Nova Premier 1.0 vs GPT-6 Sol
GPT-6 Sol leads Nova Premier 1.0 on the Artificial Analysis Intelligence Index, 47.6 to 9.2, and GPT-6 Sol costs 1.3x less per output token ($10.00 vs $12.50 per million). Updated October 21, 2026; 5 benchmarks have a result for both.
Nova Premier 1.0 or GPT-6 Sol: which to pick
Only GPT-6 Sol has a coding score, 76.0 on the Vibe Coding Index; Nova Premier 1.0 has none, so the two cannot be ranked on coding.
Compare them on price, context and the boards below.
- Shared results
- 5
- Nova Premier 1.0 only
- 8
- GPT-6 Sol only
- 95
- 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-6 Sol has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
GPT-6 Sol
GPT-6 Sol leads, 47.6 against 9.2.
Same board, both measured
Web design
Design Arena: websites
GPT-6 Sol
GPT-6 Sol leads, 1292 against 835.
Same board, both measured
Long documents
Listed context window
GPT-6 Sol
GPT-6 Sol takes 1.05M tokens against 1M.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GPT-6 Sol
Nova Premier 1.0 $0.0088, GPT-6 Sol $0.0070 per turn.
List prices
At a glance
- Coding index
- Nova Premier 1.0 not benchmarked, GPT-6 Sol 76.0 from 5 benchmarks.
- Widest category
- Coding, 77.2 points apart on average over 1 shared benchmark.
- Widest single gap
- ALE-Bench: Nova Premier 1.0 147.4 against GPT-6 Sol 2462.0, 77.2 points apart on a 0 to 100 scale.
- Output price
- Nova Premier 1.0 $12.50 against GPT-6 Sol $10.00 per million output tokens, 1.3x apart.
- Context window
- Nova Premier 1.0 takes 1M tokens, GPT-6 Sol 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 | GPT-6 Sol | Ties |
|---|---|---|---|---|
| Coding | 0 | 1 | ||
| Intelligence | 0 | 1 | ||
| Reasoning | 0 | 1 | ||
| Web design | 0 | 1 | ||
| General | 0 | 1 | ||
| All shared boards | 0 | 5 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index01
| Benchmark | Nova Premier 1.0 | GPT-6 Sol | Leader |
|---|---|---|---|
| LiveBench coding | Not measured | 93.1% | Only GPT-6 Sol measured |
| LMArena WebDev | Not measured | 1683 | Only GPT-6 Sol measured |
| Terminal-Bench 4 (Vals AI) | Not measured | 44.4% | Only GPT-6 Sol measured |
| Vibe Code Bench (Vals AI) | Not measured | 87.8% | Only GPT-6 Sol measured |
| Code migration (Vals AI) | Not measured | 57.2% | Only GPT-6 Sol measured |
| ProgramBench (Vals AI) | Not measured | 2.0% | Only GPT-6 Sol measured |
| IOI (Vals AI) | Not measured | 82.6% | Only GPT-6 Sol measured |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 83.2% | Only GPT-6 Sol measured |
| CyberBench (Vals AI) | Not measured | 78.0% | Only GPT-6 Sol measured |
| LiveCodeBench (Artificial Analysis run) | 31.7% | Not measured | Only Nova Premier 1.0 measured |
| SciCode | Not measured | 57.6% | Only GPT-6 Sol measured |
| Terminal-Bench Hard (Artificial Analysis run) | 6.8% | Not measured | Only Nova Premier 1.0 measured |
| FrontierCode | Not measured | 49.3% | Only GPT-6 Sol measured |
| ALE-Bench | 147.4 | 2462.0 | GPT-6 Sol |
| LMArena Text: coding | Not measured | 1448 | Only GPT-6 Sol measured |
| LMArena Text: software and IT | Not measured | 1433 | Only GPT-6 Sol measured |
| LMArena WebDev: React | Not measured | 1685 | Only GPT-6 Sol measured |
| LMArena WebDev: HTML | Not measured | 1685 | Only GPT-6 Sol measured |
| LMArena WebDev: from an image | Not measured | 1660 | Only GPT-6 Sol measured |
| Neither model has a result on the other 19 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Nova Premier 1.0 | GPT-6 Sol | Leader |
|---|---|---|---|
| AA Intelligence Index | 9.2 | 47.6 | GPT-6 Sol |
| Epoch Capabilities Index | Not measured | 163.7 | Only GPT-6 Sol measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index18 boards, none shared
| Benchmark | Nova Premier 1.0 | GPT-6 Sol | Leader |
|---|---|---|---|
| Design Arena: agents building web apps | Not measured | 1231 | Only GPT-6 Sol measured |
| Design Arena: agents building full-stack apps | Not measured | 1238 | Only GPT-6 Sol measured |
| Design Arena: agents building mobile apps | Not measured | 1214 | Only GPT-6 Sol measured |
| LiveBench research | Not measured | 69.3% | Only GPT-6 Sol measured |
