DeepSeek-V3.2 (Non-thinking) vs Gemini 4 Argon
Comparing DeepSeek-V3.2 (Non-thinking) and Gemini 4 Argon across benchmarks, pricing, and capabilities.
DeepSeek · Google · Updated for 2026
Which is better?
DeepSeek-V3.2 (Non-thinking) and Gemini 4 Argon trade strengths across price, capabilities, and technical limits. The better choice depends on the workload.
On price, DeepSeek-V3.2 (Non-thinking) is roughly 12.7x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Gemini 4 Argon also accepts a larger context window (1,048,576 input tokens), making it the stronger choice for long documents and large codebases.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose DeepSeek-V3.2 (Non-thinking)
- cost matters — it's about 12.7x cheaper per token
- you need open weights you can self-host or fine-tune
Choose Gemini 4 Argon
- you process long inputs — it offers a 1,048,576 token context window
- you want the most recent training data — it shipped Sep 2026
At a glance
The differences that matter most.
Individual benchmarks
0 reported for DeepSeek-V3.2 (Non-thinking) · 19 for Gemini 4 Argon
DeepSeek-V3.2 (Non-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
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek-V3.2 (Non-thinking) ($0.28/1M tokens) is 7.1x cheaper than Gemini 4 Argon ($2.00/1M tokens).
For output processing, DeepSeek-V3.2 (Non-thinking) ($0.42/1M tokens) is 23.8x cheaper than Gemini 4 Argon ($10.00/1M tokens).
In conclusion, Gemini 4 Argon is more expensive than DeepSeek-V3.2 (Non-thinking).*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Gemini 4 Argon accepts 1,048,576 input tokens compared to DeepSeek-V3.2 (Non-thinking)'s 131,072 tokens. Gemini 4 Argon can generate longer responses up to 1,048,576 tokens, while DeepSeek-V3.2 (Non-thinking) is limited to 8,192 tokens.
Input capabilities
Documented input modalities across available providers
Gemini 4 Argon supports multimodal inputs, whereas DeepSeek-V3.2 (Non-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 (Non-thinking)
Gemini 4 Argon
License
Usage and distribution terms
DeepSeek-V3.2 (Non-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.
MIT
Open weights
Proprietary
Closed source
Release Timeline
When each model was launched
DeepSeek-V3.2 (Non-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 (Non-thinking).
Dec 1, 2025
10 months ago
Sep 30, 2026
2 weeks ago
10mo newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
DeepSeek-V3.2 (Non-thinking) is available from DeepSeek. Gemini 4 Argon is available from Google.
DeepSeek-V3.2 (Non-thinking)
Gemini 4 Argon
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V3.2 (Non-thinking) and Gemini 4 Argon side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V3.2 (Non-thinking) vs Gemini 4 Argon.