Nova Premier 1.0 vs Qwen3.5 Plus 2026-04-20
Qwen3.5 Plus 2026-04-20 costs 6.9x less per output token than Nova Premier 1.0 ($1.80 vs $12.50 per million). Updated October 22, 2026; 1 benchmarks have a result for both.
Nova Premier 1.0 or Qwen3.5 Plus 2026-04-20: which to pick
Only Qwen3.5 Plus 2026-04-20 has a coding score, 39.5 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
- 1
- Nova Premier 1.0 only
- 13
- Qwen3.5 Plus 2026-04-20 only
- 24
- Like-for-like categories
- 1 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 Qwen3.5 Plus 2026-04-20 has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
No call
Only Nova Premier 1.0 has a AA Intelligence Index result, 9.2.
Directional only
Reasoning
GPQA Diamond
No call
Only Qwen3.5 Plus 2026-04-20 has a GPQA Diamond result, 87.4%.
Directional only
Math
AIME
No call
Only Qwen3.5 Plus 2026-04-20 has a AIME result, 86.0%.
Directional only
Knowledge
MMLU Pro
No call
Only Qwen3.5 Plus 2026-04-20 has a MMLU Pro result, 87.2%.
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
No call
Both take 1M tokens.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen3.5 Plus 2026-04-20
Nova Premier 1.0 $0.0088, Qwen3.5 Plus 2026-04-20 $0.0012 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Qwen3.5 Plus 2026-04-20 has the number, $1.35.
Directional only
At a glance
- Coding index
- Nova Premier 1.0 not benchmarked, Qwen3.5 Plus 2026-04-20 39.5 from 2 benchmarks.
- Widest category
- Coding, 15.4 points apart on average over 1 shared benchmark.
- Widest single gap
- ALE-Bench: Nova Premier 1.0 147.4 against Qwen3.5 Plus 2026-04-20 608.9, 15.4 points apart on a 0 to 100 scale.
- Output price
- Nova Premier 1.0 $12.50 against Qwen3.5 Plus 2026-04-20 $1.80 per million output tokens, 6.9x apart.
- Context window
- Both take 1M tokens.
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 | Qwen3.5 Plus 2026-04-20 | Ties |
|---|---|---|---|---|
| Coding | 0 | 1 | ||
| All shared boards | 0 | 1 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index01
| Benchmark | Nova Premier 1.0 | Qwen3.5 Plus 2026-04-20 | Leader |
|---|---|---|---|
| LiveCodeBench (Vals AI) | Not measured | 85.3% | Only Qwen3.5 Plus 2026-04-20 measured |
| SWE-bench Verified (Vals AI) | Not measured | 71.2% | Only Qwen3.5 Plus 2026-04-20 measured |
| Vibe Code Bench (Vals AI) | Not measured | 15.7% | Only Qwen3.5 Plus 2026-04-20 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 |
| ALE-Bench | 147.4 | 608.9 | Qwen3.5 Plus 2026-04-20 |
| Neither model has a result on the other 33 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Nova Premier 1.0 | Qwen3.5 Plus 2026-04-20 | Leader |
|---|---|---|---|
| AA Intelligence Index | 9.2 | Not measured | Only Nova Premier 1.0 measured |
| Epoch Capabilities Index | Not measured | 146.2 | Only Qwen3.5 Plus 2026-04-20 measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Nova Premier 1.0 | Qwen3.5 Plus 2026-04-20 | Leader |
|---|---|---|---|
| τ²-Bench Telecom | 38.3% | Not measured | Only Nova Premier 1.0 measured |
| Vending-Bench 2 | Not measured | $1 | Only Qwen3.5 Plus 2026-04-20 measured |
| Neither model has a result on the other 39 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | Nova Premier 1.0 | Qwen3.5 Plus 2026-04-20 | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 87.4% | Only Qwen3.5 Plus 2026-04-20 measured |
| MMMU Pro (Vals AI) | Not measured | 22.8% | Only Qwen3.5 Plus 2026-04-20 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% | Not measured | Only Nova Premier 1.0 measured |
| GPQA Diamond (Epoch AI run) | Not measured | 84.8% | Only Qwen3.5 Plus 2026-04-20 measured |
| Chess puzzles | Not measured | 8.0% | Only Qwen3.5 Plus 2026-04-20 measured |
| Mystery game puzzles | Not measured | 17.0% | Only Qwen3.5 Plus 2026-04-20 measured |
| Kagi LLM Benchmark | 44.8% | Not measured | Only Nova Premier 1.0 measured |
