Qwen3 235B A22B Instruct 2507 vs Qwen3 30B A3B
Qwen3 235B A22B Instruct 2507 leads Qwen3 30B A3B on the Artificial Analysis Intelligence Index, 12.0 to 7.6, and Qwen3 30B A3B costs 1.6x less per output token ($0.50 vs $0.775 per million). Updated October 22, 2026; 19 benchmarks have a result for both.
Qwen3 235B A22B Instruct 2507 or Qwen3 30B A3B: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick Qwen3 235B A22B Instruct 2507 for a larger context window (262K against 41K tokens).
- Shared results
- 19
- Qwen3 235B A22B Instruct 2507 only
- 5
- Qwen3 30B A3B only
- 34
- Like-for-like categories
- 8 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 235B A22B Instruct 2507
Qwen3 235B A22B Instruct 2507 leads, 12.0 against 7.6.
Same board, both measured
Web design
Design Arena: websites
Qwen3 235B A22B Instruct 2507
Qwen3 235B A22B Instruct 2507 leads, 1058 against 954.
Same board, both measured
Long documents
Listed context window
Qwen3 235B A22B Instruct 2507
Qwen3 235B A22B Instruct 2507 takes 262K tokens against 41K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen3 30B A3B
Qwen3 235B A22B Instruct 2507 $0.0005, Qwen3 30B A3B $0.0004 per turn.
List prices
At a glance
- Coding index
- Qwen3 235B A22B Instruct 2507 not benchmarked, Qwen3 30B A3B not benchmarked.
- Widest category
- Agentic work, 27.2 points apart on average over 1 shared benchmark.
- Widest single gap
- Long context reasoning (AA-LCR): Qwen3 235B A22B Instruct 2507 72.0% against Qwen3 30B A3B 0.0%, 72.0 points apart on a 0 to 100 scale.
- Output price
- Qwen3 235B A22B Instruct 2507 $0.775 against Qwen3 30B A3B $0.50 per million output tokens, 1.6x apart.
- Context window
- Qwen3 235B A22B Instruct 2507 takes 262K tokens, Qwen3 30B A3B 41K.
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 30B A3B | Ties |
|---|---|---|---|---|
| Coding | 3 | 0 | ||
| Intelligence | 1 | 0 | ||
| Agentic work | 1 | 0 | ||
| Reasoning | 2 | 0 | ||
| Math | 2 | 0 | ||
| Knowledge | 1 | 0 | ||
| Web design | 5 | 0 | ||
| General | 4 | 0 | ||
| All shared boards | 19 | 0 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index30
| Benchmark | Qwen3 235B A22B Instruct 2507 | Qwen3 30B A3B | Leader |
|---|---|---|---|
| LiveCodeBench (Artificial Analysis run) | 78.8% | 50.6% | Qwen3 235B A22B Instruct 2507 |
| SciCode | 41.4% | Not measured | Only Qwen3 235B A22B Instruct 2507 measured |
| Terminal-Bench Hard (Artificial Analysis run) | 15.2% | 6.8% | Qwen3 235B A22B Instruct 2507 |
| WeirdML | 38.7% | 29.8% | Qwen3 235B A22B Instruct 2507 |
| LMArena Text: coding | Not measured | 1337 | Only Qwen3 30B A3B measured |
| LMArena Text: software and IT | Not measured | 1340 | Only Qwen3 30B A3B measured |
| Neither model has a result on the other 37 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Qwen3 235B A22B Instruct 2507 | Qwen3 30B A3B | Leader |
|---|---|---|---|
| AA Intelligence Index | 12.0 | 7.6 | Qwen3 235B A22B Instruct 2507 |
| Epoch Capabilities Index | Not measured | 137.3 | Only Qwen3 30B A3B measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Qwen3 235B A22B Instruct 2507 | Qwen3 30B A3B | Leader |
|---|---|---|---|
| τ²-Bench Telecom | 53.2% | 26.0% | Qwen3 235B A22B Instruct 2507 |
| Berkeley Function Calling Leaderboard (BFCL) | 52.1% | Not measured | Only Qwen3 235B A22B Instruct 2507 measured |
| 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 235B A22B Instruct 2507 | Qwen3 30B A3B | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 79.0% | 61.6% | Qwen3 235B A22B Instruct 2507 |
| Humanity's Last Exam (Artificial Analysis run) | 15.9% | 6.2% | Qwen3 235B A22B Instruct 2507 |
| GPQA Diamond (Epoch AI run) | Not measured | 61.7% | Only Qwen3 30B A3B 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 |
| LMArena Text: hard prompts | Not measured | 1314 | Only Qwen3 30B A3B measured |
| LMArena Text: expert | Not measured | 1314 | Only Qwen3 30B A3B measured |
| LMArena Text: hard prompts in English | Not measured | 1329 | Only Qwen3 30B A3B measured |
| Neither model has a result on the other 15 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Qwen3 235B A22B Instruct 2507 | Qwen3 30B A3B | Leader |
|---|---|---|---|
| AA Math Index | 91.0 | 72.3 | Qwen3 235B A22B Instruct 2507 |
| AIME 2025 (Artificial Analysis run) | 91.0% | 72.3% | Qwen3 235B A22B Instruct 2507 |
| OTIS Mock AIME | Not measured | 62.8% | Only Qwen3 30B A3B measured |
| LMArena Text: math | Not measured | 1355 | Only Qwen3 30B A3B measured |
| LMArena Text: mathematical work | Not measured | 1363 | Only Qwen3 30B A3B measured |
| MathArena | Not measured | 9.4% | Only Qwen3 30B A3B measured |
