Nova Premier 1.0 vs GPT-5.4 Mini
GPT-5.4 Mini leads Nova Premier 1.0 on the Artificial Analysis Intelligence Index, 24.1 to 9.2, and GPT-5.4 Mini costs 2.8x less per output token ($4.50 vs $12.50 per million). Updated October 21, 2026; 9 benchmarks have a result for both.
Nova Premier 1.0 or GPT-5.4 Mini: which to pick
Only GPT-5.4 Mini has a coding score, 35.8 on the Vibe Coding Index; Nova Premier 1.0 has none, so the two cannot be ranked on coding.
Pick Nova Premier 1.0 for a larger context window (1M against 400K tokens) and work measured by Kagi LLM Benchmark, where it leads.
- Shared results
- 9
- Nova Premier 1.0 only
- 5
- GPT-5.4 Mini only
- 80
- Like-for-like categories
- 5 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
Only GPT-5.4 Mini has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
GPT-5.4 Mini
GPT-5.4 Mini leads, 24.1 against 9.2.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only GPT-5.4 Mini has a AA Agentic Index result, 17.9.
Directional only
Reasoning
GPQA Diamond
No call
Only GPT-5.4 Mini has a GPQA Diamond result, 83.1%.
Directional only
Math
AIME
No call
Only GPT-5.4 Mini has a AIME result, 95.6%.
Directional only
Knowledge
MMLU Pro
No call
Only GPT-5.4 Mini has a MMLU Pro result, 84.5%.
Directional only
Web design
Design Arena: websites
No call
Only Nova Premier 1.0 has a Design Arena: websites result, 835.
Directional only
Long documents
Listed context window
Nova Premier 1.0
Nova Premier 1.0 takes 1M tokens against 400K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GPT-5.4 Mini
Nova Premier 1.0 $0.0088, GPT-5.4 Mini $0.0030 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only GPT-5.4 Mini has the number, $0.70.
Directional only
At a glance
- Coding index
- Nova Premier 1.0 not benchmarked, GPT-5.4 Mini 35.8 from 5 benchmarks.
- Widest category
- Agentic work, 45.0 points apart on average over 1 shared benchmark.
- Widest single gap
- Terminal-Bench Hard (Artificial Analysis run): Nova Premier 1.0 6.8% against GPT-5.4 Mini 52.3%, 45.5 points apart on a 0 to 100 scale.
- Output price
- Nova Premier 1.0 $12.50 against GPT-5.4 Mini $4.50 per million output tokens, 2.8x apart.
- Context window
- Nova Premier 1.0 takes 1M tokens, GPT-5.4 Mini 400K.
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 | GPT-5.4 Mini | Ties |
|---|---|---|---|---|
| Coding | 0 | 2 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 0 | 1 | ||
| Reasoning | 1 | 2 | ||
| General | 0 | 2 | ||
| All shared boards | 1 | 8 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index02
| Benchmark | Nova Premier 1.0 | GPT-5.4 Mini | Leader |
|---|---|---|---|
| LMArena WebDev | Not measured | 1397 | Only GPT-5.4 Mini measured |
| AA Coding Index | Not measured | 56.1 | Only GPT-5.4 Mini measured |
| LiveCodeBench (Vals AI) | Not measured | 81.5% | Only GPT-5.4 Mini measured |
| SWE-bench Verified (Vals AI) | Not measured | 73.0% | Only GPT-5.4 Mini measured |
| Terminal-Bench 4 (Vals AI) | Not measured | 2.5% | Only GPT-5.4 Mini measured |
| Vibe Code Bench (Vals AI) | Not measured | 48.0% | Only GPT-5.4 Mini measured |
| Code migration (Vals AI) | Not measured | 12.9% | Only GPT-5.4 Mini measured |
| ProgramBench (Vals AI) | Not measured | 0.0% | Only GPT-5.4 Mini measured |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 54.7% | Only GPT-5.4 Mini measured |
| LiveCodeBench (Artificial Analysis run) | 31.7% | Not measured | Only Nova Premier 1.0 measured |
| SciCode | Not measured | 52.1% | Only GPT-5.4 Mini measured |
| Terminal-Bench Hard (Artificial Analysis run) | 6.8% | 52.3% | GPT-5.4 Mini |
| FrontierCode | Not measured | 27.0% | Only GPT-5.4 Mini measured |
| WeirdML | Not measured | 60.3% | Only GPT-5.4 Mini measured |
| ALE-Bench | 147.4 | 1188.6 | GPT-5.4 Mini |
| LMArena Text: coding | Not measured | 1438 | Only GPT-5.4 Mini measured |
| LMArena Text: software and IT | Not measured | 1436 | Only GPT-5.4 Mini measured |
| LMArena WebDev: React | Not measured | 1386 | Only GPT-5.4 Mini measured |
| LMArena WebDev: HTML | Not measured | 1419 | Only GPT-5.4 Mini measured |
| Neither model has a result on the other 20 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Nova Premier 1.0 | GPT-5.4 Mini | Leader |