| Neither model has a result on the other 14 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
| Benchmark | Nova Premier 1.0 | Qwen3.5 Plus 2026-04-20 | Leader |
|---|---|---|---|
| AIME | Not measured | 86.0% | Only Qwen3.5 Plus 2026-04-20 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 | 86.7% | Only Qwen3.5 Plus 2026-04-20 measured |
| Neither model has a result on the other 9 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | Nova Premier 1.0 | Qwen3.5 Plus 2026-04-20 | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 87.2% | Only Qwen3.5 Plus 2026-04-20 measured |
| LegalBench (Vals AI) | Not measured | 85.1% | Only Qwen3.5 Plus 2026-04-20 measured |
| CaseLaw (Vals AI) | Not measured | 59.7% | Only Qwen3.5 Plus 2026-04-20 measured |
| CorpFin (Vals AI) | Not measured | 65.3% | Only Qwen3.5 Plus 2026-04-20 measured |
| MortgageTax (Vals AI) | Not measured | 60.8% | Only Qwen3.5 Plus 2026-04-20 measured |
| MedQA (Vals AI) | Not measured | 95.2% | Only Qwen3.5 Plus 2026-04-20 measured |
| MMLU Pro (Artificial Analysis run) | 73.3% | Not measured | Only Nova Premier 1.0 measured |
| SimpleQA Verified | Not measured | 25.4% | Only Qwen3.5 Plus 2026-04-20 measured |
| Neither model has a result on the other 10 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | Nova Premier 1.0 | Qwen3.5 Plus 2026-04-20 | Leader |
|---|---|---|---|
| Design Arena: websites | 835 | Not measured | Only Nova Premier 1.0 measured |
| Neither model has a result on the other 8 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
| Benchmark | Nova Premier 1.0 | Qwen3.5 Plus 2026-04-20 | Leader |
|---|---|---|---|
| SAGE (Vals AI) | Not measured | 30.4% | Only Qwen3.5 Plus 2026-04-20 measured |
| 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 | 80.5% | Only Qwen3.5 Plus 2026-04-20 measured |
| LMCA | Not measured | 36.4% | Only Qwen3.5 Plus 2026-04-20 measured |
| CL-bench | Not measured | 19.8% | Only Qwen3.5 Plus 2026-04-20 measured |
| CL-bench Life | Not measured | 12.4% | Only Qwen3.5 Plus 2026-04-20 measured |
| Neither model has a result on the other 39 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Nova Premier 1.0 | Qwen3.5 Plus 2026-04-20 | 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
Qwen3.5 Plus 2026-04-20 costs less
Repository review
50K input + 3K output tokens
Qwen3.5 Plus 2026-04-20 costs less
Agent loop
200K input + 10K output tokens
Qwen3.5 Plus 2026-04-20 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 | Qwen3.5 Plus 2026-04-20 |
|---|---|---|
| Maker | Amazon | Qwen |
| Weights | No public weights listed | No public weights listed |
| Released | October 31, 2025 | April 27, 2026 |
| Context window | 1M | 1M |
| Input $/Mtok | $2.50 | $0.30 |
| Output $/Mtok | $12.50 | $1.80 |
| Coding index | Not benchmarked | 39.5 |
| Independent measurements behind it | 0 | 2 |
| Cost per solved task | Not computable | $1.35 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Nova Premier 1.0 better than Qwen3.5 Plus 2026-04-20 for coding?
Only Qwen3.5 Plus 2026-04-20 has a coding score, 39.5 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 Qwen3.5 Plus 2026-04-20?
Nova Premier 1.0 costs $2.50 per million input tokens and $12.50 per million output tokens; Qwen3.5 Plus 2026-04-20 costs $0.30 and $1.80. Cost per solved task is known for Qwen3.5 Plus 2026-04-20 only.
Which has the bigger context window, Nova Premier 1.0 or Qwen3.5 Plus 2026-04-20?
Neither: both take 1M tokens.
How many benchmarks is the Nova Premier 1.0 vs Qwen3.5 Plus 2026-04-20 comparison based on?
1 benchmarks have a result for both models as of October 22, 2026. Nova Premier 1.0's coding index rests on 0 independent benchmarks and Qwen3.5 Plus 2026-04-20's on 2. Where only one model has a result, the page says so instead of naming a winner.