Alibaba (Qwen), open weights
Qwen3-30B-A3B
Qwen3-30B-A3B by Alibaba (Qwen) ranks 179th of 354 ranked models on the Noometry Index as of October 2026, with a score of 38.9. Its strongest category is agentic & tool use, where it ranks 82nd. API pricing starts at $0.12 per million input tokens and $0.50 per million output tokens, with a 41K-token context window.
Last verified
Specifications
- Noometry rank
- #179 of 354
- Index score
- 38.9
- Evidence
- Confirmed 32 results
- Provider
Alibaba (Qwen)
- Released
- April 28, 2025
- Weights
- Open weights
- Reasoning
- Yes
- Context window
- 41K
- Max output
- 16K
- Input price
- $0.12 / M
- Output price
- $0.50 / M
- Blended price
- $0.21 / M
- Output speed
- 42 tokens/s Kagi
- Value
- #46 of 219
- Knowledge cutoff
- Unknown
- Input
- text
- Hugging Face
- Qwen/Qwen3-30B-A3B
Category scores
Each category score combines every public result we have in that category.
- Coding 37.5
- Agentic & Tool Use 29.8
- Reasoning 22.2
- Math 37.4
- Knowledge 41.8
- Multilingual 49.5
- Instruction Following 72.0
- Long Context 31.0
- Writing & Preference 55.6
| Category | Score | Rank | Results |
|---|---|---|---|
| Coding | 37.5 | #194 | 3 |
| Agentic & Tool Use | 29.8 | #82 | 1 |
| Reasoning | 22.2 | #204 | 6 |
| Math | 37.4 | #157 | 3 |
| Knowledge | 41.8 | #105 | 3 |
| Multilingual | 49.5 | #132 | 1 |
| Instruction Following | 72.0 | #142 | 1 |
| Long Context | 31.0 | #283 | 2 |
| Writing & Preference | 55.6 | #143 | 4 |
Strengths and weaknesses
Categories where Qwen3-30B-A3B places highest and lowest among the models ranked in each, with its score against that category's median.
Strongest categories
| Category | Score | vs median | Rank |
|---|---|---|---|
| Knowledge | 41.8 | +4.5 | #105 of 314, top 34% |
| Multilingual | 49.5 | +2.1 | #132 of 297, top 45% |
| Writing & Preference | 55.6 | +1.9 | #143 of 312, top 46% |
Weakest categories
| Category | Score | vs median | Rank |
|---|---|---|---|
| Long Context | 31.0 | −9.9 | #283 of 296, top 96% |
| Reasoning | 22.2 | −1.4 | #204 of 350, top 59% |
| Coding | 37.5 | −1.2 | #194 of 340, top 58% |
Closest competitors
The models ranked just above and below Qwen3-30B-A3B. When scores are this close, price and speed are often the better way to choose.
| Model | Rank | Score | Blended $/M | Speed | |
|---|---|---|---|---|---|
| Mercury 2 | #175 | 39.1 | $0.38 | — | Compare |
| Mistral Large 3 | #176 | 39.1 | $0.38 | 7 | Compare |
| GLM-4.5-Air | #177 | 38.9 | $0.43 | 160 | Compare |
| MiniMax-M2.1 | #178 | 38.9 | $0.52 | — | Compare |
| GLM-4.7-Flash | #180 | 38.8 | $0.15 | — | Compare |
| Qwen2.5 Plus 1127 | #181 | 38.8 | — | — | Compare |
| Qwen3.6 Flash | #182 | 38.8 | $0.42 | — | Compare |
| Olmo 3 32b Think | #183 | 38.7 | — | — | Compare |
Sponsored placements are available on pages like this one. Advertise on Noometry
Benchmark results
Every published result we track, with its source. Bold rows are the ones used for ranking; where several exist we prefer independent runs over self-reported numbers.
