Qwen3 235B A22B Instruct 2507 vs Qwen3.7 Plus
Qwen3.7 Plus leads Qwen3 235B A22B Instruct 2507 on the Artificial Analysis Intelligence Index, 25.2 to 12.0, and Qwen3 235B A22B Instruct 2507 costs 1.7x less per output token ($0.775 vs $1.28 per million). Updated October 22, 2026; 16 benchmarks have a result for both.
Qwen3 235B A22B Instruct 2507 or Qwen3.7 Plus: which to pick
Only Qwen3.7 Plus has a coding score, 33.2 on the Vibe Coding Index; Qwen3 235B A22B Instruct 2507 has none, so the two cannot be ranked on coding.
Pick Qwen3 235B A22B Instruct 2507 for output tokens 1.7x cheaper ($0.775 vs $1.28 per million).
- Shared results
- 16
- Qwen3 235B A22B Instruct 2507 only
- 8
- Qwen3.7 Plus only
- 59
- Like-for-like categories
- 6 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 Qwen3.7 Plus has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
Qwen3.7 Plus
Qwen3.7 Plus leads, 25.2 against 12.0.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only Qwen3.7 Plus has a AA Agentic Index result, 17.5.
Directional only
Web design
Design Arena: websites
Qwen3.7 Plus
Qwen3.7 Plus leads, 1269 against 1058.
Same board, both measured
Long documents
Listed context window
Qwen3.7 Plus
Qwen3.7 Plus takes 1M tokens against 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen3 235B A22B Instruct 2507
Qwen3 235B A22B Instruct 2507 $0.0005, Qwen3.7 Plus $0.0010 per turn.
List prices
At a glance
- Coding index
- Qwen3 235B A22B Instruct 2507 not benchmarked, Qwen3.7 Plus 33.2 from 2 benchmarks.
- Widest category
- Agentic work, 39.8 points apart on average over 1 shared benchmark.
- Widest single gap
- τ²-Bench Telecom: Qwen3 235B A22B Instruct 2507 53.2% against Qwen3.7 Plus 93.0%, 39.8 points apart on a 0 to 100 scale.
- Output price
- Qwen3 235B A22B Instruct 2507 $0.775 against Qwen3.7 Plus $1.28 per million output tokens, 1.7x apart.
- Context window
- Qwen3 235B A22B Instruct 2507 takes 262K tokens, Qwen3.7 Plus 1M.
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 235B A22B Instruct 2507 | Bars | Qwen3.7 Plus | Ties |
|---|---|---|---|---|
| Coding | 0 | 2 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 0 | 1 | ||
| Reasoning | 0 | 2 | ||
| Web design | 0 | 6 | ||
| General | 0 | 4 | ||
| All shared boards | 0 | 16 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index02
| Benchmark | Qwen3 235B A22B Instruct 2507 | Qwen3.7 Plus | Leader |
|---|---|---|---|
| AA Coding Index | Not measured | 55.9 | Only Qwen3.7 Plus measured |
| Vibe Code Bench (Vals AI) | Not measured | 46.4% | Only Qwen3.7 Plus measured |
| Code migration (Vals AI) | Not measured | 12.9% | Only Qwen3.7 Plus measured |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 52.8% | Only Qwen3.7 Plus measured |
| SkillsBench (Vals AI) | Not measured | 54.3% | Only Qwen3.7 Plus measured |
| LiveCodeBench (Artificial Analysis run) | 78.8% | Not measured | Only Qwen3 235B A22B Instruct 2507 measured |
| SciCode | 41.4% | 46.1% | Qwen3.7 Plus |
| Terminal-Bench Hard (Artificial Analysis run) | 15.2% | 47.0% | Qwen3.7 Plus |
| FrontierCode | Not measured | 10.2% | Only Qwen3.7 Plus measured |
| WeirdML | 38.7% | Not measured | Only Qwen3 235B A22B Instruct 2507 measured |
| LMArena Text: coding | Not measured | 1473 | Only Qwen3.7 Plus measured |
| LMArena Text: software and IT | Not measured | 1473 | Only Qwen3.7 Plus measured |
| Neither model has a result on the other 31 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Qwen3 235B A22B Instruct 2507 | Qwen3.7 Plus | Leader |
|---|---|---|---|
| AA Intelligence Index | 12.0 | 25.2 | Qwen3.7 Plus |
| Epoch Capabilities Index | Not measured | 147.0 | Only Qwen3.7 Plus measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Qwen3 235B A22B Instruct 2507 | Qwen3.7 Plus | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 17.5 | Only Qwen3.7 Plus measured |
| Finance Agent (Vals AI) | Not measured | 38.2% | Only Qwen3.7 Plus measured |