|---|---|---|---|
| AA Intelligence Index | 9.2 | 24.1 | GPT-5.4 Mini |
| Epoch Capabilities Index | Not measured | 148.7 | Only GPT-5.4 Mini measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Nova Premier 1.0 | GPT-5.4 Mini | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 17.9 | Only GPT-5.4 Mini measured |
| Finance Agent (Vals AI) | Not measured | 45.4% | Only GPT-5.4 Mini measured |
| Tax Agent Bench (Vals AI) | Not measured | 8.8% | Only GPT-5.4 Mini measured |
| Legal Research Bench (Vals AI) | Not measured | 12.5% | Only GPT-5.4 Mini measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 45.4% | Only GPT-5.4 Mini measured |
| τ²-Bench Telecom | 38.3% | 83.3% | GPT-5.4 Mini |
| DeepResearch Bench | Not measured | 36.3% | Only GPT-5.4 Mini measured |
| Neither model has a result on the other 34 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index12
| Benchmark | Nova Premier 1.0 | GPT-5.4 Mini | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 83.1% | Only GPT-5.4 Mini measured |
| MMMU Pro (Vals AI) | Not measured | 79.3% | Only GPT-5.4 Mini measured |
| GPQA Diamond (Artificial Analysis run) | 56.9% | 87.5% | GPT-5.4 Mini |
| Humanity's Last Exam (Artificial Analysis run) | 4.2% | 28.1% | GPT-5.4 Mini |
| GPQA Diamond (Epoch AI run) | Not measured | 86.9% | Only GPT-5.4 Mini measured |
| ARC-AGI | Not measured | 63.7% | Only GPT-5.4 Mini measured |
| ARC-AGI-2 | Not measured | 18.9% | Only GPT-5.4 Mini measured |
| Chess puzzles | Not measured | 23.0% | Only GPT-5.4 Mini measured |
| Mystery game puzzles | Not measured | 11.0% | Only GPT-5.4 Mini measured |
| LMArena Text: hard prompts | Not measured | 1424 | Only GPT-5.4 Mini measured |
| LMArena Text: expert | Not measured | 1435 | Only GPT-5.4 Mini measured |
| LMArena Text: hard prompts in English | Not measured | 1420 | Only GPT-5.4 Mini measured |
| LMArena Vision: diagrams | Not measured | 1266 | Only GPT-5.4 Mini measured |
| LMArena Vision: homework | Not measured | 1285 | Only GPT-5.4 Mini measured |
| Kagi LLM Benchmark | 44.8% | 37.9% | Nova Premier 1.0 |
| Neither model has a result on the other 7 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
| Benchmark | Nova Premier 1.0 | GPT-5.4 Mini | Leader |
|---|---|---|---|
| AIME | Not measured | 95.6% | Only GPT-5.4 Mini measured |
| 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 |
| OTIS Mock AIME | Not measured | 88.9% | Only GPT-5.4 Mini measured |
| FrontierMath, tiers 1 to 3 | Not measured | 51.2% | Only GPT-5.4 Mini measured |
| FrontierMath, tier 4 | Not measured | 9.8% | Only GPT-5.4 Mini measured |
| ProofBench | Not measured | 21.0% | Only GPT-5.4 Mini measured |
| LMArena Text: math | Not measured | 1418 | Only GPT-5.4 Mini measured |
| LMArena Text: mathematical work | Not measured | 1429 | Only GPT-5.4 Mini measured |
| Neither model has a result on the other 4 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index11 boards, none shared
| Benchmark | Nova Premier 1.0 | GPT-5.4 Mini | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 84.5% | Only GPT-5.4 Mini measured |
| CaseLaw (Vals AI) | Not measured | 51.7% | Only GPT-5.4 Mini measured |
| CorpFin (Vals AI) | Not measured | 60.9% | Only GPT-5.4 Mini measured |
| TaxEval (Vals AI) | Not measured | 71.2% | Only GPT-5.4 Mini measured |
| MortgageTax (Vals AI) | Not measured | 63.5% | Only GPT-5.4 Mini measured |
| MMLU Pro (Artificial Analysis run) | 73.3% | Not measured | Only Nova Premier 1.0 measured |
| SimpleQA Verified | Not measured | 29.4% | Only GPT-5.4 Mini measured |
| LMArena Text: science | Not measured | 1417 | Only GPT-5.4 Mini measured |
| LMArena Text: medicine and healthcare | Not measured | 1395 | Only GPT-5.4 Mini measured |
| LMArena Text: legal and government | Not measured | 1414 | Only GPT-5.4 Mini measured |
| LMArena Text: business and finance | Not measured | 1418 | Only GPT-5.4 Mini measured |
| Neither model has a result on the other 7 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | Nova Premier 1.0 | GPT-5.4 Mini | Leader |
|---|---|---|---|
| Design Arena: websites | 835 | Not measured | Only Nova Premier 1.0 measured |