| Neither model has a result on the other 8 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Qwen3 235B A22B Instruct 2507 | Qwen3 30B A3B | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | 84.3% | 77.7% | Qwen3 235B A22B Instruct 2507 |
| LMArena Text: science | Not measured | 1321 | Only Qwen3 30B A3B measured |
| LMArena Text: medicine and healthcare | Not measured | 1318 | Only Qwen3 30B A3B measured |
| LMArena Text: legal and government | Not measured | 1314 | Only Qwen3 30B A3B measured |
| LMArena Text: business and finance | Not measured | 1309 | Only Qwen3 30B A3B measured |
| Neither model has a result on the other 15 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index50
| Benchmark | Qwen3 235B A22B Instruct 2507 | Qwen3 30B A3B | Leader |
|---|---|---|---|
| Design Arena: websites | 1058 | 954 | Qwen3 235B A22B Instruct 2507 |
| Design Arena: UI components | 963 | 943 | Qwen3 235B A22B Instruct 2507 |
| Design Arena: game dev | 951 | 898 | Qwen3 235B A22B Instruct 2507 |
| Design Arena: data viz | 1070 | 967 | Qwen3 235B A22B Instruct 2507 |
| Design Arena: 3D | 994 | Not measured | Only Qwen3 235B A22B Instruct 2507 measured |
| Design Arena: all code categories | 1038 | 941 | Qwen3 235B A22B Instruct 2507 |
| Neither model has a result on the other 3 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index40
| Benchmark | Qwen3 235B A22B Instruct 2507 | Qwen3 30B A3B | Leader |
|---|---|---|---|
| IFBench | 51.2% | 41.5% | Qwen3 235B A22B Instruct 2507 |
| Long context reasoning (AA-LCR) | 72.0% | 0.0% | Qwen3 235B A22B Instruct 2507 |
| DTBench | 78.4% | 60.3% | Qwen3 235B A22B Instruct 2507 |
| LMCA | 23.5% | 15.8% | Qwen3 235B A22B Instruct 2507 |
| Fiction.LiveBench | Not measured | 40.6% | Only Qwen3 30B A3B measured |
| Creative writing (Lech Mazur) | Not measured | 75.3% | Only Qwen3 30B A3B measured |
| LMArena Text | Not measured | 1317 | Only Qwen3 30B A3B measured |
| LMArena Text: instruction following | Not measured | 1283 | Only Qwen3 30B A3B measured |
| LMArena Text: creative writing | Not measured | 1271 | Only Qwen3 30B A3B measured |
| LMArena Text: English | Not measured | 1335 | Only Qwen3 30B A3B measured |
| LMArena Text: non-English | Not measured | 1295 | Only Qwen3 30B A3B measured |
| LMArena Text: Chinese | Not measured | 1347 | Only Qwen3 30B A3B measured |
| LMArena Text: German | Not measured | 1307 | Only Qwen3 30B A3B measured |
| LMArena Text: Japanese | Not measured | 1254 | Only Qwen3 30B A3B measured |
| LMArena Text: Korean | Not measured | 1261 | Only Qwen3 30B A3B measured |
| LMArena Text: French | Not measured | 1352 | Only Qwen3 30B A3B measured |
| LMArena Text: Spanish | Not measured | 1317 | Only Qwen3 30B A3B measured |
| LMArena Text: Russian | Not measured | 1291 | Only Qwen3 30B A3B measured |
| LMArena Text: Polish | Not measured | 1299 | Only Qwen3 30B A3B measured |
| LMArena Text: multi-turn | Not measured | 1307 | Only Qwen3 30B A3B measured |
| LMArena Text: longer queries | Not measured | 1312 | Only Qwen3 30B A3B measured |
| LMArena Text: writing and language | Not measured | 1290 | Only Qwen3 30B A3B measured |
| LMArena Text: entertainment and media | Not measured | 1258 | Only Qwen3 30B A3B measured |
| Neither model has a result on the other 25 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Qwen3 235B A22B Instruct 2507 | Qwen3 30B A3B | 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 30B A3B costs less
Repository review
50K input + 3K output tokens
Qwen3 30B A3B costs less
Agent loop
200K input + 10K output tokens
Qwen3 30B A3B 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 30B A3B |
|---|---|---|
| Maker | Qwen | Qwen |
| Weights | Open weights | Open weights |
| Released | July 21, 2025 | April 28, 2025 |
| Context window | 262K | 41K |
| Input $/Mtok | $0.145 | $0.12 |
| Output $/Mtok | $0.775 | $0.50 |
| 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 235B A22B Instruct 2507 better than Qwen3 30B A3B for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Qwen3 235B A22B Instruct 2507 for a larger context window (262K against 41K tokens).
Which is cheaper, Qwen3 235B A22B Instruct 2507 or Qwen3 30B A3B?
Qwen3 235B A22B Instruct 2507 costs $0.145 per million input tokens and $0.775 per million output tokens; Qwen3 30B A3B costs $0.12 and $0.50. Cost per solved task is known for neither of them.
Which has the bigger context window, Qwen3 235B A22B Instruct 2507 or Qwen3 30B A3B?
Qwen3 235B A22B Instruct 2507, with 262K tokens against 41K.
How many benchmarks is the Qwen3 235B A22B Instruct 2507 vs Qwen3 30B A3B comparison based on?
19 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 30B A3B's on 0. Where only one model has a result, the page says so instead of naming a winner.