Nova Premier 1.0 vs DeepSeek V3.1 Terminus
DeepSeek V3.1 Terminus leads Nova Premier 1.0 on the Artificial Analysis Intelligence Index, 14.8 to 9.2, and DeepSeek V3.1 Terminus costs 12.3x less per output token ($1.0142 vs $12.50 per million). Updated October 21, 2026; 14 benchmarks have a result for both.
Nova Premier 1.0 or DeepSeek V3.1 Terminus: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick Nova Premier 1.0 for a larger context window (1M against 164K tokens) and work measured by LiveCodeBench (Artificial Analysis run) or Terminal-Bench Hard (Artificial Analysis run), where it leads.
- Shared results
- 14
- Nova Premier 1.0 only
- 0
- DeepSeek V3.1 Terminus only
- 31
- Like-for-like categories
- 8 of 9
Only benchmarks that tested both models count toward a pick; a result only one model has is shown but not compared.
Which one for your work
Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.
Coding
Vibe Coding Index, six public coding benchmarks
No call
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
DeepSeek V3.1 Terminus
DeepSeek V3.1 Terminus leads, 14.8 against 9.2.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only DeepSeek V3.1 Terminus has a AA Agentic Index result, 6.8.
Directional only
Web design
Design Arena: websites
DeepSeek V3.1 Terminus
DeepSeek V3.1 Terminus leads, 1187 against 835.
Same board, both measured
Long documents
Listed context window
Nova Premier 1.0
Nova Premier 1.0 takes 1M tokens against 164K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
DeepSeek V3.1 Terminus
Nova Premier 1.0 $0.0088, DeepSeek V3.1 Terminus $0.0008 per turn.
List prices
At a glance
- Coding index
- Nova Premier 1.0 not benchmarked, DeepSeek V3.1 Terminus not benchmarked.
- Widest category
- Math, 72.4 points apart on average over 2 shared benchmarks.
- Widest single gap
- AA Math Index: Nova Premier 1.0 17.3 against DeepSeek V3.1 Terminus 89.7, 72.4 points apart on a 0 to 100 scale.
- Output price
- Nova Premier 1.0 $12.50 against DeepSeek V3.1 Terminus $1.0142 per million output tokens, 12.3x apart.
- Context window
- Nova Premier 1.0 takes 1M tokens, DeepSeek V3.1 Terminus 164K.
Benchmark by benchmark
First the score: boards each model leads, per category, where both have a result. Then every board, a category to a fold; bars are each result on a 0 to 100 scale, so compare the two in a row, not one row with another.
| Category | Nova Premier 1.0 | Bars | DeepSeek V3.1 Terminus | Ties |
|---|---|---|---|---|
| Coding | 0 | 3 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 1 | 0 | ||
| Reasoning | 0 | 3 | ||
| Math | 0 | 2 | ||
| Knowledge | 0 | 1 | ||
| Web design | 0 | 1 | ||
| General | 0 | 2 | ||
| All shared boards | 1 | 13 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index03
| Benchmark | Nova Premier 1.0 | DeepSeek V3.1 Terminus | Leader |
|---|---|---|---|
| AA Coding Index | Not measured | 43.5 | Only DeepSeek V3.1 Terminus measured |
| LiveCodeBench (Artificial Analysis run) | 31.7% | 79.8% | DeepSeek V3.1 Terminus |
| SciCode | Not measured | 38.0% | Only DeepSeek V3.1 Terminus measured |
| Terminal-Bench Hard (Artificial Analysis run) | 6.8% | 31.8% | DeepSeek V3.1 Terminus |
| ALE-Bench | 147.4 | 745.2 | DeepSeek V3.1 Terminus |
| LMArena Text: coding | Not measured | 1425 | Only DeepSeek V3.1 Terminus measured |
| LMArena Text: software and IT | Not measured | 1426 | Only DeepSeek V3.1 Terminus measured |
| Neither model has a result on the other 32 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Nova Premier 1.0 | DeepSeek V3.1 Terminus | Leader |
|---|---|---|---|
| AA Intelligence Index | 9.2 | 14.8 | DeepSeek V3.1 Terminus |
| Neither model has a result on the other 1 board here | |||
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Nova Premier 1.0 | DeepSeek V3.1 Terminus | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 6.8 | Only DeepSeek V3.1 Terminus measured |
| τ²-Bench Telecom | 38.3% | 37.1% | Nova Premier 1.0 |
| Neither model has a result on the other 39 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index03
| Benchmark | Nova Premier 1.0 | DeepSeek V3.1 Terminus | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 56.9% | 79.2% | DeepSeek V3.1 Terminus |
| Humanity's Last Exam (Artificial Analysis run) | 4.2% | 16.4% | DeepSeek V3.1 Terminus |
| LMArena Text: hard prompts | Not measured | 1426 | Only DeepSeek V3.1 Terminus measured |
| LMArena Text: hard prompts in English | Not measured | 1432 | Only DeepSeek V3.1 Terminus measured |
| Kagi LLM Benchmark | 44.8% | 57.4% | DeepSeek V3.1 Terminus |
| Neither model has a result on the other 17 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Nova Premier 1.0 | DeepSeek V3.1 Terminus | Leader |
|---|---|---|---|
| AA Math Index | 17.3 | 89.7 | DeepSeek V3.1 Terminus |
| AIME 2025 (Artificial Analysis run) | 17.3% | 89.7% | DeepSeek V3.1 Terminus |
| LMArena Text: math | Not measured | 1402 | Only DeepSeek V3.1 Terminus measured |