| Tax Agent Bench (Vals AI) | Not measured | 10.5% | Only Qwen3.7 Plus measured |
| Legal Research Bench (Vals AI) | Not measured | 16.4% | Only Qwen3.7 Plus measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 49.3% | Only Qwen3.7 Plus measured |
| τ²-Bench Telecom | 53.2% | 93.0% | Qwen3.7 Plus |
| OSWorld 2.0 | Not measured | 2.8% | Only Qwen3.7 Plus measured |
| Berkeley Function Calling Leaderboard (BFCL) | 52.1% | Not measured | Only Qwen3 235B A22B Instruct 2507 measured |
| Neither model has a result on the other 34 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Qwen3 235B A22B Instruct 2507 | Qwen3.7 Plus | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 79.0% | 90.0% | Qwen3.7 Plus |
| Humanity's Last Exam (Artificial Analysis run) | 15.9% | 35.6% | Qwen3.7 Plus |
| GPQA Diamond (Epoch AI run) | Not measured | 87.9% | Only Qwen3.7 Plus measured |
| ARC-AGI | 11.0% | Not measured | Only Qwen3 235B A22B Instruct 2507 measured |
| ARC-AGI-2 | 1.3% | Not measured | Only Qwen3 235B A22B Instruct 2507 measured |
| Mystery game puzzles | Not measured | 17.0% | Only Qwen3.7 Plus measured |
| LMArena Text: hard prompts | Not measured | 1460 | Only Qwen3.7 Plus measured |
| LMArena Text: expert | Not measured | 1466 | Only Qwen3.7 Plus measured |
| LMArena Text: hard prompts in English | Not measured | 1460 | Only Qwen3.7 Plus measured |
| LMArena Vision: diagrams | Not measured | 1292 | Only Qwen3.7 Plus measured |
| LMArena Vision: homework | Not measured | 1295 | Only Qwen3.7 Plus measured |
| Neither model has a result on the other 12 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | Qwen3 235B A22B Instruct 2507 | Qwen3.7 Plus | Leader |
|---|---|---|---|
| AA Math Index | 91.0 | Not measured | Only Qwen3 235B A22B Instruct 2507 measured |
| AIME 2025 (Artificial Analysis run) | 91.0% | Not measured | Only Qwen3 235B A22B Instruct 2507 measured |
| OTIS Mock AIME | Not measured | 93.3% | Only Qwen3.7 Plus measured |
| FrontierMath, tiers 1 to 3 | Not measured | 34.4% | Only Qwen3.7 Plus measured |
| LMArena Text: math | Not measured | 1467 | Only Qwen3.7 Plus measured |
| LMArena Text: mathematical work | Not measured | 1470 | Only Qwen3.7 Plus 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 | Qwen3 235B A22B Instruct 2507 | Qwen3.7 Plus | Leader |
|---|---|---|---|
| MortgageTax (Vals AI) | Not measured | 66.2% | Only Qwen3.7 Plus measured |
| MMLU Pro (Artificial Analysis run) | 84.3% | Not measured | Only Qwen3 235B A22B Instruct 2507 measured |
| LMArena Text: science | Not measured | 1464 | Only Qwen3.7 Plus measured |
| LMArena Text: medicine and healthcare | Not measured | 1464 | Only Qwen3.7 Plus measured |
| LMArena Text: legal and government | Not measured | 1451 | Only Qwen3.7 Plus measured |
| LMArena Text: business and finance | Not measured | 1435 | Only Qwen3.7 Plus measured |
| Neither model has a result on the other 14 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index06
| Benchmark | Qwen3 235B A22B Instruct 2507 | Qwen3.7 Plus | Leader |
|---|---|---|---|
| Design Arena: websites | 1058 | 1269 | Qwen3.7 Plus |
| Design Arena: UI components | 963 | 1258 | Qwen3.7 Plus |
| Design Arena: game dev | 951 | 1262 | Qwen3.7 Plus |
| Design Arena: data viz | 1070 | 1277 | Qwen3.7 Plus |
| Design Arena: 3D | 994 | 1238 | Qwen3.7 Plus |
| Design Arena: all code categories | 1038 | 1268 | Qwen3.7 Plus |
| Design Arena: SVG | Not measured | 1207 | Only Qwen3.7 Plus measured |
| Design Arena: ASCII art | Not measured | 1143 | Only Qwen3.7 Plus measured |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index04
| Benchmark | Qwen3 235B A22B Instruct 2507 | Qwen3.7 Plus | Leader |
|---|---|---|---|
| SAGE (Vals AI) | Not measured | 39.3% | Only Qwen3.7 Plus measured |
| Vals Multimodal Index | Not measured | 53.9% | Only Qwen3.7 Plus measured |
| IFBench | 51.2% | 78.0% | Qwen3.7 Plus |