| Neither model has a result on the other 8 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Nova Premier 1.0 | GPT-5.4 Mini | Leader |
|---|---|---|---|
| SAGE (Vals AI) | Not measured | 50.8% | Only GPT-5.4 Mini measured |
| Vals Multimodal Index | Not measured | 54.2% | Only GPT-5.4 Mini measured |
| IFBench | 36.2% | 73.3% | GPT-5.4 Mini |
| Long context reasoning (AA-LCR) | 34.3% | 77.0% | GPT-5.4 Mini |
| DTBench | Not measured | 80.0% | Only GPT-5.4 Mini measured |
| LMCA | Not measured | 40.8% | Only GPT-5.4 Mini measured |
| LMArena Text | Not measured | 1412 | Only GPT-5.4 Mini measured |
| LMArena Text: instruction following | Not measured | 1405 | Only GPT-5.4 Mini measured |
| LMArena Text: creative writing | Not measured | 1370 | Only GPT-5.4 Mini measured |
| LMArena Vision | Not measured | 1245 | Only GPT-5.4 Mini measured |
| LMArena Text: English | Not measured | 1412 | Only GPT-5.4 Mini measured |
| LMArena Text: non-English | Not measured | 1405 | Only GPT-5.4 Mini measured |
| LMArena Text: Chinese | Not measured | 1446 | Only GPT-5.4 Mini measured |
| LMArena Text: German | Not measured | 1408 | Only GPT-5.4 Mini measured |
| LMArena Text: Japanese | Not measured | 1375 | Only GPT-5.4 Mini measured |
| LMArena Text: Korean | Not measured | 1370 | Only GPT-5.4 Mini measured |
| LMArena Text: French | Not measured | 1441 | Only GPT-5.4 Mini measured |
| LMArena Text: Spanish | Not measured | 1405 | Only GPT-5.4 Mini measured |
| LMArena Text: Russian | Not measured | 1417 | Only GPT-5.4 Mini measured |
| LMArena Text: Polish | Not measured | 1415 | Only GPT-5.4 Mini measured |
| LMArena Text: multi-turn | Not measured | 1429 | Only GPT-5.4 Mini measured |
| LMArena Text: longer queries | Not measured | 1408 | Only GPT-5.4 Mini measured |
| LMArena Text: writing and language | Not measured | 1393 | Only GPT-5.4 Mini measured |
| LMArena Text: entertainment and media | Not measured | 1373 | Only GPT-5.4 Mini measured |
| LMArena Vision: English | Not measured | 1244 | Only GPT-5.4 Mini measured |
| LMArena Vision: Chinese | Not measured | 1286 | Only GPT-5.4 Mini measured |
| LMArena Vision: reading text | Not measured | 1253 | Only GPT-5.4 Mini measured |
| LMArena Vision: humor | Not measured | 1235 | Only GPT-5.4 Mini measured |
| LMArena Vision: recognizing things | Not measured | 1218 | Only GPT-5.4 Mini measured |
| LMArena Vision: creative writing | Not measured | 1222 | Only GPT-5.4 Mini measured |
| Neither model has a result on the other 16 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Nova Premier 1.0 | GPT-5.4 Mini | 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
GPT-5.4 Mini costs less
Repository review
50K input + 3K output tokens
GPT-5.4 Mini costs less
Agent loop
200K input + 10K output tokens
GPT-5.4 Mini 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 | OpenAI GPT-5.4 Mini |
|---|---|---|
| Maker | Amazon | OpenAI |
| Weights | No public weights listed | No public weights listed |
| Released | October 31, 2025 | March 17, 2026 |
| Context window | 1M | 400K |
| Input $/Mtok | $2.50 | $0.75 |
| Output $/Mtok | $12.50 | $4.50 |
| Coding index | Not benchmarked | 35.8 |
| Independent measurements behind it | 0 | 5 |
| Cost per solved task | Not computable | $0.70 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Nova Premier 1.0 better than GPT-5.4 Mini for coding?
Only GPT-5.4 Mini has a coding score, 35.8 on the Vibe Coding Index; Nova Premier 1.0 has none, so the two cannot be ranked on coding. Pick Nova Premier 1.0 for a larger context window (1M against 400K tokens) and work measured by Kagi LLM Benchmark, where it leads.
Which is cheaper, Nova Premier 1.0 or GPT-5.4 Mini?
Nova Premier 1.0 costs $2.50 per million input tokens and $12.50 per million output tokens; GPT-5.4 Mini costs $0.75 and $4.50. Cost per solved task is known for GPT-5.4 Mini only.
Which has the bigger context window, Nova Premier 1.0 or GPT-5.4 Mini?
Nova Premier 1.0, with 1M tokens against 400K.
How many benchmarks is the Nova Premier 1.0 vs GPT-5.4 Mini comparison based on?
9 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 GPT-5.4 Mini's on 5. Where only one model has a result, the page says so instead of naming a winner.