Alibaba Cloud / Qwen Team model product
Qwen3-Next-80B-A3B-Instruct is the first in the Qwen3-Next series, featuring groundbreaking architectural innovations. It uses Hybrid Attention combining Gated DeltaNet and Gated Attention for efficient ultra-long context modeling, High-Sparsity MoE with 512 experts (10 activated + 1 shared) achieving extreme low activation ratio, and Multi-Token Prediction for improved performance and faster inference. With 80B total parameters and only 3B activated, it outperforms Qwen3-32B-Base with 10% training cost and 10x throughput for 32K+ contexts. The model performs on par with Qwen3-235B-A22B-Instruct-2507 while excelling at ultra-long-context tasks up to 256K tokens (extensible to 1M with YaRN). Architecture: 48 layers, 15T training tokens, hybrid layout of 12*(3*(Gated DeltaNet->MoE)->(Gated Attention->MoE)).
Updated Aug 10, 2026. Default version: Qwen3-Next-80B-A3B-Instruct
Structured fields from the published default version.
This profile uses the latest version under this unique model that has a calculated LLMBoard score. Arena and price are excluded.
Published benchmark records for the scored version Qwen3-Next-80B-A3B-Instruct.
| Arena-Hard v2 | 0.8 | 2 | 16 | 93.3% | C | |
| MultiPL-E | 0.9 | 2 | 13 | 91.7% | C | |
| WritingBench | 0.9 | 2 | 15 | 92.9% | C | |
| LiveBench 20241125 | 0.8 | 4 | 14 | 76.9% | C | |
| Creative Writing v3 | 0.9 | 8 | 13 | 41.7% | C | |
| Multi-IF | 0.8 | 8 | 20 | 63.2% | C | |
| BFCL-v3 | 0.7 | 10 | 19 | 50.0% | C | |
| Include | 0.8 | 13 | 31 | 60.0% | C | |
| Aider-Polyglot | 0.5 | 16 | 22 | 28.6% | C | |
| MMLU-ProX | 0.8 | 16 | 32 | 51.6% | C | |
| PolyMATH | 0.5 | 16 | 23 | 31.8% | C | |
| TAU-bench Airline | 0.4 | 18 | 23 | 22.7% | C | |
| SuperGPQA | 0.6 | 19 | 34 | 45.5% | C | |
| TAU-bench Retail | 0.6 | 19 | 25 | 25.0% | C | |
| HMMT25 | 0.5 | 21 | 25 | 16.7% | C | |
| Tau2 Airline | 0.5 | 22 | 23 | 4.5% | C | |
| MMLU-Redux | 0.9 | 23 | 48 | 53.2% | C | |
| Tau2 Retail | 0.6 | 25 | 26 | 4.0% | C | |
| IFEval | 0.9 | 31 | 65 | 53.1% | C | |
| Tau2 Telecom | 0.1 | 35 | 35 | 0.0% | C | |
| LiveCodeBench v6 | 0.6 | 39 | 53 | 26.9% | C | |
| MMLU-Pro | 0.8 | 52 | 129 | 60.2% | C | |
| AIME 2025 | 0.7 | 90 | 114 | 21.2% | C | |
| GPQA | 0.7 | 120 | 233 | 48.7% | C |
Preference and agent-evaluation signals from published Arena datasets.
