GPT-5.6 Sol Pro vs Qwen3.5-9B
Qwen3.5-9B costs 133.3x less per output token than GPT-5.6 Sol Pro ($0.15 vs $20.00 per million). Updated October 22, 2026; 2 benchmarks have a result for both.
GPT-5.6 Sol Pro or Qwen3.5-9B: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick GPT-5.6 Sol Pro for a larger context window (1.05M against 262K tokens).
- Shared results
- 2
- GPT-5.6 Sol Pro only
- 5
- Qwen3.5-9B only
- 13
- 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
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
No call
Only Qwen3.5-9B has a AA Intelligence Index result, 13.3.
Directional only
Long documents
Listed context window
GPT-5.6 Sol Pro
GPT-5.6 Sol Pro takes 1.05M tokens against 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen3.5-9B
GPT-5.6 Sol Pro $0.014, Qwen3.5-9B $0.0002 per turn.
List prices
At a glance
- Coding index
- GPT-5.6 Sol Pro not benchmarked, Qwen3.5-9B not benchmarked.
- Widest category
- General, 29.8 points apart on average over 2 shared benchmarks.
- Widest single gap
- LMCA: GPT-5.6 Sol Pro 59.2% against Qwen3.5-9B 24.5%, 34.7 points apart on a 0 to 100 scale.
- Output price
- GPT-5.6 Sol Pro $20.00 against Qwen3.5-9B $0.15 per million output tokens, 133.3x apart.
- Context window
- GPT-5.6 Sol Pro takes 1.05M 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 | GPT-5.6 Sol Pro | Bars | Qwen3.5-9B | Ties |
|---|---|---|---|---|
| General | 2 | 0 | ||
| All shared boards | 2 | 0 |
CodingDirectional onlySix of these boards feed the Vibe Coding Index5 boards, none shared
| Benchmark | GPT-5.6 Sol Pro | Qwen3.5-9B | Leader |
|---|---|---|---|
| AA Coding Index | Not measured | 23.5 | Only Qwen3.5-9B measured |
| SciCode | Not measured | 29.5% | Only Qwen3.5-9B measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 24.2% | Only Qwen3.5-9B measured |
| Terminal-Bench | Not measured | 9.2% | Only Qwen3.5-9B measured |
| WeirdML | 89.4% | Not measured | Only GPT-5.6 Sol Pro measured |
| Neither model has a result on the other 34 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | GPT-5.6 Sol Pro | Qwen3.5-9B | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 13.3 | Only Qwen3.5-9B measured |
| Epoch Capabilities Index | Not measured | 139.3 | Only Qwen3.5-9B measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | GPT-5.6 Sol Pro | Qwen3.5-9B | Leader |
|---|---|---|---|
| τ²-Bench Telecom | Not measured | 86.8% | Only Qwen3.5-9B measured |
| APEX-Agents | 51.4% | Not measured | Only GPT-5.6 Sol Pro measured |
| Neither model has a result on the other 39 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
| Benchmark | GPT-5.6 Sol Pro | Qwen3.5-9B | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | Not measured | 80.6% | Only Qwen3.5-9B measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 14.9% | Only Qwen3.5-9B measured |
| GPQA Diamond (Epoch AI run) | Not measured | 79.0% | Only Qwen3.5-9B measured |
| SimpleBench | 71.7% | Not measured | Only GPT-5.6 Sol Pro measured |
| Chess puzzles | 68.0% | Not measured | Only GPT-5.6 Sol Pro measured |
| Neither model has a result on the other 17 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | GPT-5.6 Sol Pro | Qwen3.5-9B | Leader |
|---|---|---|---|
| OTIS Mock AIME | Not measured | 61.7% | Only Qwen3.5-9B measured |
| FrontierMath, tier 4 | 80.5% | Not measured | Only GPT-5.6 Sol Pro measured |
| Neither model has a result on the other 11 boards here | |||
KnowledgeNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-5.6 Sol Pro | Qwen3.5-9B | Leader |
|---|---|---|---|
| Neither model has a result on 18 boards here | |||
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-5.6 Sol Pro | Qwen3.5-9B | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GPT-5.6 Sol Pro | Qwen3.5-9B | Leader |
|---|---|---|---|
| IFBench | Not measured | 66.7% | Only Qwen3.5-9B measured |
| Long context reasoning (AA-LCR) | Not measured | 70.0% | Only Qwen3.5-9B measured |
| DTBench | 96.0% | 71.2% | GPT-5.6 Sol Pro |
| LMCA | 59.2% | 24.5% | GPT-5.6 Sol Pro |
| Neither model has a result on the other 42 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-5.6 Sol Pro | 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 | OpenAI GPT-5.6 Sol Pro | Qwen3.5-9B |
|---|---|---|
| Maker | OpenAI | Qwen |
| Weights | No public weights listed | Open weights |
| Released | July 9, 2026 | March 10, 2026 |
| Context window | 1.05M | 262K |
| Input $/Mtok | $4.00 | $0.10 |
| Output $/Mtok | $20.00 | $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 GPT-5.6 Sol Pro better than Qwen3.5-9B for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GPT-5.6 Sol Pro for a larger context window (1.05M against 262K tokens).
Which is cheaper, GPT-5.6 Sol Pro or Qwen3.5-9B?
GPT-5.6 Sol Pro costs $4.00 per million input tokens and $20.00 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, GPT-5.6 Sol Pro or Qwen3.5-9B?
GPT-5.6 Sol Pro, with 1.05M tokens against 262K.
How many benchmarks is the GPT-5.6 Sol Pro vs Qwen3.5-9B comparison based on?
2 benchmarks have a result for both models as of October 22, 2026. GPT-5.6 Sol Pro'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.