Nova Pro 1.0 vs Qwen3.5-9B
Qwen3.5-9B leads Nova Pro 1.0 on the Artificial Analysis Intelligence Index, 13.3 to 7.0, and Qwen3.5-9B costs 21.3x less per output token ($0.15 vs $3.20 per million). Updated October 21, 2026; 7 benchmarks have a result for both.
Nova Pro 1.0 or Qwen3.5-9B: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick Nova Pro 1.0 for a larger context window (300K against 262K tokens) and work measured by Terminal-Bench Hard (Artificial Analysis run) or AA Intelligence Index, where it leads.
- Shared results
- 7
- Nova Pro 1.0 only
- 35
- Qwen3.5-9B only
- 8
- 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
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
Qwen3.5-9B
Qwen3.5-9B leads, 13.3 against 7.0.
Same board, both measured
Web design
Design Arena: websites
No call
Only Nova Pro 1.0 has a Design Arena: websites result, 796.
Directional only
Long documents
Listed context window
Nova Pro 1.0
Nova Pro 1.0 takes 300K tokens against 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen3.5-9B
Nova Pro 1.0 $0.0024, Qwen3.5-9B $0.0002 per turn.
List prices
At a glance
- Coding index
- Nova Pro 1.0 not benchmarked, Qwen3.5-9B not benchmarked.
- Widest category
- Agentic work, 72.8 points apart on average over 1 shared benchmark.
- Widest single gap
- τ²-Bench Telecom: Nova Pro 1.0 14.0% against Qwen3.5-9B 86.8%, 72.8 points apart on a 0 to 100 scale.
- Output price
- Nova Pro 1.0 $3.20 against Qwen3.5-9B $0.15 per million output tokens, 21.3x apart.
- Context window
- Nova Pro 1.0 takes 300K tokens, Qwen3.5-9B 262K.
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 Pro 1.0 | Bars | Qwen3.5-9B | Ties |
|---|---|---|---|---|
| Coding | 0 | 1 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 0 | 1 | ||
| Reasoning | 0 | 2 | ||
| General | 0 | 2 | ||
| All shared boards | 0 | 7 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index01
| Benchmark | Nova Pro 1.0 | Qwen3.5-9B | Leader |
|---|---|---|---|
| AA Coding Index | Not measured | 23.5 | Only Qwen3.5-9B measured |
| LiveCodeBench (Artificial Analysis run) | 23.3% | Not measured | Only Nova Pro 1.0 measured |
| SciCode | Not measured | 29.5% | Only Qwen3.5-9B measured |
| Terminal-Bench Hard (Artificial Analysis run) | 6.1% | 24.2% | Qwen3.5-9B |
| Terminal-Bench | Not measured | 9.2% | Only Qwen3.5-9B measured |
| LMArena Text: coding | 1270 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: software and IT | 1271 | Not measured | Only Nova Pro 1.0 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 Pro 1.0 | Qwen3.5-9B | Leader |
|---|---|---|---|
| AA Intelligence Index | 7.0 | 13.3 | Qwen3.5-9B |
| Epoch Capabilities Index | Not measured | 139.3 | Only Qwen3.5-9B measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Nova Pro 1.0 | Qwen3.5-9B | Leader |
|---|---|---|---|
| τ²-Bench Telecom | 14.0% | 86.8% | Qwen3.5-9B |
| Neither model has a result on the other 40 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Nova Pro 1.0 | Qwen3.5-9B | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 49.9% | 80.6% | Qwen3.5-9B |
| Humanity's Last Exam (Artificial Analysis run) | 3.2% | 14.9% | Qwen3.5-9B |
| GPQA Diamond (Epoch AI run) | Not measured | 79.0% | Only Qwen3.5-9B measured |
| LMArena Text: hard prompts | 1246 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: expert | 1211 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: hard prompts in English | 1259 | Not measured | Only Nova Pro 1.0 measured |
| Neither model has a result on the other 16 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
| Benchmark | Nova Pro 1.0 | Qwen3.5-9B | Leader |
|---|---|---|---|
| AA Math Index | 7.0 | Not measured | Only Nova Pro 1.0 measured |
| AIME 2025 (Artificial Analysis run) | 7.0% | Not measured | Only Nova Pro 1.0 measured |
| OTIS Mock AIME | Not measured | 61.7% | Only Qwen3.5-9B measured |
| LMArena Text: math | 1252 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: mathematical work | 1261 | Not measured | Only Nova Pro 1.0 measured |
| Neither model has a result on the other 8 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | Nova Pro 1.0 | Qwen3.5-9B | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | 69.1% | Not measured | Only Nova Pro 1.0 measured |
| MMLU | 82.0% | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: science | 1255 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: medicine and healthcare | 1260 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: legal and government | 1281 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: business and finance | 1229 | Not measured | Only Nova Pro 1.0 measured |
| Neither model has a result on the other 12 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | Nova Pro 1.0 | Qwen3.5-9B | Leader |
|---|---|---|---|
| Design Arena: websites | 796 | Not measured | Only Nova Pro 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 Pro 1.0 | Qwen3.5-9B | Leader |
|---|---|---|---|
| IFBench | 38.1% | 66.7% | Qwen3.5-9B |
| Long context reasoning (AA-LCR) | 21.0% | 70.0% | Qwen3.5-9B |
| DTBench | Not measured | 71.2% | Only Qwen3.5-9B measured |
| LMCA | Not measured | 24.5% | Only Qwen3.5-9B measured |
| LMArena Text | 1259 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: instruction following | 1235 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: creative writing | 1212 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Vision | 980 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: English | 1276 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: non-English | 1233 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: Chinese | 1244 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: German | 1243 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: Japanese | 1200 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: Korean | 1203 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: French | 1271 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: Spanish | 1182 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: Russian | 1240 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: multi-turn | 1246 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: longer queries | 1255 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: writing and language | 1247 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: entertainment and media | 1210 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Vision: English | 987 | Not measured | Only Nova Pro 1.0 measured |
| Neither model has a result on the other 24 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Nova Pro 1.0 | Qwen3.5-9B | 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
Qwen3.5-9B costs less
Repository review
50K input + 3K output tokens
Qwen3.5-9B costs less
Agent loop
200K input + 10K output tokens
Qwen3.5-9B 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 Pro 1.0 | Qwen3.5-9B |
|---|---|---|
| Maker | Amazon | Qwen |
| Weights | No public weights listed | Open weights |
| Released | December 5, 2024 | March 10, 2026 |
| Context window | 300K | 262K |
| Input $/Mtok | $0.80 | $0.10 |
| Output $/Mtok | $3.20 | $0.15 |
| 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 Pro 1.0 better than Qwen3.5-9B for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Nova Pro 1.0 for a larger context window (300K against 262K tokens) and work measured by Terminal-Bench Hard (Artificial Analysis run) or AA Intelligence Index, where it leads.
Which is cheaper, Nova Pro 1.0 or Qwen3.5-9B?
Nova Pro 1.0 costs $0.80 per million input tokens and $3.20 per million output tokens; Qwen3.5-9B costs $0.10 and $0.15. Cost per solved task is known for neither of them.
Which has the bigger context window, Nova Pro 1.0 or Qwen3.5-9B?
Nova Pro 1.0, with 300K tokens against 262K.
How many benchmarks is the Nova Pro 1.0 vs Qwen3.5-9B comparison based on?
7 benchmarks have a result for both models as of October 21, 2026. Nova Pro 1.0's coding index rests on 0 independent benchmarks and Qwen3.5-9B's on 0. Where only one model has a result, the page says so instead of naming a winner.