| text | industry medicine and healthcare | 44 | 1456.1 | 1,171 | N/A | |
| text | spanish | 49 | 1449.2 | 612 | N/A | |
| text | japanese | 56 | 1404.7 | 268 | N/A | |
| text | math | 58 | 1441.4 | 1,209 | N/A | |
| text | chinese | 72 | 1472.1 | 1,182 | N/A | |
| text | industry business and management and financial operations | 80 | 1422.0 | 4,277 | N/A | |
| text | german | 81 | 1420.1 | 459 | N/A | |
| text | industry legal and government | 81 | 1435.2 | 1,425 | N/A | |
| text | industry mathematical | 81 | 1434.0 | 1,040 | N/A | |
| text | industry software and it services | 83 | 1449.2 | 8,112 | N/A | |
| text style control | japanese | 84 | 1379.1 | 268 | N/A | |
| text factuality | industry business and management and financial operations | 86 | 1431.6 | 791 | N/A | |
| text style control | spanish | 87 | 1422.4 | 612 | N/A | |
| text | non english | 91 | 1408.1 | 11,937 | N/A | |
| text | coding | 93 | 1441.1 | 4,790 | N/A | |
| text | hard prompts | 95 | 1428.5 | 11,892 | N/A | |
| text | industry life and physical and social science | 95 | 1434.4 | 3,508 | N/A | |
| text | hard prompts english | 99 | 1433.7 | 6,051 | N/A | |
| text factuality | non english | 100 | 1412.3 | 3,380 | N/A | |
| text | overall | 101 | 1418.8 | 22,846 | N/A | |
| text | exclude ties | 101 | 1406.5 | 16,143 | N/A | |
| text | korean | 101 | 1360.5 | 483 | N/A | |
| text | multi turn | 101 | 1417.7 | 4,084 | N/A | |
| text | polish | 101 | 1401.5 | 990 | N/A | |
| text factuality | multi turn | 104 | 1420.4 | 748 | N/A | |
| text | english | 106 | 1425.0 | 10,870 | N/A | |
| text style control | industry medicine and healthcare | 108 | 1439.6 | 1,171 | N/A | |
| text style control | math | 108 | 1417.3 | 1,209 | N/A | |
| text factuality | exclude ties | 109 | 1410.4 | 5,217 | N/A | |
| text factuality | hard prompts | 110 | 1441.9 | 3,798 | N/A | |
| text factuality | industry software and it services | 111 | 1449.6 | 1,533 | N/A | |
| text factuality | overall | 112 | 1418.6 | 7,632 | N/A | |
| text factuality | coding | 112 | 1451.8 | 907 | N/A | |
| text style control | chinese | 112 | 1452.2 | 1,182 | N/A | |
| text | russian | 113 | 1401.1 | 1,192 | N/A | |
| text | french | 114 | 1416.0 | 347 | N/A | |
| text factuality | creative writing | 116 | 1355.3 | 499 | N/A | |
| text | expert | 118 | 1409.6 | 1,007 | N/A | |
| text factuality | hard prompts english | 118 | 1430.8 | 1,232 | N/A | |
| text factuality | industry entertainment and sports and media | 118 | 1345.6 | 715 | N/A | |
| text factuality | instruction following | 118 | 1392.7 | 1,228 | N/A | |
| text style control | industry business and management and financial operations | 118 | 1412.0 | 4,277 | N/A | |
| text | instruction following | 119 | 1389.4 | 6,309 | N/A | |
| text factuality | industry life and physical and social science | 119 | 1395.0 | 524 | N/A | |
| text style control | german | 119 | 1389.3 | 459 | N/A | |
| text | longer query | 120 | 1402.3 | 5,213 | N/A | |
| text factuality | industry writing and literature and language | 120 | 1369.6 | 955 | N/A | |
| text factuality | longer query | 120 | 1408.2 | 997 | N/A | |
| text style control | industry mathematical | 122 | 1414.6 | 1,040 | N/A | |
| text style control | industry software and it services | 124 | 1443.5 | 8,112 | N/A | |
| text factuality | english | 125 | 1416.1 | 3,304 | N/A | |
| text style control | industry legal and government | 129 | 1413.3 | 1,425 | N/A | |
| text style control | hard prompts | 131 | 1420.9 | 11,892 | N/A | |
| text style control | hard prompts english | 134 | 1428.7 | 6,051 | N/A | |
| text style control | overall | 135 | 1401.1 | 22,846 | N/A | |
| text style control | coding | 135 | 1445.5 | 4,790 | N/A | |
| text style control | exclude ties | 135 | 1384.0 | 16,143 | N/A | |
| text style control | multi turn | 135 | 1403.4 | 4,084 | N/A | |
| text style control | non english | 135 | 1387.0 | 11,937 | N/A | |
| text style control | polish | 136 | 1372.7 | 990 | N/A | |
| text style control | french | 137 | 1403.3 | 347 | N/A | |
| text style control | industry life and physical and social science | 137 | 1416.8 | 3,508 | N/A | |
| text style control | russian | 140 | 1387.2 | 1,192 | N/A | |
| text | industry entertainment and sports and media | 141 | 1351.8 | 4,196 | N/A | |
| text style control | english | 141 | 1410.9 | 10,870 | N/A | |
| text style control | korean | 147 | 1323.7 | 483 | N/A | |
| text | industry writing and literature and language | 149 | 1356.0 | 5,043 | N/A | |
| text style control | instruction following | 155 | 1378.4 | 6,309 | N/A | |
| text style control | longer query | 156 | 1389.7 | 5,213 | N/A | |
| text style control | expert | 159 | 1393.5 | 1,007 | N/A | |
| text | creative writing | 161 | 1335.1 | 3,021 | N/A | |
| text style control | industry entertainment and sports and media | 173 | 1327.9 | 4,196 | N/A | |
| text style control | industry writing and literature and language | 177 | 1343.7 | 5,043 | N/A | |
| text style control | creative writing | 193 | 1315.7 | 3,021 | N/A |
Official vendor API PAYG pricing is summarized first. The table then lists individual provider offerings without treating their minimum as the official price.
