Alibaba (Qwen), open weights
Qwen3-Next 80B-A3B Instruct
Qwen3-Next 80B-A3B Instruct by Alibaba (Qwen) ranks 102nd of 354 ranked models on the Noometry Index as of October 2026, with a score of 43.0. Its strongest category is reasoning, where it ranks 81st. API pricing starts at $0.50 per million input tokens and $2 per million output tokens, with a 131K-token context window.
Last verified
Specifications
- Noometry rank
- #102 of 354
- Index score
- 43.0
- Evidence
- Confirmed 25 results
- Provider
Alibaba (Qwen)- Released
- September 1, 2025
- Weights
- Open weights
- Reasoning
- No
- Context window
- 131K
- Max output
- 33K
- Input price
- $0.50 / M
- Output price
- $2 / M
- Blended price
- $0.88 / M
- Output speed
- 111 tokens/s Kagi
- Value
- #95 of 219
- Knowledge cutoff
- April 2025
- Input
- text
- Hugging Face
- Qwen/Qwen3-Next-80B-A3B-Instruct
Category scores
Each category score combines every public result we have in that category.
- Coding 42.5
- Reasoning 31.1
- Math 38.8
- Knowledge 41.8
- Multilingual 52.1
- Instruction Following 70.8
- Long Context 37.0
- Writing & Preference 58.0
| Category | Score | Rank | Results |
|---|---|---|---|
| Coding | 42.5 | #98 | 1 |
| Reasoning | 31.1 | #81 | 2 |
| Math | 38.8 | #126 | 2 |
| Knowledge | 41.8 | #106 | 4 |
| Multilingual | 52.1 | #93 | 1 |
| Instruction Following | 70.8 | #159 | 2 |
| Long Context | 37.0 | #223 | 2 |
| Writing & Preference | 58.0 | #121 | 4 |
Strengths and weaknesses
Categories where Qwen3-Next 80B-A3B Instruct 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 |
|---|---|---|---|
| Reasoning | 31.1 | +7.5 | #81 of 350, top 24% |
| Coding | 42.5 | +3.8 | #98 of 340, top 29% |
| Multilingual | 52.1 | +4.7 | #93 of 297, top 32% |
Weakest categories
| Category | Score | vs median | Rank |
|---|---|---|---|
| Long Context | 37.0 | −3.9 | #223 of 296, top 76% |
| Instruction Following | 70.8 | −0.5 | #159 of 305, top 53% |
| Writing & Preference | 58.0 | +4.3 | #121 of 312, top 39% |
Closest competitors
The models ranked just above and below Qwen3-Next 80B-A3B Instruct. When scores are this close, price and speed are often the better way to choose.
| Model | Rank | Score | Blended $/M | Speed | |
|---|---|---|---|---|---|
| Hunyuan Vision 1.5 | #98 | 43.1 | — | — | Compare |
| Mistral Large 4 | #99 | 43.1 | $1.03 | — | Compare |
| Claude Opus 4 | #100 | 43.1 | $30 | 29 | Compare |
| Amazon Nova Experimental Chat 11 10 | #101 | 43.0 | — | — | Compare |
| MiMo-V2-Pro | #103 | 43.0 | $0.54 | — | Compare |
| Amazon Nova Experimental Chat 12 10 | #104 | 42.9 | — | — | Compare |
| o3-pro | #105 | 42.9 | $35 | 1 | Compare |
| Qwen3.5 Plus | #106 | 42.9 | $0.90 | — | 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 |
|---|---|---|---|---|---|
| LMArena Coding | 1440 | #97 of 294, top 33% | LMArena | 2026-10-08 | |
| LMArena Coding | 1391 | thinking | LMArena | 2026-10-08 |
Reasoning
| Benchmark | Score | Position | Setting | Source | Date |
|---|---|---|---|---|---|
