Model comparison
Amazon Nova Pro vs DeepSeek-V3.2-Speciale
DeepSeek-V3.2-Speciale is the stronger model overall, scoring 39.7 to 31.0 on the Noometry Index.
Last verified . 0 shared benchmarks.
DeepSeekSummary
- The widest gap is in reasoning, where DeepSeek-V3.2-Speciale leads 32.9 to 20.0.
- DeepSeek-V3.2-Speciale is cheaper at $0.58 / $1.68 per million input/output tokens, against $0.80 / $3.20 for Amazon Nova Pro.
- Amazon Nova Pro accepts more context: 300K tokens versus 128K.
- DeepSeek-V3.2-Speciale has downloadable open weights; the other is API-only.
Side by side
| Amazon Nova Pro | DeepSeek-V3.2-Speciale | |
|---|---|---|
| Provider | Amazon | DeepSeek |
| Noometry Index | 31.0 | 39.7 |
| Released | 2024-12-03 | 2025-12-01 |
| Weights | Proprietary | Open |
| Context window | 300K | 128K |
| Max output | 10K | 128K |
| Input $ / M tokens | $0.80 | $0.58 |
| Output $ / M tokens | $3.20 | $1.68 |
| Results tracked | 38 | 3 |
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Category by category
Coding DeepSeek-V3.2-Speciale leads
Amazon Nova Pro: 35.1 (#229), DeepSeek-V3.2-Speciale: 40.4 (#140)
| Benchmark | Amazon Nova Pro | DeepSeek-V3.2-Speciale |
|---|---|---|
| WeirdML | — | 46.7% |
| LiveBench Coding | 38.1% | — |
| LMArena Coding | 1270 | — |
Agentic & Tool Use Not comparable
Amazon Nova Pro: 16.7 (#147), DeepSeek-V3.2-Speciale: —
| Benchmark | Amazon Nova Pro | DeepSeek-V3.2-Speciale |
|---|---|---|
| Berkeley Function Calling Leaderboard | 25% | — |
| TheAgentCompany | 1.7% | — |
Reasoning DeepSeek-V3.2-Speciale leads
Amazon Nova Pro: 20.0 (#243), DeepSeek-V3.2-Speciale: 32.9 (#73)
| Benchmark | Amazon Nova Pro | DeepSeek-V3.2-Speciale |
|---|---|---|
| SimpleBench | — | 52.6% |
| LiveBench Reasoning | 32.6% | — |
| LMArena Hard Prompts | 1246 | — |
| LiveBench Data Analysis | 48.3% | — |
| Epoch Capabilities Index | 123.8 | — |
| LiveBench | 43.5% | — |
Math Not comparable
Amazon Nova Pro: 28.5 (#243), DeepSeek-V3.2-Speciale: —
| Benchmark | Amazon Nova Pro | DeepSeek-V3.2-Speciale |
|---|---|---|
| Omni-MATH | 24.2% | — |
| LiveBench Math | 38% | — |
| LMArena Math | 1252 | — |
Knowledge Not comparable
Amazon Nova Pro: 27.4 (#250), DeepSeek-V3.2-Speciale: —
| Benchmark | Amazon Nova Pro | DeepSeek-V3.2-Speciale |
|---|---|---|
| Humanity's Last Exam | 4.4% | — |
| MMLU-Pro | 67.3% | — |
| Confabulations | 30.1% | — |
| Vectara Hallucination Rate | 5.1% | — |
| GPQA (HELM) | 44.6% | — |
| LMArena Expert | 1211 | — |
| MMLU | 82% | — |
Multimodal Not comparable
Amazon Nova Pro: 25.0 (#126), DeepSeek-V3.2-Speciale: —
| Benchmark | Amazon Nova Pro | DeepSeek-V3.2-Speciale |
|---|---|---|
| LMArena Vision | 980 | — |
Multilingual Not comparable
Amazon Nova Pro: 39.7 (#223), DeepSeek-V3.2-Speciale: —
| Benchmark | Amazon Nova Pro | DeepSeek-V3.2-Speciale |
|---|---|---|
| LMArena Non-English | 1234 | — |
| LMArena Chinese | 1244 | — |
| LMArena French | 1271 | — |
| LMArena German | 1243 | — |
| LMArena Japanese | 1200 | — |
| LMArena Korean | 1203 | — |
| LMArena Russian | 1240 | — |
| LMArena Spanish | 1182 | — |
Instruction Following Not comparable
Amazon Nova Pro: 64.9 (#226), DeepSeek-V3.2-Speciale: —
| Benchmark | Amazon Nova Pro | DeepSeek-V3.2-Speciale |
|---|---|---|
| LiveBench Instruction Following | 67.1% | — |
| IFEval | 81.5% | — |
| LMArena Instruction Following | 1235 | — |
Long Context Not comparable
Amazon Nova Pro: 38.1 (#205), DeepSeek-V3.2-Speciale: —
| Benchmark | Amazon Nova Pro | DeepSeek-V3.2-Speciale |
|---|---|---|
| LMArena Longer Query | 1255 | — |
Writing & Preference DeepSeek-V3.2-Speciale leads
Amazon Nova Pro: 43.9 (#226), DeepSeek-V3.2-Speciale: 46.0 (#222)
| Benchmark | Amazon Nova Pro | DeepSeek-V3.2-Speciale |
|---|---|---|
| LMArena Text | 1259 | — |
| LMArena Creative Writing | 1212 | — |
| Short-Story Creative Writing | 60.5% | — |
| EQ-Bench Creative Writing | — | 1276 |
| WildBench | 77.7% | — |
| LMArena Multi-Turn | 1246 | — |
| LiveBench Language | 37% | — |
Frequently asked questions
Is Amazon Nova Pro better than DeepSeek-V3.2-Speciale?
DeepSeek-V3.2-Speciale is the stronger model overall, scoring 39.7 to 31.0 on the Noometry Index.
Which is cheaper, Amazon Nova Pro or DeepSeek-V3.2-Speciale?
DeepSeek-V3.2-Speciale is cheaper. It lists at $0.58 per million input tokens and $1.68 per million output tokens; Amazon Nova Pro lists at $0.80 and $3.20.
Is Amazon Nova Pro or DeepSeek-V3.2-Speciale better for coding?
DeepSeek-V3.2-Speciale scores higher on coding benchmarks: 40.4 versus 35.1 in the Noometry coding category.
Which has the bigger context window?
Amazon Nova Pro does, with 300K tokens against 128K.
How many benchmarks do Amazon Nova Pro and DeepSeek-V3.2-Speciale share?
0 benchmarks have published results for both models. Amazon Nova Pro has 38 scored results on Noometry and DeepSeek-V3.2-Speciale has 3.