Model comparison
DeepSeek-V3.1-Terminus vs Nova Premier 1.0
DeepSeek-V3.1-Terminus is the stronger model overall, scoring 42.6 to 37.7 on the Noometry Index.
Last verified . 1 shared benchmarks.
DeepSeekSummary
- They share 1 benchmark with published results for both. DeepSeek-V3.1-Terminus scores higher in 4 categories and Nova Premier 1.0 in 0 categories; 4 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where DeepSeek-V3.1-Terminus leads 61.3 to 51.0.
- The biggest single-benchmark swing is Kagi LLM Benchmark: 57.4% for DeepSeek-V3.1-Terminus and 44.8% for Nova Premier 1.0.
- DeepSeek-V3.1-Terminus is cheaper at $0.30 / $1 per million input/output tokens, against $2.50 / $12.50 for Nova Premier 1.0.
- Nova Premier 1.0 accepts more context: 1M tokens versus 164K.
- DeepSeek-V3.1-Terminus has downloadable open weights; the other is API-only.
Side by side
| DeepSeek-V3.1-Terminus | Nova Premier 1.0 | |
|---|---|---|
| Provider | DeepSeek | Amazon |
| Noometry Index | 42.6 | 37.7 |
| Released | 2025-09-22 | 2025-04-30 |
| Weights | Open | Proprietary |
| Context window | 164K | 1M |
| Max output | 66K | 10K |
| Input $ / M tokens | $0.30 | $2.50 |
| Output $ / M tokens | $1 | $12.50 |
| Results tracked | 16 | 6 |
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Category by category
Coding Not comparable
DeepSeek-V3.1-Terminus: 41.5 (#114), Nova Premier 1.0: —
| Benchmark | DeepSeek-V3.1-Terminus | Nova Premier 1.0 |
|---|---|---|
| SciCode | 40.6% | — |
| LMArena Coding | 1426 | — |
| ALE-Bench | 745.17 | — |
Reasoning DeepSeek-V3.1-Terminus leads
DeepSeek-V3.1-Terminus: 25.7 (#126), Nova Premier 1.0: 22.3 (#182)
| Benchmark | DeepSeek-V3.1-Terminus | Nova Premier 1.0 |
|---|---|---|
| Kagi LLM Benchmark | 57.4% | 44.8% |
| CritPt | 1.7% | — |
| LMArena Hard Prompts | 1427 | — |
| DTBench | 81.3% | — |
| LMCA | 28.6% | — |
Math DeepSeek-V3.1-Terminus leads
DeepSeek-V3.1-Terminus: 35.7 (#138), Nova Premier 1.0: 31.5 (#194)
| Benchmark | DeepSeek-V3.1-Terminus | Nova Premier 1.0 |
|---|---|---|
| Omni-MATH | — | 35% |
| LMArena Math | 1402 | — |
Knowledge Not comparable
DeepSeek-V3.1-Terminus: —, Nova Premier 1.0: 35.4 (#176)
| Benchmark | DeepSeek-V3.1-Terminus | Nova Premier 1.0 |
|---|---|---|
| MMLU-Pro | — | 72.6% |
| GPQA (HELM) | — | 51.8% |
Multilingual Not comparable
DeepSeek-V3.1-Terminus: 52.3 (#87), Nova Premier 1.0: —
| Benchmark | DeepSeek-V3.1-Terminus | Nova Premier 1.0 |
|---|---|---|
| LMArena Non-English | 1407 | — |
| LMArena Russian | 1434 | — |
Instruction Following DeepSeek-V3.1-Terminus leads
DeepSeek-V3.1-Terminus: 74.4 (#96), Nova Premier 1.0: 66.9 (#201)
| Benchmark | DeepSeek-V3.1-Terminus | Nova Premier 1.0 |
|---|---|---|
| IFEval | — | 80.3% |
| LMArena Instruction Following | 1406 | — |
Long Context Not comparable
DeepSeek-V3.1-Terminus: 43.5 (#88), Nova Premier 1.0: —
| Benchmark | DeepSeek-V3.1-Terminus | Nova Premier 1.0 |
|---|---|---|
| LMArena Longer Query | 1426 | — |
Writing & Preference DeepSeek-V3.1-Terminus leads
DeepSeek-V3.1-Terminus: 61.3 (#87), Nova Premier 1.0: 51.0 (#174)
| Benchmark | DeepSeek-V3.1-Terminus | Nova Premier 1.0 |
|---|---|---|
| LMArena Text | 1420 | — |
| LMArena Creative Writing | 1404 | — |
| WildBench | — | 78.8% |
| LMArena Multi-Turn | 1411 | — |
Frequently asked questions
Is DeepSeek-V3.1-Terminus better than Nova Premier 1.0?
DeepSeek-V3.1-Terminus is the stronger model overall, scoring 42.6 to 37.7 on the Noometry Index.
Which is cheaper, DeepSeek-V3.1-Terminus or Nova Premier 1.0?
DeepSeek-V3.1-Terminus is cheaper. It lists at $0.30 per million input tokens and $1 per million output tokens; Nova Premier 1.0 lists at $2.50 and $12.50.
Which has the bigger context window?
Nova Premier 1.0 does, with 1M tokens against 164K.
How many benchmarks do DeepSeek-V3.1-Terminus and Nova Premier 1.0 share?
1 benchmark has published results for both models. DeepSeek-V3.1-Terminus has 16 scored results on Noometry and Nova Premier 1.0 has 6.