Coding
| Benchmark | Score | Position | Setting | Source | Date |
|---|---|---|---|---|---|
| SciCode | 33.3% | #102 of 121, top 85% | Epoch AI | ||
| WeirdML | 29.8% | #97 of 119, top 82% | Epoch AI | ||
| LMArena Coding | 1337 | LMArena | 2026-10-08 | ||
| LMArena Coding | 1416 | #120 of 294, top 41% | LMArena | 2026-10-08 |
Agentic & Tool Use
| Benchmark | Score | Position | Setting | Source | Date |
|---|---|---|---|---|---|
| Berkeley Function Calling Leaderboard | 41.4% | #22 of 49, top 45% | fc | Berkeley Function Calling Leaderboard |
Reasoning
| Benchmark | Score | Position | Setting | Source | Date |
|---|---|---|---|---|---|
| Kagi LLM Benchmark | 54.9% | #52 of 99, top 53% | Kagi LLM Benchmark | ||
| CritPt | 0.3% | #97 of 134, top 73% | Epoch AI | ||
| Chess Puzzles | 8% | #85 of 129, top 66% | Epoch AI | 2026-08-30 | |
| Chess Puzzles | 4% | Epoch AI | 2026-08-30 | ||
| Chess Puzzles | 2% | Epoch AI | 2026-08-30 | ||
| Chess Puzzles | 1% | none | Epoch AI | 2026-08-30 | |
| LMArena Hard Prompts | 1314 | LMArena | 2026-10-08 | ||
| LMArena Hard Prompts | 1398 | #130 of 297, top 44% | LMArena | 2026-10-08 | |
| DTBench | 67.2% | Epoch AI | |||
| DTBench | 60.3% | Epoch AI | |||
| DTBench | 69.3% | #93 of 151, top 62% | Epoch AI | ||
| LMCA | 22.4% | #89 of 125, top 72% | Epoch AI | ||
| LMCA | 19.5% | Epoch AI | |||
| LMCA | 15.8% | Epoch AI | |||
| Epoch Capabilities Index | 139.63 | #110 of 213, top 52% | Epoch AI | 2025-07-30 | |
| Epoch Capabilities Index | 137.42 | Epoch AI | 2025-07-29 | ||
| Epoch Capabilities Index | 136.18 | Epoch AI | 2025-04-29 |
Math
| Benchmark | Score | Position | Setting | Source | Date |
|---|---|---|---|---|---|
| MathArena Final-Answer Competitions | 47.8% | #28 of 29, top 97% | MathArena | ||
| OTIS Mock AIME 2024-2025 | 62.8% | Epoch AI | 2026-08-28 | ||
| OTIS Mock AIME 2024-2025 | 70.3% | #92 of 173, top 54% | Epoch AI | 2026-08-30 | |
| OTIS Mock AIME 2024-2025 | 62.2% | Epoch AI | 2026-08-30 | ||
| OTIS Mock AIME 2024-2025 | 25.6% | none | Epoch AI | 2026-08-30 | |
| LMArena Math | 1355 | LMArena | 2026-10-08 | ||
| LMArena Math | 1394 | #133 of 285, top 47% | LMArena | 2026-10-08 |
Knowledge
| Benchmark | Score | Position | Setting | Source | Date |
|---|---|---|---|---|---|
| GPQA Diamond | 55.6% | Epoch AI | 2026-08-30 | ||
| GPQA Diamond | 61.7% | Epoch AI | 2026-08-30 | ||
| GPQA Diamond | 70.1% | #98 of 186, top 53% | Epoch AI | 2026-08-30 | |
| GPQA Diamond | 50.4% | none | Epoch AI | 2026-08-30 | |
| Confabulations (lower is better) | 12.3% | #6 of 51, top 12% | Lech Mazur benchmarks | ||
| LMArena Expert | 1396 | #127 of 273, top 47% | LMArena | 2026-10-08 | |
| LMArena Expert | 1314 | LMArena | 2026-10-08 |
Multilingual
| Benchmark | Score | Position | Setting | Source | Date |
|---|---|---|---|---|---|
| LMArena Non-English | 1372 | #132 of 297, top 45% | LMArena | 2026-10-08 | |
| LMArena Non-English | 1295 | LMArena | 2026-10-08 | ||
| LMArena Chinese | 1347 | LMArena | 2026-10-08 | ||
| LMArena Chinese | 1433 | #116 of 285, top 41% | LMArena | 2026-10-08 | |
| LMArena French | 1352 | LMArena | 2026-10-08 | ||
| LMArena French | 1418 | #102 of 223, top 46% | LMArena | 2026-10-08 | |
| LMArena German | 1380 | #111 of 231, top 49% | LMArena | 2026-10-08 | |
| LMArena German | 1307 | LMArena | 2026-10-08 | ||
| LMArena Japanese | 1254 | LMArena | 2026-10-08 | ||
| LMArena Japanese | 1337 | #107 of 211, top 51% | LMArena | 2026-10-08 | |
| LMArena Korean | 1331 | #113 of 213, top 54% | LMArena | 2026-10-08 | |
| LMArena Korean | 1261 | LMArena | 2026-10-08 | ||
