Nova Premier 1.0 vs DeepSeek V4 Flash 0423
Updated October 21, 2026. 3 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Neither model has a coding score yet, so the two cannot be ranked on coding.
Nova Premier 1.0 has the edge where what matters is ALE-Bench or AA Intelligence Index, where it leads.
- Shared results
- 3
- Nova Premier 1.0 only
- 10
- DeepSeek V4 Flash 0423 only
- 45
- Like-for-like categories
- 3 of 9
Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.
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 V4 Flash 0423
DeepSeek V4 Flash 0423 leads, 24.4 against 9.2.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only DeepSeek V4 Flash 0423 has a AA Agentic Index result, 26.3.
Directional only
Web design
Design Arena: websites
DeepSeek V4 Flash 0423
DeepSeek V4 Flash 0423 leads, 1208 against 835.
Same board, both measured
Long documents
Listed context window
DeepSeek V4 Flash 0423
DeepSeek V4 Flash 0423 takes 1.05M tokens against 1M.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
DeepSeek V4 Flash 0423
Nova Premier 1.0 $0.0088, DeepSeek V4 Flash 0423 $0.0003 per turn.
List prices
At a glance
- Coding index
- Nova Premier 1.0 not benchmarked, DeepSeek V4 Flash 0423 not benchmarked.
- Widest category
- Web design, 46.6 points apart on average over 1 shared benchmark.
- Widest single gap
- Design Arena: websites: Nova Premier 1.0 835 against DeepSeek V4 Flash 0423 1208, 46.6 points apart on a 0 to 100 scale.
- Output price
- Nova Premier 1.0 $12.50 against DeepSeek V4 Flash 0423 $0.28 per million output tokens, 44.6x apart.
- Context window
- Nova Premier 1.0 takes 1M tokens, DeepSeek V4 Flash 0423 1.05M.
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 V4 Flash 0423 | Ties |
|---|---|---|---|---|
| Coding | 0 | 1 | ||
| Intelligence | 0 | 1 | ||
| Web design | 0 | 1 | ||
| All shared boards | 0 | 3 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index01
| Benchmark | Nova Premier 1.0 | DeepSeek V4 Flash 0423 | Leader |
|---|---|---|---|
| LMArena WebDev | Not measured | 1582 | Only DeepSeek V4 Flash 0423 measured |
| AA Coding Index | Not measured | 52.0 | Only DeepSeek V4 Flash 0423 measured |
| LiveCodeBench (Artificial Analysis run) | 31.7% | Not measured | Only Nova Premier 1.0 measured |
| Terminal-Bench Hard (Artificial Analysis run) | 6.8% | Not measured | Only Nova Premier 1.0 measured |
| WeirdML | Not measured | 45.6% | Only DeepSeek V4 Flash 0423 measured |
| ALE-Bench | 147.4 | 678.2 | DeepSeek V4 Flash 0423 |
| LMArena Text: coding | Not measured | 1457 | Only DeepSeek V4 Flash 0423 measured |
| LMArena Text: software and IT | Not measured | 1453 | Only DeepSeek V4 Flash 0423 measured |
| LMArena WebDev: React | Not measured | 1585 | Only DeepSeek V4 Flash 0423 measured |
| LMArena WebDev: HTML | Not measured | 1558 | Only DeepSeek V4 Flash 0423 measured |
| Neither model has a result on the other 28 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Nova Premier 1.0 | DeepSeek V4 Flash 0423 | Leader |
|---|---|---|---|
| AA Intelligence Index | 9.2 | 24.4 | DeepSeek V4 Flash 0423 |
| Epoch Capabilities Index | Not measured | 146.1 | Only DeepSeek V4 Flash 0423 measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Nova Premier 1.0 | DeepSeek V4 Flash 0423 | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 26.3 | Only DeepSeek V4 Flash 0423 measured |
| τ²-Bench Telecom | 38.3% | Not measured | Only Nova Premier 1.0 measured |
| Neither model has a result on the other 37 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | Nova Premier 1.0 | DeepSeek V4 Flash 0423 | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 56.9% | Not measured | Only Nova Premier 1.0 measured |
| Humanity's Last Exam (Artificial Analysis run) | 4.2% | Not measured | Only Nova Premier 1.0 measured |
| SimpleBench | Not measured | 46.3% | Only DeepSeek V4 Flash 0423 measured |
| LMArena Text: hard prompts | Not measured | 1444 | Only DeepSeek V4 Flash 0423 measured |
| LMArena Text: expert | Not measured | 1441 | Only DeepSeek V4 Flash 0423 measured |
| LMArena Text: hard prompts in English | Not measured | 1449 | Only DeepSeek V4 Flash 0423 measured |
| Neither model has a result on the other 15 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
| Benchmark | Nova Premier 1.0 | DeepSeek V4 Flash 0423 | Leader |
|---|---|---|---|
| AA Math Index | 17.3 | Not measured | Only Nova Premier 1.0 measured |
| AIME 2025 (Artificial Analysis run) | 17.3% | Not measured | Only Nova Premier 1.0 measured |
| LMArena Text: math | Not measured | 1426 | Only DeepSeek V4 Flash 0423 measured |
| LMArena Text: mathematical work | Not measured | 1432 | Only DeepSeek V4 Flash 0423 measured |
| Neither model has a result on the other 9 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
| Benchmark | Nova Premier 1.0 | DeepSeek V4 Flash 0423 | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | 73.3% | Not measured | Only Nova Premier 1.0 measured |
