DeepSeek V3.2 Exp vs gpt-oss-120b (Comparative Analysis)
Loading comparison form...
Comparative Analysis: DeepSeek V3.2 Exp vs. gpt-oss-120b
Want to try out these models side by side?Try Magica for free
Overview
gpt-oss-120b was released 1 month before DeepSeek V3.2 Exp.
 DeepSeek V3.2 Exp |  gpt-oss-120b | |
|---|---|---|
Model Provider The organization behind this AI's development | DeepSeek | OpenAI |
Input Context Window Maximum input tokens this model can process at once | 163.8K tokens | 131.1K tokens |
Output Token Limit Maximum output tokens this model can generate at once | 65.5K tokens | 131.1K tokens |
Release Date When this model first became publicly available | September 29, 2025 10 months ago September 29th, 2025 | August 5, 2025 11 months ago August 5th, 2025 |
Knowledge Cutoff Latest training-data date reported by the provider | July 31, 2025 | June 30, 2024 |
Capabilities & Features
Compare supported features, modalities, and advanced capabilities
DeepSeek V3.2 Exp | gpt-oss-120b | |
|---|---|---|
Input Types Supported input formats | 📝Text | 📝Text |
Reasoning Controls Defaults and configurable reasoning effort | Optional | Always enabledEffort: High, Medium, LowDefault: Medium |
Output Types Supported output formats | 📝Text | 📝Text |
Tokenizer Text encoding system | DeepSeek | GPT |
Key Features Advanced capabilities | ✓Function Calling✓Structured Output✓Reasoning ModeContent Moderation | ✓Function Calling✓Structured Output✓Reasoning ModeContent Moderation |
Open Source Model availability | Available on HuggingFace → | Available on HuggingFace → |
Pricing
DeepSeek V3.2 Exp is roughly 6.8x more expensive compared to gpt-oss-120b for input tokens and roughly 2.4x more expensive for output tokens.
| DeepSeek V3.2 Exp | gpt-oss-120b | |
|---|---|---|
Input Token Cost Cost per million input tokens | $0.27 per million tokens | $0.04 per million tokens |
Output Token Cost Cost per million output tokens | $0.41 per million tokens | $0.17 per million tokens |
Benchmarks
Compare relevant benchmarks between DeepSeek V3.2 Exp and gpt-oss-120b.
| DeepSeek V3.2 Exp | gpt-oss-120b | |
|---|---|---|
Intelligence Index Overall model quality across independent evaluations | Benchmark not available. | 23.8 (Artificial Analysis index; higher is better) |
Coding Index Programming performance across independent evaluations | Benchmark not available. | 30.4 (Artificial Analysis index; higher is better) |
Agentic Index Ability to complete multi-step agentic tasks | Benchmark not available. | 13.2 (Artificial Analysis index; higher is better) |
Best Design Arena Score Highest human-preference Elo score across design arenas | 1,206 Elo (#43 in 3D (56.4% win rate)) | 1,050 Elo (#91 in Game Dev (40.6% win rate)) |
At a Glance
Quick overview of what makes DeepSeek V3.2 Exp and gpt-oss-120b unique.
DeepSeek V3.2 Exp by DeepSeek can use external tools and APIs, offers advanced reasoning, generates structured data. It can handle standard conversations with its 163.8K token context window. Very affordable at $0.27/M input and $0.41/M output tokens. Released September 29th, 2025.gpt-oss-120b by OpenAI can use external tools and APIs, offers advanced reasoning, generates structured data. It can handle standard conversations with its 131.1K token context window. Very affordable at $0.04/M input and $0.17/M output tokens. Released August 5th, 2025.Explore More Comparisons
Compare your models with top performers across different categories
Compare DeepSeek V3.2 Exp with:
🚀Programming
Best models for coding and development
🎨Creative & Roleplay
Models optimized for creative writing
📢Marketing
Content creation and marketing tasks
💻Technology
Technical analysis and explanations
🔬Science
Scientific research and analysis
🌐Translation
Multilingual translation tasks
Compare gpt-oss-120b with:
🚀Programming
Best models for coding and development
🎨Creative & Roleplay
Models optimized for creative writing
📢Marketing
Content creation and marketing tasks
💻Technology
Technical analysis and explanations
🔬Science
Scientific research and analysis
🌐Translation
Multilingual translation tasks