| LMArena Russian | 1291 | LMArena | 2026-10-08 | ||
| LMArena Russian | 1370 | #136 of 283, top 49% | LMArena | 2026-10-08 | |
| LMArena Spanish | 1317 | LMArena | 2026-10-08 | ||
| LMArena Spanish | 1404 | #107 of 226, top 48% | LMArena | 2026-10-08 |
Instruction Following
| Benchmark | Score | Position | Setting | Source | Date |
|---|---|---|---|---|---|
| LMArena Instruction Following | 1363 | #137 of 298, top 46% | LMArena | 2026-10-08 | |
| LMArena Instruction Following | 1283 | LMArena | 2026-10-08 |
Long Context
| Benchmark | Score | Position | Setting | Source | Date |
|---|---|---|---|---|---|
| Fiction.LiveBench | 40.6% | #43 of 47, top 92% | Epoch AI | ||
| LMArena Longer Query | 1379 | #133 of 291, top 46% | LMArena | 2026-10-08 | |
| LMArena Longer Query | 1312 | LMArena | 2026-10-08 |
Writing & Preference
| Benchmark | Score | Position | Setting | Source | Date |
|---|---|---|---|---|---|
| LMArena Text | 1384 | #132 of 297, top 45% | LMArena | 2026-10-08 | |
| LMArena Text | 1317 | LMArena | 2026-10-08 | ||
| LMArena Creative Writing | 1271 | LMArena | 2026-10-08 | ||
| LMArena Creative Writing | 1317 | #156 of 295, top 53% | LMArena | 2026-10-08 | |
| Short-Story Creative Writing | 75.3% | #24 of 39, top 62% | Epoch AI | ||
| LMArena Multi-Turn | 1307 | LMArena | 2026-10-08 | ||
| LMArena Multi-Turn | 1378 | #136 of 295, top 47% | LMArena | 2026-10-08 |
API pricing by provider
| Route | Input $/M | Output $/M | Cached input $/M | Checked |
|---|---|---|---|---|
| deepinfra | $0.12 | $0.50 | — | 2026-10-10 |
| openrouter | $0.12 | $0.50 | — | 2026-10-10 |
Compare Qwen3-30B-A3B
- Qwen3-30B-A3B vs Qwen3 235B-A22B
- Qwen3-30B-A3B vs MiniMax-M2.1
- Qwen3-30B-A3B vs GLM-4.7-Flash
- Qwen3-30B-A3B vs GLM-4.5-Air
- Qwen3-30B-A3B vs Qwen2.5 Plus 1127
- Qwen3-30B-A3B vs Mistral Large 3
- Qwen3-30B-A3B vs Qwen3.6 Flash
- Qwen3-30B-A3B vs GPT-6 Astra
- Qwen3-30B-A3B vs Claude Fable 5.1
- Qwen3-30B-A3B vs Gemini 3.8 Flash
- Qwen3-30B-A3B vs Kimi K3
- Qwen3-30B-A3B vs Grok 4.6
- Qwen3-30B-A3B vs GLM-5.3
- Qwen3-30B-A3B vs Muse Spark 1.3
Other Alibaba (Qwen) models
- Qwen3.8 Max56.8
- Qwen3.7 Max51.5
- Qwen3.6 Max Preview51.5
- Qwen3.6 Plus47.5
- Qwen3.5 397B-A17B46.0
- Qwen3.8 27B46.0
- Qwen3.5 Max Preview45.3
- Qwen3.7 Plus45.3
Frequently asked questions
How good is Qwen3-30B-A3B?
Qwen3-30B-A3B by Alibaba (Qwen) ranks 179th of 354 ranked models on the Noometry Index as of October 2026, with a score of 38.9. Its strongest category is agentic & tool use, where it ranks 82nd. API pricing starts at $0.12 per million input tokens and $0.50 per million output tokens, with a 41K-token context window.
How much does Qwen3-30B-A3B cost?
Qwen3-30B-A3B costs $0.12 per million input tokens and $0.50 per million output tokens on deepinfra.
What is Qwen3-30B-A3B's context window?
Qwen3-30B-A3B accepts up to 41K tokens of input and can write up to 16K tokens in one response.
Is Qwen3-30B-A3B open source?
Yes. Qwen3-30B-A3B's weights are downloadable from Hugging Face (Qwen/Qwen3-30B-A3B); check the license for commercial terms.
How fast is Qwen3-30B-A3B?
Qwen3-30B-A3B generated about 42 output tokens per second in the Kagi LLM Benchmark's timed runs. Speed varies by provider, load and reasoning effort.
What are Qwen3-30B-A3B's strengths and weaknesses?
Relative to other ranked models, Qwen3-30B-A3B places best in knowledge, multilingual, writing & preference and lowest in long context, reasoning, coding.
What is Qwen3-30B-A3B best at?
Its best category is agentic & tool use, where it ranks 82nd on Noometry.