Model comparison
Amazon Nova Experimental Chat 10 20 vs DeepSeek-V3.1-Terminus
DeepSeek-V3.1-Terminus is the stronger model overall, scoring 43.1 to 42.1 on the Noometry Index.
Last verified . 10 shared benchmarks.
DeepSeekSummary
- They share 10 benchmarks with published results for both. Amazon Nova Experimental Chat 10 20 scores higher in 2 categories and DeepSeek-V3.1-Terminus in 5 categories; 5 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where DeepSeek-V3.1-Terminus leads 61.0 to 56.6.
- DeepSeek-V3.1-Terminus has downloadable open weights; the other is API-only.
Side by side
| Amazon Nova Experimental Chat 10 20 | DeepSeek-V3.1-Terminus | |
|---|---|---|
| Provider | Amazon | DeepSeek |
| Noometry Index | 42.1 | 43.1 |
| Released | — | 2025-09-22 |
| Weights | Proprietary | Open |
| Context window | — | 164K |
| Max output | — | 147K |
| Input $ / M tokens | — | $0.27 |
| Output $ / M tokens | — | $1 |
| Results tracked | 17 | 16 |
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Category by category
Coding Too close to call
Amazon Nova Experimental Chat 10 20: 41.6 (#123), DeepSeek-V3.1-Terminus: 42.0 (#113)
| Benchmark | Amazon Nova Experimental Chat 10 20 | DeepSeek-V3.1-Terminus |
|---|---|---|
| LMArena Coding | 1412 | 1426 |
| SciCode | — | 40.6% |
| ALE-Bench | — | 745.17 |
Reasoning Amazon Nova Experimental Chat 10 20 leads
Amazon Nova Experimental Chat 10 20: 28.4 (#106), DeepSeek-V3.1-Terminus: 26.4 (#133)
| Benchmark | Amazon Nova Experimental Chat 10 20 | DeepSeek-V3.1-Terminus |
|---|---|---|
| LMArena Hard Prompts | 1396 | 1426 |
| Kagi LLM Benchmark | — | 57.4% |
| CritPt | — | 1.7% |
| DTBench | — | 81.3% |
| LMCA | — | 28.6% |
Math Too close to call
Amazon Nova Experimental Chat 10 20: 39.0 (#119), DeepSeek-V3.1-Terminus: 38.5 (#137)
| Benchmark | Amazon Nova Experimental Chat 10 20 | DeepSeek-V3.1-Terminus |
|---|---|---|
| LMArena Math | 1425 | 1402 |
Knowledge Not comparable
Amazon Nova Experimental Chat 10 20: 38.5 (#144), DeepSeek-V3.1-Terminus: —
| Benchmark | Amazon Nova Experimental Chat 10 20 | DeepSeek-V3.1-Terminus |
|---|---|---|
| LMArena Expert | 1386 | — |
Multilingual DeepSeek-V3.1-Terminus leads
Amazon Nova Experimental Chat 10 20: 49.5 (#131), DeepSeek-V3.1-Terminus: 52.1 (#92)
| Benchmark | Amazon Nova Experimental Chat 10 20 | DeepSeek-V3.1-Terminus |
|---|---|---|
| LMArena Non-English | 1372 | 1407 |
| LMArena Russian | 1371 | 1436 |
| LMArena Chinese | 1404 | — |
| LMArena French | 1425 | — |
| LMArena German | 1391 | — |
| LMArena Japanese | 1360 | — |
| LMArena Korean | 1324 | — |
| LMArena Spanish | 1382 | — |
Instruction Following DeepSeek-V3.1-Terminus leads
Amazon Nova Experimental Chat 10 20: 72.1 (#141), DeepSeek-V3.1-Terminus: 74.0 (#106)
| Benchmark | Amazon Nova Experimental Chat 10 20 | DeepSeek-V3.1-Terminus |
|---|---|---|
| LMArena Instruction Following | 1365 | 1404 |
Long Context DeepSeek-V3.1-Terminus leads
Amazon Nova Experimental Chat 10 20: 41.7 (#133), DeepSeek-V3.1-Terminus: 43.4 (#97)
| Benchmark | Amazon Nova Experimental Chat 10 20 | DeepSeek-V3.1-Terminus |
|---|---|---|
| LMArena Longer Query | 1370 | 1421 |
Writing & Preference DeepSeek-V3.1-Terminus leads
Amazon Nova Experimental Chat 10 20: 56.6 (#136), DeepSeek-V3.1-Terminus: 61.0 (#92)
| Benchmark | Amazon Nova Experimental Chat 10 20 | DeepSeek-V3.1-Terminus |
|---|---|---|
| LMArena Text | 1394 | 1419 |
| LMArena Creative Writing | 1318 | 1403 |
| LMArena Multi-Turn | 1364 | 1411 |
Frequently asked questions
Is Amazon Nova Experimental Chat 10 20 better than DeepSeek-V3.1-Terminus?
DeepSeek-V3.1-Terminus is the stronger model overall, scoring 43.1 to 42.1 on the Noometry Index.
Is Amazon Nova Experimental Chat 10 20 or DeepSeek-V3.1-Terminus better for coding?
They score almost the same on coding (41.6 vs 42.0); test both on your own repository before choosing.
How many benchmarks do Amazon Nova Experimental Chat 10 20 and DeepSeek-V3.1-Terminus share?
10 benchmarks have published results for both models. Amazon Nova Experimental Chat 10 20 has 17 scored results on Noometry and DeepSeek-V3.1-Terminus has 16.