Model comparison
DeepSeek V3.2 vs GPT-5 nano
Head-to-head evidence from 0 shared benchmark results across 0 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: DeepSeek V3.2 #88 (Supported); GPT-5 nano #146 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. DeepSeek V3.2 and GPT-5 nano share 0 comparable benchmark results. 0 of 8 categories are comparable. 19 results are unique to DeepSeek V3.2; 0 to GPT-5 nano.
Updated July 24, 2026- Shared results
- 0
- DeepSeek V3.2 only
- 19
- GPT-5 nano only
- 0
- Comparable categories
- 0 / 8
Benchmark data for DeepSeek V3.2 and GPT-5 nano is coming soon on BenchLM.
Confidence note. This is a partial-evidence comparison with 0 shared benchmark results across 0 evidence categories; 0 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
BenchLM does not have sourced benchmark coverage for GPT-5 nano yet. This comparison is currently limited to metadata such as context window, reasoning mode, and pricing where available.
DeepSeek V3.2 is priced at $0.28 input / $0.42 output per 1M tokens, versus $0.05 input / $0.40 output per 1M tokens for GPT-5 nano. GPT-5 nano has the larger context window at 400K, compared with 128K for DeepSeek V3.2.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | DeepSeek V3.2 | GPT-5 nano | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | DeepSeek V3.2$0.28 input / $0.42 output | GPT-5 nano$0.05 input / $0.4 output | GPT-5 nano has the lower combined listed price. |
| Generation speedtokens per second | DeepSeek V3.235 tok/s | GPT-5 nano137 tok/s | GPT-5 nano has the higher measured throughput. |
| First-answer latencyseconds to first token | DeepSeek V3.23.75 s | GPT-5 nano83.30 s | DeepSeek V3.2 reaches the first token sooner. |
| Context windowmaximum listed tokens | DeepSeek V3.2128K | GPT-5 nano400K | GPT-5 nano lists the larger context window. |
Benchmark Deep Dive
Agentic4 benchmarks
Coding3 benchmarks
Reasoning2 benchmarks
Knowledge6 benchmarks
| Benchmark | DeepSeek V3.2 | GPT-5 nano | 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 |
Math2 benchmarks
Multimodal1 benchmarks
| Benchmark | DeepSeek V3.2 | GPT-5 nano | Result |
|---|---|---|---|
| Design Arena WebsiteSource | 1204 | — | Not comparable |
Inst. Following1 benchmarks
| Benchmark | DeepSeek V3.2 | GPT-5 nano | Result |
|---|---|---|---|
| AA-IFBenchSource | 49.0% | — | Not comparable |
Frequently Asked Questions (3)
Can I compare DeepSeek V3.2 and GPT-5 nano on BenchLM yet?
Not fully yet. BenchLM is tracking both models, but the sourced benchmark breakdown for this comparison is still coming soon.
Why does this comparison show “coming soon”?
BenchLM only shows category winners and benchmark-level calls when we have sourced results that can be compared fairly. For these models, the public benchmark coverage is not complete enough yet.
What data is available for DeepSeek V3.2 and GPT-5 nano today?
DeepSeek V3.2: $0.28 input / $0.42 output per 1M tokens GPT-5 nano: $0.05 input / $0.40 output per 1M tokens Both model pages still include creator, context window, reasoning mode, and other metadata while benchmark coverage fills in.