| LMArena Text: science | Not measured | 1446 | Only DeepSeek V4 Flash 0423 measured |
| LMArena Text: medicine and healthcare | Not measured | 1448 | Only DeepSeek V4 Flash 0423 measured |
| LMArena Text: legal and government | Not measured | 1439 | Only DeepSeek V4 Flash 0423 measured |
| LMArena Text: business and finance | Not measured | 1425 | Only DeepSeek V4 Flash 0423 measured |
| Neither model has a result on the other 12 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Nova Premier 1.0 | DeepSeek V4 Flash 0423 | Leader |
|---|---|---|---|
| Design Arena: websites | 835 | 1208 | DeepSeek V4 Flash 0423 |
| Design Arena: UI components | Not measured | 1165 | Only DeepSeek V4 Flash 0423 measured |
| Design Arena: game dev | Not measured | 1197 | Only DeepSeek V4 Flash 0423 measured |
| Design Arena: data viz | Not measured | 1127 | Only DeepSeek V4 Flash 0423 measured |
| Design Arena: 3D | Not measured | 1189 | Only DeepSeek V4 Flash 0423 measured |
| Design Arena: all code categories | Not measured | 1205 | Only DeepSeek V4 Flash 0423 measured |
| Design Arena: SVG | Not measured | 1155 | Only DeepSeek V4 Flash 0423 measured |
| Design Arena: ASCII art | Not measured | 1109 | Only DeepSeek V4 Flash 0423 measured |
| Neither model has a result on the other 1 board here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index21 boards, none shared
| Benchmark | Nova Premier 1.0 | DeepSeek V4 Flash 0423 | Leader |
|---|---|---|---|
| IFBench | 36.2% | Not measured | Only Nova Premier 1.0 measured |
| Long context reasoning (AA-LCR) | 34.3% | Not measured | Only Nova Premier 1.0 measured |
| DTBench | Not measured | 86.4% | Only DeepSeek V4 Flash 0423 measured |
| LMCA | Not measured | 35.9% | Only DeepSeek V4 Flash 0423 measured |
| LMArena Text | Not measured | 1432 | Only DeepSeek V4 Flash 0423 measured |
| LMArena Text: instruction following | Not measured | 1421 | Only DeepSeek V4 Flash 0423 measured |
| LMArena Text: creative writing | Not measured | 1403 | Only DeepSeek V4 Flash 0423 measured |
| LMArena Text: English | Not measured | 1441 | Only DeepSeek V4 Flash 0423 measured |
| LMArena Text: non-English | Not measured | 1419 | Only DeepSeek V4 Flash 0423 measured |
| LMArena Text: Chinese | Not measured | 1463 | Only DeepSeek V4 Flash 0423 measured |
| LMArena Text: German | Not measured | 1419 | Only DeepSeek V4 Flash 0423 measured |
| LMArena Text: Japanese | Not measured | 1389 | Only DeepSeek V4 Flash 0423 measured |
| LMArena Text: Korean | Not measured | 1383 | Only DeepSeek V4 Flash 0423 measured |
| LMArena Text: French | Not measured | 1439 | Only DeepSeek V4 Flash 0423 measured |
| LMArena Text: Spanish | Not measured | 1436 | Only DeepSeek V4 Flash 0423 measured |
| LMArena Text: Russian | Not measured | 1427 | Only DeepSeek V4 Flash 0423 measured |
| LMArena Text: Polish | Not measured | 1436 | Only DeepSeek V4 Flash 0423 measured |
| LMArena Text: multi-turn | Not measured | 1449 | Only DeepSeek V4 Flash 0423 measured |
| LMArena Text: longer queries | Not measured | 1434 | Only DeepSeek V4 Flash 0423 measured |
| LMArena Text: writing and language | Not measured | 1410 | Only DeepSeek V4 Flash 0423 measured |
| LMArena Text: entertainment and media | Not measured | 1400 | Only DeepSeek V4 Flash 0423 measured |
| Neither model has a result on the other 25 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Nova Premier 1.0 | DeepSeek V4 Flash 0423 | 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 V4 Flash 0423 costs less
Repository review
50K input + 3K output tokens
DeepSeek V4 Flash 0423 costs less
Agent loop
200K input + 10K output tokens
DeepSeek V4 Flash 0423 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 V4 Flash 0423 |
|---|---|---|
| Maker | Amazon | DeepSeek |
| Weights | No public weights listed | Open weights |
| Released | October 31, 2025 | April 24, 2026 |
| Context window | 1M | 1.05M |
| Input $/Mtok | $2.50 | $0.14 |
| Output $/Mtok | $12.50 | $0.28 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 1 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Nova Premier 1.0 better than DeepSeek V4 Flash 0423 for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Nova Premier 1.0 has the edge where what matters is ALE-Bench or AA Intelligence Index, where it leads.
Which is cheaper, Nova Premier 1.0 or DeepSeek V4 Flash 0423?
Nova Premier 1.0 costs $2.50 per million input tokens and $12.50 per million output tokens; DeepSeek V4 Flash 0423 costs $0.14 and $0.28. Cost per solved task is known for neither of them.
Which has the bigger context window, Nova Premier 1.0 or DeepSeek V4 Flash 0423?
DeepSeek V4 Flash 0423, with 1.05M tokens against 1M.
How many benchmarks is the Nova Premier 1.0 vs DeepSeek V4 Flash 0423 comparison based on?
3 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 V4 Flash 0423's on 1. Where only one model has a result, the page says so instead of naming a winner.