Qwen3.5-9B vs Solar Pro 3
Qwen3.5-9B leads Solar Pro 3 on the Artificial Analysis Intelligence Index, 13.3 to 7.8, and Qwen3.5-9B costs 4.0x less per output token ($0.15 vs $0.60 per million). Updated October 22, 2026; 9 benchmarks have a result for both.
Qwen3.5-9B or Solar Pro 3: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick Qwen3.5-9B for output tokens 4.0x cheaper ($0.15 vs $0.60 per million) and a larger context window (262K against 131K tokens).
- Shared results
- 9
- Qwen3.5-9B only
- 7
- Solar Pro 3 only
- 1
- 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 7.8.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only Solar Pro 3 has a AA Agentic Index result, 1.4.
Directional only
Long documents
Listed context window
Qwen3.5-9B
Qwen3.5-9B takes 262K tokens against 131K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen3.5-9B
Qwen3.5-9B $0.0002, Solar Pro 3 $0.0004 per turn.
List prices
At a glance
- Coding index
- Qwen3.5-9B not benchmarked, Solar Pro 3 not benchmarked.
- Widest category
- General, 21.1 points apart on average over 2 shared benchmarks.
- Widest single gap
- Long context reasoning (AA-LCR): Qwen3.5-9B 70.0% against Solar Pro 3 32.3%, 37.7 points apart on a 0 to 100 scale.
- Output price
- Qwen3.5-9B $0.15 against Solar Pro 3 $0.60 per million output tokens, 4.0x apart.
- Context window
- Qwen3.5-9B takes 262K tokens, Solar Pro 3 131K.
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 | Qwen3.5-9B | Bars | Solar Pro 3 | Ties |
|---|---|---|---|---|
| Coding | 3 | 0 | ||
| Intelligence | 1 | 0 | ||
| Agentic work | 1 | 0 | ||
| Reasoning | 2 | 0 | ||
| General | 1 | 1 | ||
| All shared boards | 8 | 1 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index30
| Benchmark | Qwen3.5-9B | Solar Pro 3 | Leader |
|---|---|---|---|
| AA Coding Index | 23.5 | 16.2 | Qwen3.5-9B |
| SciCode | 29.5% | 25.5% | Qwen3.5-9B |
| Terminal-Bench Hard (Artificial Analysis run) | 24.2% | 7.6% | Qwen3.5-9B |
| Terminal-Bench | 9.2% | Not measured | Only Qwen3.5-9B measured |
| Neither model has a result on the other 39 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Qwen3.5-9B | Solar Pro 3 | Leader |
|---|---|---|---|
| AA Intelligence Index | 13.3 | 7.8 | Qwen3.5-9B |
| Epoch Capabilities Index | 139.3 | Not measured | Only Qwen3.5-9B measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Qwen3.5-9B | Solar Pro 3 | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 1.4 | Only Solar Pro 3 measured |
| τ²-Bench Telecom | 86.8% | 86.3% | 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 index20
| Benchmark | Qwen3.5-9B | Solar Pro 3 | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 80.6% | 72.4% | Qwen3.5-9B |
| Humanity's Last Exam (Artificial Analysis run) | 14.9% | 10.3% | Qwen3.5-9B |
| GPQA Diamond (Epoch AI run) | 79.0% | Not measured | Only Qwen3.5-9B measured |
| Neither model has a result on the other 20 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Qwen3.5-9B | Solar Pro 3 | Leader |
|---|---|---|---|
| OTIS Mock AIME | 61.7% | Not measured | Only Qwen3.5-9B measured |
| MathArena | 13.0% | Not measured | Only Qwen3.5-9B measured |
| Neither model has a result on the other 12 boards here | |||
KnowledgeNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Qwen3.5-9B | Solar Pro 3 | Leader |
|---|---|---|---|
| Neither model has a result on 20 boards here | |||
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Qwen3.5-9B | Solar Pro 3 | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index11
| Benchmark | Qwen3.5-9B | Solar Pro 3 | Leader |
|---|---|---|---|
| IFBench | 66.7% | 71.2% | Solar Pro 3 |
| Long context reasoning (AA-LCR) | 70.0% | 32.3% | Qwen3.5-9B |
| DTBench | 71.2% | Not measured | Only Qwen3.5-9B measured |
| LMCA | 24.5% | Not measured | Only Qwen3.5-9B measured |
| Neither model has a result on the other 44 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Qwen3.5-9B | Solar Pro 3 | 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 | Qwen3.5-9B | Upstage Solar Pro 3 |
|---|---|---|
| Maker | Qwen | Upstage |
| Weights | Open weights | No public weights listed |
| Released | March 10, 2026 | January 27, 2026 |
| Context window | 262K | 131K |
| Input $/Mtok | $0.10 | $0.15 |
| Output $/Mtok | $0.15 | $0.60 |
| 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 Qwen3.5-9B better than Solar Pro 3 for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Qwen3.5-9B for output tokens 4.0x cheaper ($0.15 vs $0.60 per million) and a larger context window (262K against 131K tokens).
Which is cheaper, Qwen3.5-9B or Solar Pro 3?
Qwen3.5-9B costs $0.10 per million input tokens and $0.15 per million output tokens; Solar Pro 3 costs $0.15 and $0.60. Cost per solved task is known for neither of them.
Which has the bigger context window, Qwen3.5-9B or Solar Pro 3?
Qwen3.5-9B, with 262K tokens against 131K.
How many benchmarks is the Qwen3.5-9B vs Solar Pro 3 comparison based on?
9 benchmarks have a result for both models as of October 22, 2026. Qwen3.5-9B's coding index rests on 0 independent benchmarks and Solar Pro 3's on 0. Where only one model has a result, the page says so instead of naming a winner.