DeepSeek-V3.2 (Thinking) vs Gemini 4 Argon

Gemini 4 Argon leads the LLM Stats Score 55.4 to 32.5.

DeepSeek · Google · Updated for 2026

Which is better?

Gemini 4 Argon leads the overall LLM Stats Score 55.4 to 32.5, ranking #4 overall.

Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose DeepSeek-V3.2 (Thinking)

  • you need open weights you can self-host or fine-tune

Choose Gemini 4 Argon

  • overall performance matters — it scores 55.4 and ranks #4 on LLM Stats
  • your work emphasizes reasoning and coding — it leads those capability indexes
  • you want the most recent training data — it shipped Sep 2026

At a glance

The differences that matter most.

DeepSeek-V3.2 (Thinking)
DeepSeek
Gemini 4 Argon
Google
Core performance indexes
LLM Stats Score
32.5
#118
55.4
#4
Reasoning
32.5
#114
53.3
#6
Coding
22.6
#92
43.0
#7
Agents
11.1
#124
40.9
#4
Cost, coverage & limits
Benchmark wins
—
—
Input price
$0.28 / M
— / M
Output price
$0.42 / M
— / M
Context window
131,072
—

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
DeepSeek-V3.2 (Thinking)
Gemini 4 Argon
Tool use
9.8#139
31.8#5
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

14 reported for DeepSeek-V3.2 (Thinking) · 19 for Gemini 4 Argon

No common benchmarks found

DeepSeek-V3.2 (Thinking) and Gemini 4 Argondon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Human preference

Blind head-to-head votes and playground preference scores

Context Window

Maximum input and output token capacity

Only DeepSeek-V3.2 (Thinking) specifies input context (131,072 tokens). Only DeepSeek-V3.2 (Thinking) specifies output context (65,536 tokens).

DeepSeek
DeepSeek-V3.2 (Thinking)
Input131,072 tokens
Output65,536 tokens
Google
Gemini 4 Argon
Input- tokens
Output- tokens
Fri Oct 16 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Gemini 4 Argon supports multimodal inputs, whereas DeepSeek-V3.2 (Thinking) does not.

Gemini 4 Argon can handle both text and other forms of data like images, making it suitable for multimodal applications.

DeepSeek-V3.2 (Thinking)

Text
Images
Audio
Video

Gemini 4 Argon

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V3.2 (Thinking) is licensed under MIT, while Gemini 4 Argon uses a proprietary license.

License differences may affect how you can use these models in commercial or open-source projects.

DeepSeek-V3.2 (Thinking)

MIT

Open weights

Gemini 4 Argon

Proprietary

Closed source

Release Timeline

When each model was launched

DeepSeek-V3.2 (Thinking) was released on 2025-12-01, while Gemini 4 Argon was released on 2026-09-30.

Gemini 4 Argon is 10 months newer than DeepSeek-V3.2 (Thinking).

DeepSeek-V3.2 (Thinking)

Dec 1, 2025

10 months ago

Gemini 4 Argon

Sep 30, 2026

1 weeks ago

10mo newer

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

Outputs Comparison

Notice missing or incorrect data?

Judge for yourself.

Run your own prompts against DeepSeek-V3.2 (Thinking) and Gemini 4 Argon side-by-side, then vote on the output you prefer.

DeepSeek-V3.2 (Thinking)
✓ Preferred
Gemini 4 Argon
Open in Playground

FAQ

Common questions about DeepSeek-V3.2 (Thinking) vs Gemini 4 Argon.

Which is better, DeepSeek-V3.2 (Thinking) or Gemini 4 Argon?

Gemini 4 Argon leads the LLM Stats Score 55.4 to 32.5. DeepSeek-V3.2 (Thinking) is made by DeepSeek and Gemini 4 Argon is made by Google. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does DeepSeek-V3.2 (Thinking) compare to Gemini 4 Argon in benchmarks?

DeepSeek-V3.2 (Thinking) scores AIME 2025: 93.1%, HMMT 2025: 90.2%, MMLU-Pro: 85.0%, LiveCodeBench: 83.3%, GPQA: 82.4%. Gemini 4 Argon scores Graphwalks BFS <128k: 99.7%, Vibe Code Bench: 91.9%, LVBench: 91.7%, LABBench2: 88.8%, Graphwalks BFS >128k: 84.2%.

What are the context window sizes for DeepSeek-V3.2 (Thinking) and Gemini 4 Argon?

DeepSeek-V3.2 (Thinking) supports 131K tokens and Gemini 4 Argon supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between DeepSeek-V3.2 (Thinking) and Gemini 4 Argon?

Key differences include LLM Stats Score (32.5 vs 55.4), multimodal support (no vs yes), licensing (MIT vs Proprietary). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V3.2 (Thinking) and Gemini 4 Argon?

DeepSeek-V3.2 (Thinking) is developed by DeepSeek and Gemini 4 Argon is developed by Google.

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