| Neither model has a result on the other 10 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Nova Premier 1.0 | DeepSeek V3.1 Terminus | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | 73.3% | 85.1% | DeepSeek V3.1 Terminus |
| LMArena Text: science | Not measured | 1451 | Only DeepSeek V3.1 Terminus measured |
| LMArena Text: medicine and healthcare | Not measured | 1468 | Only DeepSeek V3.1 Terminus measured |
| LMArena Text: legal and government | Not measured | 1457 | Only DeepSeek V3.1 Terminus measured |
| LMArena Text: business and finance | Not measured | 1414 | Only DeepSeek V3.1 Terminus measured |
| Neither model has a result on the other 13 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Nova Premier 1.0 | DeepSeek V3.1 Terminus | Leader |
|---|---|---|---|
| Design Arena: websites | 835 | 1187 | DeepSeek V3.1 Terminus |
| Design Arena: UI components | Not measured | 1182 | Only DeepSeek V3.1 Terminus measured |
| Design Arena: game dev | Not measured | 1131 | Only DeepSeek V3.1 Terminus measured |
| Design Arena: data viz | Not measured | 1167 | Only DeepSeek V3.1 Terminus measured |
| Design Arena: 3D | Not measured | 1141 | Only DeepSeek V3.1 Terminus measured |
| Design Arena: all code categories | Not measured | 1175 | Only DeepSeek V3.1 Terminus measured |
| Design Arena: SVG | Not measured | 1065 | Only DeepSeek V3.1 Terminus measured |
| Neither model has a result on the other 2 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Nova Premier 1.0 | DeepSeek V3.1 Terminus | Leader |
|---|---|---|---|
| IFBench | 36.2% | 57.0% | DeepSeek V3.1 Terminus |
| Long context reasoning (AA-LCR) | 34.3% | 69.3% | DeepSeek V3.1 Terminus |
| DTBench | Not measured | 81.3% | Only DeepSeek V3.1 Terminus measured |
| LMCA | Not measured | 28.6% | Only DeepSeek V3.1 Terminus measured |
| LMArena Text | Not measured | 1419 | Only DeepSeek V3.1 Terminus measured |
| LMArena Text: instruction following | Not measured | 1404 | Only DeepSeek V3.1 Terminus measured |
| LMArena Text: creative writing | Not measured | 1403 | Only DeepSeek V3.1 Terminus measured |
| LMArena Text: English | Not measured | 1429 | Only DeepSeek V3.1 Terminus measured |
| LMArena Text: non-English | Not measured | 1408 | Only DeepSeek V3.1 Terminus measured |
| LMArena Text: Russian | Not measured | 1435 | Only DeepSeek V3.1 Terminus measured |
| LMArena Text: Polish | Not measured | 1427 | Only DeepSeek V3.1 Terminus measured |
| LMArena Text: multi-turn | Not measured | 1411 | Only DeepSeek V3.1 Terminus measured |
| LMArena Text: longer queries | Not measured | 1422 | Only DeepSeek V3.1 Terminus measured |
| LMArena Text: writing and language | Not measured | 1409 | Only DeepSeek V3.1 Terminus measured |
| LMArena Text: entertainment and media | Not measured | 1391 | Only DeepSeek V3.1 Terminus measured |
| Neither model has a result on the other 31 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Nova Premier 1.0 | DeepSeek V3.1 Terminus | Leader |
|---|---|---|---|
| Neither model has a result on 5 boards here | |||
What each workload costs
Three fixed token mixes at each model's listed price, so per-token rates become a bill.
Chat turn
1K input + 500 output tokens
DeepSeek V3.1 Terminus costs less
Repository review
50K input + 3K output tokens
DeepSeek V3.1 Terminus costs less
Agent loop
200K input + 10K output tokens
DeepSeek V3.1 Terminus costs less
Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.
Specification differences
The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.
| Specification | Amazon Nova Premier 1.0 | DeepSeek V3.1 Terminus |
|---|---|---|
| Maker | Amazon | DeepSeek |
| Weights | No public weights listed | Open weights |
| Released | October 31, 2025 | September 22, 2025 |
| Context window | 1M | 164K |
| Input $/Mtok | $2.50 | $0.3063 |
| Output $/Mtok | $12.50 | $1.0142 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Nova Premier 1.0 better than DeepSeek V3.1 Terminus for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Nova Premier 1.0 for a larger context window (1M against 164K tokens) and work measured by LiveCodeBench (Artificial Analysis run) or Terminal-Bench Hard (Artificial Analysis run), where it leads.
Which is cheaper, Nova Premier 1.0 or DeepSeek V3.1 Terminus?
Nova Premier 1.0 costs $2.50 per million input tokens and $12.50 per million output tokens; DeepSeek V3.1 Terminus costs $0.3063 and $1.0142. Cost per solved task is known for neither of them.
Which has the bigger context window, Nova Premier 1.0 or DeepSeek V3.1 Terminus?
Nova Premier 1.0, with 1M tokens against 164K.
How many benchmarks is the Nova Premier 1.0 vs DeepSeek V3.1 Terminus comparison based on?
14 benchmarks have a result for both models as of October 21, 2026. Nova Premier 1.0's coding index rests on 0 independent benchmarks and DeepSeek V3.1 Terminus's on 0. Where only one model has a result, the page says so instead of naming a winner.