| LiveBench browser | Not measured | 92.0% | Only GPT-6 Sol measured |
| LiveBench long agentic | Not measured | 66.9% | Only GPT-6 Sol measured |
| SREBench (Vals AI) | Not measured | 30.5% | Only GPT-6 Sol measured |
| Finance Agent (Vals AI) | Not measured | 49.0% | Only GPT-6 Sol measured |
| Tax Agent Bench (Vals AI) | Not measured | 15.0% | Only GPT-6 Sol measured |
| Legal Research Bench (Vals AI) | Not measured | 28.9% | Only GPT-6 Sol measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 71.5% | Only GPT-6 Sol measured |
| BioMysteryBench (Vals AI) | Not measured | 74.8% | Only GPT-6 Sol measured |
| Terminal-Bench-Science (Vals AI) | Not measured | 30.0% | Only GPT-6 Sol measured |
| Vals Science Index | Not measured | 45.0% | Only GPT-6 Sol measured |
| τ²-Bench Telecom | 38.3% | Not measured | Only Nova Premier 1.0 measured |
| APEX-Agents | Not measured | 54.3% | Only GPT-6 Sol measured |
| SpireClimb | Not measured | 7.5% | Only GPT-6 Sol measured |
| Vending-Bench 2 | Not measured | $14,428 | Only GPT-6 Sol measured |
| Neither model has a result on the other 21 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Nova Premier 1.0 | GPT-6 Sol | Leader |
|---|---|---|---|
| LiveBench reasoning | Not measured | 88.7% | Only GPT-6 Sol measured |
| MysteryMechanism (Vals AI) | Not measured | 30.2% | Only GPT-6 Sol measured |
| GPQA Diamond (Artificial Analysis run) | 56.9% | Not measured | Only Nova Premier 1.0 measured |
| Humanity's Last Exam (Artificial Analysis run) | 4.2% | 47.9% | GPT-6 Sol |
| GPQA Diamond (Epoch AI run) | Not measured | 94.3% | Only GPT-6 Sol measured |
| ARC-AGI | Not measured | 95.5% | Only GPT-6 Sol measured |
| ARC-AGI-2 | Not measured | 89.6% | Only GPT-6 Sol measured |
| Chess puzzles | Not measured | 56.0% | Only GPT-6 Sol measured |
| Mystery game puzzles | Not measured | 56.0% | Only GPT-6 Sol measured |
| EBR-bench | Not measured | 53.3% | Only GPT-6 Sol measured |
| LMArena Text: hard prompts | Not measured | 1422 | Only GPT-6 Sol measured |
| LMArena Text: expert | Not measured | 1437 | Only GPT-6 Sol measured |
| LMArena Text: hard prompts in English | Not measured | 1420 | Only GPT-6 Sol measured |
| LMArena Vision: diagrams | Not measured | 1270 | Only GPT-6 Sol measured |
| LMArena Vision: homework | Not measured | 1286 | Only GPT-6 Sol measured |
| Neither model has a result on the other 6 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | Nova Premier 1.0 | GPT-6 Sol | 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 |
| OTIS Mock AIME | Not measured | 100.0% | Only GPT-6 Sol measured |
| FrontierMath, tiers 1 to 3 | Not measured | 89.8% | Only GPT-6 Sol measured |
| FrontierMath, tier 4 | Not measured | 90.0% | Only GPT-6 Sol measured |
| ProofBench | Not measured | 83.0% | Only GPT-6 Sol measured |
| LMArena Text: math | Not measured | 1407 | Only GPT-6 Sol measured |
| LMArena Text: mathematical work | Not measured | 1424 | Only GPT-6 Sol measured |
| Neither model has a result on the other 5 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
| Benchmark | Nova Premier 1.0 | GPT-6 Sol | Leader |
|---|---|---|---|
| MedCode (Vals AI) | Not measured | 47.1% | Only GPT-6 Sol measured |
| MMLU Pro (Artificial Analysis run) | 73.3% | Not measured | Only Nova Premier 1.0 measured |
| SimpleQA Verified | Not measured | 60.7% | Only GPT-6 Sol measured |
| LMArena Text: science | Not measured | 1389 | Only GPT-6 Sol measured |
| LMArena Text: medicine and healthcare | Not measured | 1366 | Only GPT-6 Sol measured |
| LMArena Text: legal and government | Not measured | 1396 | Only GPT-6 Sol measured |
| LMArena Text: business and finance | Not measured | 1380 | Only GPT-6 Sol measured |
| Neither model has a result on the other 10 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Nova Premier 1.0 | GPT-6 Sol | Leader |
|---|---|---|---|
| Design Arena: websites | 835 | 1292 | GPT-6 Sol |
| Design Arena: UI components | Not measured | 1292 | Only GPT-6 Sol measured |
| Design Arena: game dev | Not measured | 1314 | Only GPT-6 Sol measured |
| Design Arena: data viz | Not measured | 1269 | Only GPT-6 Sol measured |
| Design Arena: 3D | Not measured | 1318 | Only GPT-6 Sol measured |