| Long context reasoning (AA-LCR) | 72.0% | 73.0% | Qwen3.7 Plus |
| DTBench | 78.4% | 84.0% | Qwen3.7 Plus |
| LMCA | 23.5% | 37.6% | Qwen3.7 Plus |
| LMArena Text | Not measured | 1454 | Only Qwen3.7 Plus measured |
| LMArena Text: instruction following | Not measured | 1439 | Only Qwen3.7 Plus measured |
| LMArena Text: creative writing | Not measured | 1438 | Only Qwen3.7 Plus measured |
| LMArena Vision | Not measured | 1278 | Only Qwen3.7 Plus measured |
| LMArena Text: English | Not measured | 1458 | Only Qwen3.7 Plus measured |
| LMArena Text: non-English | Not measured | 1445 | Only Qwen3.7 Plus measured |
| LMArena Text: Chinese | Not measured | 1509 | Only Qwen3.7 Plus measured |
| LMArena Text: German | Not measured | 1471 | Only Qwen3.7 Plus measured |
| LMArena Text: Japanese | Not measured | 1412 | Only Qwen3.7 Plus measured |
| LMArena Text: Korean | Not measured | 1413 | Only Qwen3.7 Plus measured |
| LMArena Text: French | Not measured | 1472 | Only Qwen3.7 Plus measured |
| LMArena Text: Spanish | Not measured | 1457 | Only Qwen3.7 Plus measured |
| LMArena Text: Russian | Not measured | 1457 | Only Qwen3.7 Plus measured |
| LMArena Text: Polish | Not measured | 1449 | Only Qwen3.7 Plus measured |
| LMArena Text: multi-turn | Not measured | 1459 | Only Qwen3.7 Plus measured |
| LMArena Text: longer queries | Not measured | 1454 | Only Qwen3.7 Plus measured |
| LMArena Text: writing and language | Not measured | 1437 | Only Qwen3.7 Plus measured |
| LMArena Text: entertainment and media | Not measured | 1422 | Only Qwen3.7 Plus measured |
| LMArena Vision: English | Not measured | 1280 | Only Qwen3.7 Plus measured |
| LMArena Vision: Chinese | Not measured | 1332 | Only Qwen3.7 Plus measured |
| LMArena Vision: reading text | Not measured | 1288 | Only Qwen3.7 Plus measured |
| LMArena Vision: humor | Not measured | 1261 | Only Qwen3.7 Plus measured |
| LMArena Vision: creative writing | Not measured | 1258 | Only Qwen3.7 Plus measured |
| LMArena Document | Not measured | 1444 | Only Qwen3.7 Plus measured |
| Neither model has a result on the other 18 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Qwen3 235B A22B Instruct 2507 | Qwen3.7 Plus | 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 235B A22B Instruct 2507 costs less
Repository review
50K input + 3K output tokens
Qwen3 235B A22B Instruct 2507 costs less
Agent loop
200K input + 10K output tokens
Qwen3 235B A22B Instruct 2507 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 235B A22B Instruct 2507 | Qwen3.7 Plus |
|---|---|---|
| Maker | Qwen | Qwen |
| Weights | Open weights | No public weights listed |
| Released | July 21, 2025 | June 3, 2026 |
| Context window | 262K | 1M |
| Input $/Mtok | $0.145 | $0.32 |
| Output $/Mtok | $0.775 | $1.28 |
| Coding index | Not benchmarked | 33.2 |
| Independent measurements behind it | 0 | 2 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Qwen3 235B A22B Instruct 2507 better than Qwen3.7 Plus for coding?
Only Qwen3.7 Plus has a coding score, 33.2 on the Vibe Coding Index; Qwen3 235B A22B Instruct 2507 has none, so the two cannot be ranked on coding. Pick Qwen3 235B A22B Instruct 2507 for output tokens 1.7x cheaper ($0.775 vs $1.28 per million).
Which is cheaper, Qwen3 235B A22B Instruct 2507 or Qwen3.7 Plus?
Qwen3 235B A22B Instruct 2507 costs $0.145 per million input tokens and $0.775 per million output tokens; Qwen3.7 Plus costs $0.32 and $1.28. Cost per solved task is known for neither of them.
Which has the bigger context window, Qwen3 235B A22B Instruct 2507 or Qwen3.7 Plus?
Qwen3.7 Plus, with 1M tokens against 262K.
How many benchmarks is the Qwen3 235B A22B Instruct 2507 vs Qwen3.7 Plus comparison based on?
16 benchmarks have a result for both models as of October 22, 2026. Qwen3 235B A22B Instruct 2507's coding index rests on 0 independent benchmarks and Qwen3.7 Plus's on 2. Where only one model has a result, the page says so instead of naming a winner.