Model comparison
DeepSeek V3.2 vs o3
Head-to-head evidence from 14 shared benchmark results across 7 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: DeepSeek V3.2 #82 (Supported); o3 #131 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. DeepSeek V3.2 and o3 share 14 comparable benchmark results. 1 of 8 categories are comparable. 5 results are unique to DeepSeek V3.2; 2 to o3.
Updated July 20, 2026- Shared results
- 14
- DeepSeek V3.2 only
- 5
- o3 only
- 2
- Comparable categories
- 1 / 8
Pick DeepSeek V3.2 if you want the stronger benchmark profile. o3 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 14 shared benchmark results across 7 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, 55.4 to 47.89. 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 mathematics, where it averages 17.1 against 14.5. The single biggest benchmark swing on the page is FrontierMath v2 (Tiers 1-3), 22.100% to 18.685%.
o3 is also the more expensive model on tokens at $2.00 input / $8.00 output per 1M tokens, versus $0.28 input / $0.42 output per 1M tokens for DeepSeek V3.2. That is roughly 19.0x on output cost alone. o3 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 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 |
|---|---|---|---|
| Math | DeepSeek V3.217.1 | Margin← 2.6 | o314.5 |
| Coding | DeepSeek V3.260.9 | MarginNo overlap | o3Not measured |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
FrontierMath v2 (Tiers 1-3)
MathA 22.100%B 18.685%Winner: DeepSeek V3.2Δ 3.4FrontierMath v2 (Tiers 1-3): DeepSeek V3.2 scored 22.100%; o3 scored 18.685%. DeepSeek V3.2 wins this benchmark. - Source ↗
FrontierMath v2 (Tier 4)
MathA 2.100%B 2.083%Winner: DeepSeek V3.2Δ 0FrontierMath v2 (Tier 4): DeepSeek V3.2 scored 2.100%; o3 scored 2.083%. DeepSeek V3.2 wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | DeepSeek V3.2 | o3 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | DeepSeek V3.2$0.28 input / $0.42 output | o3$2 input / $8 output | DeepSeek V3.2 has the lower combined listed price. |
| Generation speedtokens per second | DeepSeek V3.235 tok/s | o3118 tok/s | o3 has the higher measured throughput. |
| First-answer latencyseconds to first token | DeepSeek V3.23.75 s | o35.38 s | DeepSeek V3.2 reaches the first token sooner. |
| Context windowmaximum listed tokens | DeepSeek V3.2128K | o3200K | o3 lists the larger context window. |
Benchmark Deep Dive
Agentic4 benchmarks
Coding3 benchmarks
Reasoning2 benchmarks
Knowledge6 benchmarks
| Benchmark | DeepSeek V3.2 | o3 | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 24.7% | 30.4% | o3 leads |
| AA-GPQA DiamondSource | 75.1% | 82.7% | o3 leads |
| AA-HLESource | 10.5% | 20.0% | o3 leads |
| AA-Omniscience IndexSource | -46.7% | -15.3% | o3 leads |
| AA-Omniscience AccuracySource | 24.2% | 38.4% | o3 leads |
| AA-Omniscience Hallucination RateSource | 93.5% | 87.1% | o3 leads |
MathDeepSeek V3.2 wins3 benchmarks
Multimodal2 benchmarks
Inst. Following1 benchmarks
| Benchmark | DeepSeek V3.2 | o3 | Result |
|---|---|---|---|
| AA-IFBenchSource | 49.0% | 71.4% | o3 leads |
Frequently Asked Questions (2)
Which is better, DeepSeek V3.2 or o3?
DeepSeek V3.2 is ahead on BenchLM's BenchAlign leaderboard, 55.4 to 47.89. The biggest single separator in this matchup is FrontierMath v2 (Tiers 1-3), where the scores are 22.100% and 18.685%.
Which is better for math, DeepSeek V3.2 or o3?
DeepSeek V3.2 has the edge for math in this comparison, averaging 17.1 versus 14.5. Inside this category, FrontierMath v2 (Tiers 1-3) is the benchmark that creates the most daylight between them.
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