| Design Arena: all code categories | Not measured | 1301 | Only GPT-6 Sol measured |
| Design Arena: SVG | Not measured | 1316 | Only GPT-6 Sol measured |
| Design Arena: ASCII art | Not measured | 1225 | Only GPT-6 Sol measured |
| LiveBench design | Not measured | 82.2% | Only GPT-6 Sol measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Nova Premier 1.0 | GPT-6 Sol | Leader |
|---|---|---|---|
| LiveBench data analysis | Not measured | 81.2% | Only GPT-6 Sol measured |
| Public Benefits Bench (Vals AI) | Not measured | 56.6% | Only GPT-6 Sol measured |
| SAGE (Vals AI) | Not measured | 44.8% | Only GPT-6 Sol measured |
| MedScribe (Vals AI) | Not measured | 82.0% | Only GPT-6 Sol measured |
| IFBench | 36.2% | Not measured | Only Nova Premier 1.0 measured |
| Long context reasoning (AA-LCR) | 34.3% | 83.7% | GPT-6 Sol |
| DTBench | Not measured | 97.3% | Only GPT-6 Sol measured |
| LMCA | Not measured | 59.1% | Only GPT-6 Sol measured |
| Furniture assembly | Not measured | 58.3% | Only GPT-6 Sol measured |
| LMArena Text | Not measured | 1398 | Only GPT-6 Sol measured |
| LMArena Text: instruction following | Not measured | 1413 | Only GPT-6 Sol measured |
| LMArena Text: creative writing | Not measured | 1378 | Only GPT-6 Sol measured |
| LMArena Vision | Not measured | 1240 | Only GPT-6 Sol measured |
| LMArena Text: English | Not measured | 1396 | Only GPT-6 Sol measured |
| LMArena Text: non-English | Not measured | 1388 | Only GPT-6 Sol measured |
| LMArena Text: Chinese | Not measured | 1412 | Only GPT-6 Sol measured |
| LMArena Text: German | Not measured | 1379 | Only GPT-6 Sol measured |
| LMArena Text: Japanese | Not measured | 1377 | Only GPT-6 Sol measured |
| LMArena Text: Korean | Not measured | 1336 | Only GPT-6 Sol measured |
| LMArena Text: French | Not measured | 1399 | Only GPT-6 Sol measured |
| LMArena Text: Spanish | Not measured | 1387 | Only GPT-6 Sol measured |
| LMArena Text: Russian | Not measured | 1402 | Only GPT-6 Sol measured |
| LMArena Text: Polish | Not measured | 1372 | Only GPT-6 Sol measured |
| LMArena Text: multi-turn | Not measured | 1414 | Only GPT-6 Sol measured |
| LMArena Text: longer queries | Not measured | 1416 | Only GPT-6 Sol measured |
| LMArena Text: writing and language | Not measured | 1389 | Only GPT-6 Sol measured |
| LMArena Text: entertainment and media | Not measured | 1373 | Only GPT-6 Sol measured |
| LMArena Vision: English | Not measured | 1229 | Only GPT-6 Sol measured |
| LMArena Vision: reading text | Not measured | 1258 | Only GPT-6 Sol measured |
| LMArena Vision: creative writing | Not measured | 1219 | Only GPT-6 Sol 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-6 Sol | 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-6 Sol costs less
Repository review
50K input + 3K output tokens
GPT-6 Sol costs less
Agent loop
200K input + 10K output tokens
GPT-6 Sol 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-6 Sol |
|---|---|---|
| Maker | Amazon | OpenAI |
| Weights | No public weights listed | No public weights listed |
| Released | October 31, 2025 | September 22, 2026 |
| Context window | 1M | 1.05M |
| Input $/Mtok | $2.50 | $2.00 |
| Output $/Mtok | $12.50 | $10.00 |
| Coding index | Not benchmarked | 76.0 |
| Independent measurements behind it | 0 | 5 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Nova Premier 1.0 better than GPT-6 Sol for coding?
Only GPT-6 Sol has a coding score, 76.0 on the Vibe Coding Index; Nova Premier 1.0 has none, so the two cannot be ranked on coding. Compare them on price, context and the boards below.
Which is cheaper, Nova Premier 1.0 or GPT-6 Sol?
Nova Premier 1.0 costs $2.50 per million input tokens and $12.50 per million output tokens; GPT-6 Sol costs $2.00 and $10.00. Cost per solved task is known for neither of them.
Which has the bigger context window, Nova Premier 1.0 or GPT-6 Sol?
GPT-6 Sol, with 1.05M tokens against 1M.
How many benchmarks is the Nova Premier 1.0 vs GPT-6 Sol comparison based on?
5 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-6 Sol's on 5. Where only one model has a result, the page says so instead of naming a winner.