DeepSeek V3.2vsDeepSeek-V3-0324
Across 8 shared benchmarks, DeepSeek V3.2 leads overall: DeepSeek V3.2 wins 8, DeepSeek-V3-0324 wins 0, with 0 ties and an average score difference of +31.50.
DeepSeek V3.2
DeepSeek-AI · 2025-12-01 · Reasoning model
DeepSeek-V3-0324
DeepSeek-AI · 2025-03-24 · AI model
DeepSeek V3.28 wins(100%)(0%)0 winsDeepSeek-V3-0324
Benchmark scores
Grouped by capability, sorted by largest gap within each. 8 shared benchmarks.
General Knowledge
DeepSeek V3.2 3/3| Benchmark | DeepSeek V3.2 | DeepSeek-V3-0324 | Diff |
|---|---|---|---|
| ARC-AGI | 5738 / 65Thinking (No Tools) | 959 / 65 | +48 |
| HLE | 25.1079 / 149Thinking (No Tools) | 5.20142 / 149 | +19.90 |
| GPQA Diamond | 82.4061 / 175Thinking (No Tools) | 68.40116 / 175 | +14 |
Specs
| Field | DeepSeek V3.2 | DeepSeek-V3-0324 |
|---|---|---|
| Publisher | DeepSeek-AI | DeepSeek-AI |
| Release date | 2025-12-01 | 2025-03-24 |
| Model type | Reasoning model | AI model |
| Architecture | MoE | MoE |
| Parameters | 6710.0 | 6710.0 |
| Context length | 128K | 128K |
| Max output | 8192 | Not available |
API pricing
Prices use DataLearner records when available; missing fields are not inferred.
| Item | DeepSeek V3.2 | DeepSeek-V3-0324 |
|---|---|---|
| Text input | Not public | 0.27 美元/100万 tokens |
| Text output | Not public | 1.1 美元/100万 tokens |
One or both models have incomplete public pricing.
Summary
- DeepSeek V3.2leads in:General Knowledge (3/3), Agent Level Benchmark (2/2), Coding and Software Engineer (2/2), Math and Reasoning (1/1)
On average across the 8 shared benchmarks, DeepSeek V3.2 scores 31.50 higher.
Largest single-benchmark gap: ARC-AGI — DeepSeek V3.2 57 vs DeepSeek-V3-0324 9 (+48).
Page generated from structured model, pricing and benchmark records. No real-time LLM is used to write the prose.