Model comparison
DeepSeek V3.2 vs GPT-5.5 Pro
Head-to-head evidence from 3 shared benchmark results across 2 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: DeepSeek V3.2 #82 (Supported); GPT-5.5 Pro #38 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. DeepSeek V3.2 and GPT-5.5 Pro share 3 comparable benchmark results. 1 of 8 categories are comparable. 16 results are unique to DeepSeek V3.2; 4 to GPT-5.5 Pro.
Updated July 22, 2026- Shared results
- 3
- DeepSeek V3.2 only
- 16
- GPT-5.5 Pro only
- 4
- Comparable categories
- 1 / 8
Pick GPT-5.5 Pro if you want the stronger benchmark profile. DeepSeek V3.2 only becomes the better choice if you want the cheaper token bill or you would rather avoid the extra latency and token burn of a reasoning model.
Confidence note. This is a partial-evidence comparison with 3 shared benchmark results across 2 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
GPT-5.5 Pro is clearly ahead on the BenchAlign aggregate, 63.69 to 55.4. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-5.5 Pro's sharpest advantage is in mathematics, where it averages 48.1 against 17.1. The single biggest benchmark swing on the page is FrontierMath v2 (Tier 4), 2.100% to 39.600%.
GPT-5.5 Pro is also the more expensive model on tokens at $30.00 input / $180.00 output per 1M tokens, versus $0.28 input / $0.42 output per 1M tokens for DeepSeek V3.2. That is roughly 428.6x on output cost alone. GPT-5.5 Pro 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. GPT-5.5 Pro gives you the larger context window at 1M, 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 | GPT-5.5 Pro |
|---|---|---|---|
| Math | DeepSeek V3.217.1 | Margin→ 31.0 | GPT-5.5 Pro48.1 |
| Agentic | DeepSeek V3.2Not measured | MarginNo overlap | GPT-5.5 Pro90.1 |
| Coding | DeepSeek V3.260.9 | MarginNo overlap | GPT-5.5 ProNot measured |
| Knowledge | DeepSeek V3.2Not measured | MarginNo overlap | GPT-5.5 Pro57.2 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
FrontierMath v2 (Tier 4)
MathA 2.100%B 39.600%Winner: GPT-5.5 ProΔ 37.5FrontierMath v2 (Tier 4): DeepSeek V3.2 scored 2.100%; GPT-5.5 Pro scored 39.600%. GPT-5.5 Pro wins this benchmark. - Source ↗
FrontierMath v2 (Tiers 1-3)
MathA 22.100%B 51.000%Winner: GPT-5.5 ProΔ 28.9FrontierMath v2 (Tiers 1-3): DeepSeek V3.2 scored 22.100%; GPT-5.5 Pro scored 51.000%. GPT-5.5 Pro wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | DeepSeek V3.2 | GPT-5.5 Pro | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | DeepSeek V3.2$0.28 input / $0.42 output | GPT-5.5 Pro$30 input / $180 output | DeepSeek V3.2 has the lower combined listed price. |
| Generation speedtokens per second | DeepSeek V3.235 tok/s | GPT-5.5 ProNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | DeepSeek V3.23.75 s | GPT-5.5 ProNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | DeepSeek V3.2128K | GPT-5.5 Pro1M | GPT-5.5 Pro lists the larger context window. |
Benchmark Deep Dive
Agentic5 benchmarks
Coding3 benchmarks
Reasoning2 benchmarks
Knowledge8 benchmarks
| Benchmark | DeepSeek V3.2 | GPT-5.5 Pro | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 24.7% | — | Not comparable |
| AA-GPQA DiamondSource | 75.1% | — | Not comparable |
| AA-HLESource | 10.5% | — | Not comparable |
| AA-Omniscience IndexSource | -46.7% | — | Not comparable |
| AA-Omniscience AccuracySource | 24.2% | — | Not comparable |
| AA-Omniscience Hallucination RateSource | 93.5% | — | Not comparable |
| HLESource | — | 57.2% | Not comparable |
| HLE w/o toolsSource | — | 43.1% | Not comparable |
MathGPT-5.5 Pro wins3 benchmarks
Multimodal1 benchmarks
| Benchmark | DeepSeek V3.2 | GPT-5.5 Pro | Result |
|---|---|---|---|
| Design Arena WebsiteSource | 1204 | — | Not comparable |
Inst. Following1 benchmarks
| Benchmark | DeepSeek V3.2 | GPT-5.5 Pro | Result |
|---|---|---|---|
| AA-IFBenchSource | 49.0% | — | Not comparable |
Frequently Asked Questions (2)
Which is better, DeepSeek V3.2 or GPT-5.5 Pro?
GPT-5.5 Pro is ahead on BenchLM's BenchAlign leaderboard, 63.69 to 55.4. The biggest single separator in this matchup is FrontierMath v2 (Tier 4), where the scores are 2.100% and 39.600%.
Which is better for math, DeepSeek V3.2 or GPT-5.5 Pro?
GPT-5.5 Pro has the edge for math in this comparison, averaging 48.1 versus 17.1. Inside this category, FrontierMath v2 (Tier 4) is the benchmark that creates the most daylight between them.
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