Model comparison
Amazon Nova Experimental Chat 26 02 10 vs DeepSeek-V3.2-Exp
Amazon Nova Experimental Chat 26 02 10 and DeepSeek-V3.2-Exp score almost the same on the Noometry Index (44.5 vs 44.3), so choose on price, context window or the category you care about most.
Last verified . 12 shared benchmarks.
DeepSeekSummary
- They share 12 benchmarks with published results for both. Amazon Nova Experimental Chat 26 02 10 scores higher in 3 categories and DeepSeek-V3.2-Exp in 5 categories; 6 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where DeepSeek-V3.2-Exp leads 51.7 to 42.3.
- DeepSeek-V3.2-Exp has downloadable open weights; the other is API-only.
Side by side
| Amazon Nova Experimental Chat 26 02 10 | DeepSeek-V3.2-Exp | |
|---|---|---|
| Provider | Amazon | DeepSeek |
| Noometry Index | 44.5 | 44.3 |
| Released | — | 2025-09-29 |
| Weights | Proprietary | Open |
| Context window | — | 164K |
| Max output | — | 66K |
| Input $ / M tokens | — | $0.26 |
| Output $ / M tokens | — | $0.38 |
| Results tracked | 12 | 49 |
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Category by category
Coding DeepSeek-V3.2-Exp leads
Amazon Nova Experimental Chat 26 02 10: 43.9 (#82), DeepSeek-V3.2-Exp: 46.5 (#65)
| Benchmark | Amazon Nova Experimental Chat 26 02 10 | DeepSeek-V3.2-Exp |
|---|---|---|
| LMArena Coding | 1483 | 1454 |
| SWE-bench Verified (bash only) | — | 70% |
| Aider Polyglot | — | 74.2% |
| LMArena WebDev | — | 1362 |
| SWE-bench Multilingual | — | 59% |
| SciCode | — | 38.9% |
| WeirdML | — | 39.5% |
Agentic & Tool Use Not comparable
Amazon Nova Experimental Chat 26 02 10: —, DeepSeek-V3.2-Exp: 32.7 (#59)
| Benchmark | Amazon Nova Experimental Chat 26 02 10 | DeepSeek-V3.2-Exp |
|---|---|---|
| Terminal-Bench | — | 39.6% |
| APEX-Agents | — | 21.3% |
| Berkeley Function Calling Leaderboard | — | 56.7% |
| TheAgentCompany | — | 42.9% |
| Vending-Bench 2 | — | 1,034 |
Reasoning Amazon Nova Experimental Chat 26 02 10 leads
Amazon Nova Experimental Chat 26 02 10: 30.1 (#86), DeepSeek-V3.2-Exp: 22.1 (#208)
| Benchmark | Amazon Nova Experimental Chat 26 02 10 | DeepSeek-V3.2-Exp |
|---|---|---|
| LMArena Hard Prompts | 1458 | 1434 |
| ARC-AGI-2 | — | 4% |
| Kagi LLM Benchmark | — | 52.2% |
| NYT Connections (extended) | — | 36.7% |
| ARC-AGI-1 | — | 57% |
| CritPt | — | 2.9% |
| Chess Puzzles | — | 14% |
| Thematic Generalization | — | 65% |
| DTBench | — | 87.7% |
| LMCA | — | 29.1% |
| Epoch Capabilities Index | — | 146.27 |
Math DeepSeek-V3.2-Exp leads
Amazon Nova Experimental Chat 26 02 10: 39.3 (#109), DeepSeek-V3.2-Exp: 41.7 (#87)
| Benchmark | Amazon Nova Experimental Chat 26 02 10 | DeepSeek-V3.2-Exp |
|---|---|---|
| LMArena Math | 1438 | 1435 |
| MathArena Final-Answer Competitions | — | 57.7% |
| OTIS Mock AIME 2024-2025 | — | 87.8% |
| ProofBench | — | 8% |
| FrontierMath (Feb 2025 set) | — | 22.1% |
| FrontierMath Tier 4 (v1) | — | 2.1% |
Knowledge DeepSeek-V3.2-Exp leads
Amazon Nova Experimental Chat 26 02 10: 42.3 (#97), DeepSeek-V3.2-Exp: 51.7 (#66)
| Benchmark | Amazon Nova Experimental Chat 26 02 10 | DeepSeek-V3.2-Exp |
|---|---|---|
| LMArena Expert | 1506 | 1436 |
| GPQA Diamond | — | 83.4% |
| Vectara Hallucination Rate | — | 5.3% |
Multilingual Amazon Nova Experimental Chat 26 02 10 leads
Amazon Nova Experimental Chat 26 02 10: 54.0 (#50), DeepSeek-V3.2-Exp: 52.2 (#90)
| Benchmark | Amazon Nova Experimental Chat 26 02 10 | DeepSeek-V3.2-Exp |
|---|---|---|
| LMArena Non-English | 1434 | 1409 |
| LMArena Chinese | 1463 | 1461 |
| LMArena Russian | 1423 | 1424 |
| LMArena French | — | 1433 |
| LMArena German | — | 1440 |
| LMArena Japanese | — | 1374 |
| LMArena Korean | — | 1371 |
| LMArena Spanish | — | 1440 |
Instruction Following Too close to call
Amazon Nova Experimental Chat 26 02 10: 75.2 (#69), DeepSeek-V3.2-Exp: 74.5 (#93)
| Benchmark | Amazon Nova Experimental Chat 26 02 10 | DeepSeek-V3.2-Exp |
|---|---|---|
| LMArena Instruction Following | 1427 | 1413 |
Long Context DeepSeek-V3.2-Exp leads
Amazon Nova Experimental Chat 26 02 10: 44.0 (#77), DeepSeek-V3.2-Exp: 47.6 (#16)
| Benchmark | Amazon Nova Experimental Chat 26 02 10 | DeepSeek-V3.2-Exp |
|---|---|---|
| LMArena Longer Query | 1441 | 1428 |
| Fiction.LiveBench | — | 83.3% |
| CL-bench | — | 13.2% |
| CL-bench Life | — | 9.5% |
Writing & Preference Too close to call
Amazon Nova Experimental Chat 26 02 10: 61.8 (#84), DeepSeek-V3.2-Exp: 62.4 (#77)
| Benchmark | Amazon Nova Experimental Chat 26 02 10 | DeepSeek-V3.2-Exp |
|---|---|---|
| LMArena Text | 1448 | 1425 |
| LMArena Creative Writing | 1368 | 1403 |
| LMArena Multi-Turn | 1442 | 1427 |
| EQ-Bench Creative Writing | — | 1515 |
Frequently asked questions
Is Amazon Nova Experimental Chat 26 02 10 better than DeepSeek-V3.2-Exp?
Amazon Nova Experimental Chat 26 02 10 and DeepSeek-V3.2-Exp score almost the same on the Noometry Index (44.5 vs 44.3), so choose on price, context window or the category you care about most.
Is Amazon Nova Experimental Chat 26 02 10 or DeepSeek-V3.2-Exp better for coding?
DeepSeek-V3.2-Exp scores higher on coding benchmarks: 46.5 versus 43.9 in the Noometry coding category.
How many benchmarks do Amazon Nova Experimental Chat 26 02 10 and DeepSeek-V3.2-Exp share?
12 benchmarks have published results for both models. Amazon Nova Experimental Chat 26 02 10 has 12 scored results on Noometry and DeepSeek-V3.2-Exp has 49.