| Charm Hyper | qwen3-next-80b-a3b-instruct | global | $0.1175 | $1.14 | 262.1K | |
| Helicone | qwen3-next-80b-a3b-instruct | global | $0.14 | $1.4 | 262K | |
| Alibaba (China) | qwen3-next-80b-a3b-instruct | global | $0.144 | $0.574 | 131.1K | |
| LLM Gateway | qwen3-next-80b-a3b-instruct | global | $0.15 | $1.2 | 131.1K | |
| Neon | qwen3-next-80b-a3b-instruct | global | $0.15 | $1.2 | 131.1K |
Official prices use only the vendor's configured official Provider and positive standard USD PAYG rates. Third-party offers remain explicitly labeled.
All published versions linked to this unique model. The score columns identify the version used by the current overall ranking.
| Qwen3-Next-80B-A3B-Base | N/A | 80B | N/A | N/A | No | Apache 2.0 | |
| Qwen3-Next-80B-A3B-Instruct | 41.8 | 80B | 131.1K | 32.8K | Yes | Apache 2.0 |
A concise description based on the published model registry.
Qwen3-Next-80B-A3B-Instruct is the first in the Qwen3-Next series, featuring groundbreaking architectural innovations. It uses Hybrid Attention combining Gated DeltaNet and Gated Attention for efficient ultra-long context modeling, High-Sparsity MoE with 512 experts (10 activated + 1 shared) achieving extreme low activation ratio, and Multi-Token Prediction for improved performance and faster inference. With 80B total parameters and only 3B activated, it outperforms Qwen3-32B-Base with 10% training cost and 10x throughput for 32K+ contexts. The model performs on par with Qwen3-235B-A22B-Instruct-2507 while excelling at ultra-long-context tasks up to 256K tokens (extensible to 1M with YaRN). Architecture: 48 layers, 15T training tokens, hybrid layout of 12*(3*(Gated DeltaNet->MoE)->(Gated Attention->MoE)).
Use the benchmark, Arena and pricing sections above as separate evidence. A missing field means the current data snapshot does not support that claim.
Data snapshot: 2026-08-07. Editorial model content is not available in the backend.
Open a comparison with the three ranked models immediately above and below this model.
Recommendations prioritize the same model type and family, then the closest published LLMBoard score.
Common questions about Qwen3 Next 80B A3B.
Qwen3 Next 80B A3B's default version was released on Sep 10, 2025.
Qwen3 Next 80B A3B's official API price is $0.144 per million input tokens and $0.574 per million output tokens via Alibaba (China). The lowest tracked third-party offer starts at $0.1175 input and $1.14 output via Charm Hyper.
Qwen3 Next 80B A3B is published under Alibaba Cloud / Qwen Team in the model registry.
The default version has a 131.1K token context window.
Yes. The default version is marked as open weight under Apache 2.0.
6 published provider offerings are linked to the default version.
Nearby ranked alternatives include GPT-5.4-nano, Qwen3 VL 235B A22B, Phi 3.5 MoE.