| Kagi LLM Benchmark | 66.7% | #31 of 99, top 32% | Kagi LLM Benchmark | ||
| Kagi LLM Benchmark | 54.4% | Kagi LLM Benchmark | |||
| LMArena Hard Prompts | 1428 | #93 of 297, top 32% | LMArena | 2026-10-08 | |
| LMArena Hard Prompts | 1371 | thinking | LMArena | 2026-10-08 |
Math
| Benchmark | Score | Position | Setting | Source | Date |
|---|---|---|---|---|---|
| Omni-MATH | 46.7% | #19 of 57, top 34% | HELM Capabilities | ||
| LMArena Math | 1440 | #71 of 285, top 25% | LMArena | 2026-10-08 | |
| LMArena Math | 1398 | thinking | LMArena | 2026-10-08 |
Knowledge
| Benchmark | Score | Position | Setting | Source | Date |
|---|---|---|---|---|---|
| MMLU-Pro | 78.6% | #20 of 58, top 35% | HELM Capabilities | ||
| Vectara Hallucination Rate (lower is better) | 9.3% | #48 of 96, top 50% | Vectara Hallucination Leaderboard | ||
| GPQA (HELM) | 63% | #20 of 57, top 36% | HELM Capabilities | ||
| LMArena Expert | 1417 | #110 of 273, top 41% | LMArena | 2026-10-08 | |
| LMArena Expert | 1376 | thinking | LMArena | 2026-10-08 |
Multilingual
| Benchmark | Score | Position | Setting | Source | Date |
|---|---|---|---|---|---|
| LMArena Non-English | 1407 | #93 of 297, top 32% | LMArena | 2026-10-08 | |
| LMArena Non-English | 1342 | thinking | LMArena | 2026-10-08 | |
| LMArena Chinese | 1460 | #92 of 285, top 33% | LMArena | 2026-10-08 | |
| LMArena Chinese | 1406 | thinking | LMArena | 2026-10-08 | |
| LMArena French | 1413 | #107 of 223, top 48% | LMArena | 2026-10-08 | |
| LMArena French | 1351 | thinking | LMArena | 2026-10-08 | |
| LMArena German | 1417 | #81 of 231, top 36% | LMArena | 2026-10-08 | |
| LMArena German | 1356 | thinking | LMArena | 2026-10-08 | |
| LMArena Japanese | 1395 | #63 of 211, top 30% | LMArena | 2026-10-08 | |
| LMArena Japanese | 1280 | thinking | LMArena | 2026-10-08 | |
| LMArena Korean | 1364 | #89 of 213, top 42% | LMArena | 2026-10-08 | |
| LMArena Korean | 1310 | thinking | LMArena | 2026-10-08 | |
| LMArena Russian | 1404 | #102 of 283, top 37% | LMArena | 2026-10-08 | |
| LMArena Russian | 1338 | thinking | LMArena | 2026-10-08 | |
| LMArena Spanish | 1435 | #73 of 226, top 33% | LMArena | 2026-10-08 | |
| LMArena Spanish | 1358 | thinking | LMArena | 2026-10-08 |
Instruction Following
| Benchmark | Score | Position | Setting | Source | Date |
|---|---|---|---|---|---|
| IFEval | 81% | #40 of 57, top 71% | HELM Capabilities | ||
| LMArena Instruction Following | 1389 | #113 of 298, top 38% | LMArena | 2026-10-08 | |
| LMArena Instruction Following | 1344 | thinking | LMArena | 2026-10-08 |
Long Context
| Benchmark | Score | Position | Setting | Source | Date |
|---|---|---|---|---|---|
| Fiction.LiveBench | 41.7% | Epoch AI | |||
| Fiction.LiveBench | 55.6% | #32 of 47, top 69% | Epoch AI | ||
| LMArena Longer Query | 1403 | #114 of 291, top 40% | LMArena | 2026-10-08 | |
| LMArena Longer Query | 1353 | thinking | LMArena | 2026-10-08 |
Writing & Preference
| Benchmark | Score | Position | Setting | Source | Date |
|---|---|---|---|---|---|
