Model comparison
DeepSeek V3.2 vs o3-mini
Head-to-head evidence from 5 shared benchmark results across 3 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: DeepSeek V3.2 #88 (Supported); o3-mini #141 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. DeepSeek V3.2 and o3-mini share 5 comparable benchmark results. 1 of 8 categories are comparable. 14 results are unique to DeepSeek V3.2; 5 to o3-mini.
Updated July 24, 2026- Shared results
- 5
- DeepSeek V3.2 only
- 14
- o3-mini only
- 5
- Comparable categories
- 1 / 8
Pick DeepSeek V3.2 if you want the stronger benchmark profile. o3-mini only becomes the better choice if you need the larger 200K context window or you want the stronger reasoning-first profile.
Confidence note. This is a partial-evidence comparison with 5 shared benchmark results across 3 evidence categories; 1 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
DeepSeek V3.2 is clearly ahead on the BenchAlign aggregate, 54.55 to 46.59. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
DeepSeek V3.2's sharpest advantage is in coding, where it averages 60.9 against 49.3.
o3-mini is also the more expensive model on tokens at $1.10 input / $4.40 output per 1M tokens, versus $0.28 input / $0.42 output per 1M tokens for DeepSeek V3.2. That is roughly 10.5x on output cost alone. o3-mini is the reasoning model in the pair, while DeepSeek V3.2 is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use. o3-mini gives you the larger context window at 200K, compared with 128K for DeepSeek V3.2.
Category breakdown
Exact category averages are shown below. Not measured means BenchLM does not have enough sourced public coverage for that model and category.
| Category | DeepSeek V3.2 | Δ | o3-mini |
|---|---|---|---|
| Coding | DeepSeek V3.260.9 | Margin← 11.6 | o3-mini49.3 |
| Knowledge | DeepSeek V3.2Not measured | MarginNo overlap | o3-mini77.2 |
| Math | DeepSeek V3.217.1 | MarginNo overlap | o3-miniNot measured |
| Inst. Following | DeepSeek V3.2Not measured | MarginNo overlap | o3-mini93.9 |
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | DeepSeek V3.2 | o3-mini | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | DeepSeek V3.2$0.28 input / $0.42 output | o3-mini$1.1 input / $4.4 output | DeepSeek V3.2 has the lower combined listed price. |
| Generation speedtokens per second | DeepSeek V3.235 tok/s | o3-mini160 tok/s | o3-mini has the higher measured throughput. |
| First-answer latencyseconds to first token | DeepSeek V3.23.75 s | o3-mini7.12 s | DeepSeek V3.2 reaches the first token sooner. |
| Context windowmaximum listed tokens | DeepSeek V3.2128K | o3-mini200K | o3-mini lists the larger context window. |
Benchmark Deep Dive
Agentic4 benchmarks
CodingDeepSeek V3.2 wins4 benchmarks
Reasoning2 benchmarks
Knowledge8 benchmarks
| Benchmark | DeepSeek V3.2 | o3-mini | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 24.7% | 19.0% | DeepSeek V3.2 leads |
| AA-GPQA DiamondSource | 75.1% | 74.8% | DeepSeek V3.2 leads |
| AA-HLESource | 10.5% | 8.7% | DeepSeek V3.2 leads |
| AA-Omniscience IndexSource | -46.7% | — | Not comparable |
| AA-Omniscience AccuracySource | 24.2% | — | Not comparable |
| AA-Omniscience Hallucination RateSource | 93.5% | — | Not comparable |
| MMLUSource | — | 86.9% | Not comparable |
| GPQASource | — | 77.2% | Not comparable |
Math3 benchmarks
Multimodal1 benchmarks
| Benchmark | DeepSeek V3.2 | o3-mini | Result |
|---|---|---|---|
| Design Arena WebsiteSource | 1204 | — | Not comparable |
Frequently Asked Questions (2)
Which is better, DeepSeek V3.2 or o3-mini?
DeepSeek V3.2 is ahead on BenchLM's BenchAlign leaderboard, 54.55 to 46.59.
Which is better for coding, DeepSeek V3.2 or o3-mini?
DeepSeek V3.2 has the edge for coding in this comparison, averaging 60.9 versus 49.3. Inside this category, AA-SciCode is the benchmark that creates the most daylight between them.