Specifications
Context Window
164K tokens
Input Price/1M
$0.27
Output Price/1M
$0.41
Parameters
—
Max Output
66K tokens
Benchmarks
DeepSeek V3.2 Exp results on the main AI model evaluation benchmarks. Higher scores indicate better performance.
Coding
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| LiveCodeBench | 78.9 | 100.0 | Artificial Analysis official API |
| LiveBench Coding | 73.2 | 100.0 | Contamination-free benchmark with objective ground-truth answers |
| AA Coding Index | 33.3 | 100.0 | Artificial Analysis official API |
Data Analysis
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| LiveBench Data Analysis | 44.3 | 100.0 | Contamination-free benchmark with objective ground-truth answers |
Language
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| LiveBench Language | 65.6 | 100.0 | Contamination-free benchmark with objective ground-truth answers |
Math
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| AIME 2025 | 87.7 | 100.0 | Artificial Analysis official API |
| AA Math Index | 87.7 | 100.0 | Artificial Analysis official API |
| LiveBench Math | 64.4 | 100.0 | Contamination-free benchmark with objective ground-truth answers |
overall
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| LMArena Elo | 1423.0 | 2000.0 | Crowdsourced blind pairwise comparisons |
| LiveBench Global | 49.9 | 100.0 | Contamination-free benchmark with objective ground-truth answers |
| AA Intelligence Index | 32.9 | 100.0 | Artificial Analysis official API |
Reasoning
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| MMLU Pro | 85.0 | 100.0 | Artificial Analysis official API |
| GPQA Diamond | 79.7 | 100.0 | Artificial Analysis official API |
| LiveBench Reasoning | 45.5 | 100.0 | Contamination-free benchmark with objective ground-truth answers |
Information
- Release date
- September 29, 2025
- Tool Calling
- ❌ Not supported
- Vision
- ❌ Not supported
- Audio
- ❌ Not supported
Full Analysis: DeepSeek V3.2 Exp
What is DeepSeek V3.2 Exp?
DeepSeek V3.2 Exp is an AI model developed by DeepSeek, classified as a large language model (LLM). It focuses on text processing and natural language generation. As an open source model, it is available for download, customization, and on-premises deployment. With a context window of 164K tokens, it is suitable for processing long documents such as contracts, books, and complete codebases.
Pricing & Costs in 2026
DeepSeek V3.2 Exp is usage-based, priced at $0.27/1M input tokens and $0.41/1M output tokens. For context: 1 million tokens is approximately 750,000 words, or about 10 average-length books. At this aggressive price point, it is one of the most cost-effective options on the market, ideal for high-volume applications like chatbots, bulk document analysis, and automation.
Benchmarks & Performance
DeepSeek V3.2 Exp was evaluated on 14 different benchmarks, covering categories like Coding, Data Analysis, Language, Math, overall, Reasoning. Results show exceptional performance across available evaluations.
It's important to note that benchmarks measure specific aspects and don't capture the full user experience. Factors like instruction adherence, behavior in long conversations, and real-world task quality vary significantly between models and aren't always reflected in standard scores.
Recommended Use Cases
DeepSeek V3.2 Exp is suitable for a wide range of AI applications: long document analysis (contracts, legal proceedings, codebases), high-volume chatbots and automated support, text generation, summarization, translation, and general assistance.
Comparison with Alternatives
In the 2026 AI model ecosystem, DeepSeek V3.2 Exp competes directly with similarly capable models. DeepSeek competes in this segment against OpenAI, Anthropic, Google, and Meta. The choice between models depends on the specific use case, budget, latency requirements, and need for features like multimodality and tool calling.
For a detailed side-by-side comparison, use our comparison tool or check the overall model ranking.
Frequently Asked Questions
What is DeepSeek V3.2 Exp?
DeepSeek V3.2 Exp is an AI model developed by DeepSeek. It is a language model (LLM), open source.
How much does DeepSeek V3.2 Exp cost?
DeepSeek V3.2 Exp costs $0.27/1M input tokens and $0.41/1M output tokens. For heavy usage (e.g., a chatbot handling 100k messages/month), costs can range from $10 to $1,000 depending on volume.
How does DeepSeek V3.2 Exp compare with other models?
In available benchmarks, DeepSeek V3.2 Exp scored: LiveCodeBench: 78.9/100, LiveBench Coding: 73.19/100, AA Coding Index: 33.3/100. See the full table above for a detailed comparison.
Is DeepSeek V3.2 Exp open source?
Yes, DeepSeek V3.2 Exp is an open source model. You can deploy it on-premises, customize it via fine-tuning, and maintain full control over your data. Check the official repository for the specific license.
What is DeepSeek V3.2 Exp best for?
DeepSeek V3.2 Exp excels at general-purpose language tasks. With its large context window, it handles long documents, codebases, and extended conversations.
Last updated: June 01, 2026 • View methodology →