| LMArena Text | 1417 | #101 of 297, top 35% | LMArena | 2026-10-08 | |
| LMArena Text | 1368 | thinking | LMArena | 2026-10-08 | |
| LMArena Creative Writing | 1334 | #141 of 295, top 48% | LMArena | 2026-10-08 | |
| LMArena Creative Writing | 1315 | thinking | LMArena | 2026-10-08 | |
| WildBench | 80.7% | #26 of 57, top 46% | HELM Capabilities | ||
| LMArena Multi-Turn | 1416 | #101 of 295, top 35% | LMArena | 2026-10-08 | |
| LMArena Multi-Turn | 1346 | thinking | LMArena | 2026-10-08 |
API pricing by provider
| Route | Input $/M | Output $/M | Cached input $/M | Checked |
|---|---|---|---|---|
| alibaba | $0.50 | $2 | — | 2026-10-10 |
| bedrock | $0.15 | $1.20 | — | 2026-10-10 |
| deepinfra | $0.09 | $1.10 | — | 2026-10-10 |
| openrouter | $0.10 | $1.10 | $0.07 | 2026-10-10 |
Compare Qwen3-Next 80B-A3B Instruct
- Qwen3-Next 80B-A3B Instruct vs Amazon Nova Experimental Chat 11 10
- Qwen3-Next 80B-A3B Instruct vs MiMo-V2-Pro
- Qwen3-Next 80B-A3B Instruct vs Claude Opus 4
- Qwen3-Next 80B-A3B Instruct vs Amazon Nova Experimental Chat 12 10
- Qwen3-Next 80B-A3B Instruct vs Mistral Large 4
- Qwen3-Next 80B-A3B Instruct vs o3-pro
- Qwen3-Next 80B-A3B Instruct vs GPT-6 Astra
- Qwen3-Next 80B-A3B Instruct vs Claude Fable 5.1
- Qwen3-Next 80B-A3B Instruct vs Gemini 3.8 Flash
- Qwen3-Next 80B-A3B Instruct vs Kimi K3
- Qwen3-Next 80B-A3B Instruct vs Grok 4.6
- Qwen3-Next 80B-A3B Instruct vs GLM-5.3
- Qwen3-Next 80B-A3B Instruct vs Muse Spark 1.3
- Qwen3-Next 80B-A3B Instruct vs DeepSeek V4 Pro
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-Next 80B-A3B Instruct?
Qwen3-Next 80B-A3B Instruct by Alibaba (Qwen) ranks 102nd of 354 ranked models on the Noometry Index as of October 2026, with a score of 43.0. Its strongest category is reasoning, where it ranks 81st. API pricing starts at $0.50 per million input tokens and $2 per million output tokens, with a 131K-token context window.
How much does Qwen3-Next 80B-A3B Instruct cost?
Qwen3-Next 80B-A3B Instruct costs $0.50 per million input tokens and $2 per million output tokens on Alibaba (Qwen)'s own API.
What is Qwen3-Next 80B-A3B Instruct's context window?
Qwen3-Next 80B-A3B Instruct accepts up to 131K tokens of input and can write up to 33K tokens in one response.
Is Qwen3-Next 80B-A3B Instruct open source?
Yes. Qwen3-Next 80B-A3B Instruct's weights are downloadable from Hugging Face (Qwen/Qwen3-Next-80B-A3B-Instruct); check the license for commercial terms.
How fast is Qwen3-Next 80B-A3B Instruct?
Qwen3-Next 80B-A3B Instruct generated about 111 output tokens per second in the Kagi LLM Benchmark's timed runs. Speed varies by provider, load and reasoning effort.
What are Qwen3-Next 80B-A3B Instruct's strengths and weaknesses?
Relative to other ranked models, Qwen3-Next 80B-A3B Instruct places best in reasoning, coding, multilingual and lowest in long context, instruction following, writing & preference.
What is Qwen3-Next 80B-A3B Instruct best at?
Its best category is reasoning, where it ranks 81st on Noometry.