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Qwen: Qwen3 Next 80B A3B Instruct

by Qwen

Qwen3-Next-80B-A3B-Instruct is an instruction-tuned chat model in the Qwen3-Next series optimized for fast, stable responses without “thinking” traces. It targets complex tasks across reasoning, code generation, knowledge QA, and multilingual use, while remaining robust on alignment and formatting. Compared with prior Qwen3 instruct variants, it focuses on higher throughput and stability on ultra-long inputs and multi-turn dialogues, making it well-suited for RAG, tool use, and agentic workflows that require consistent final answers rather than visible chain-of-thought. The model employs scaling-efficient training and decoding to improve parameter efficiency and inference speed, and has been validated on a broad set of public benchmarks where it reaches or approaches larger Qwen3 systems in several categories while outperforming earlier mid-sized baselines. It is best used as a general assistant, code helper, and long-context task solver in production settings where deterministic, instruction-following outputs are preferred.

Avg Score

71.4%

14 answers

Avg Latency

27.9s

10 runs

Pricing

$0.09

input

/

$1.10

output

per 1M tokens

Context

262K

tokens

Alternatives

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Other Models from Qwen

Compare performance with other models from the same creator

ModelScoreLatencyCost/1M
Qwen: Qwen3 Coder 480B A35B100.0%1.1sFree
Qwen: Qwen3 VL 235B A22B Instruct88.6%48.0s$0.70
Qwen: Qwen3 Max87.9%31.7s$3.60
Qwen: Qwen-Plus85.8%22.0s$0.80
Qwen: Qwen3 235B A22B Thinking 250784.6%248.4s$0.35
Qwen: Qwen3 Coder Plus84.2%20.5s$3.00
Qwen: Qwen3 Coder 480B A35B83.5%19.2s$0.58
Qwen: Qwen3 Coder 480B A35B81.3%6.2s$1.01
Qwen: Qwen3 Next 80B A3B Thinking80.8%28.8s$0.68
Qwen: Qwen3 VL 235B A22B Thinking80.4%112.0s$1.98
Qwen: Qwen3 VL 32B Instruct78.8%26.3s$1.00
Qwen: Qwen Plus 072878.5%19.6s$0.80
Qwen: Qwen3 235B A22B74.6%78.3s$0.40
Qwen: Qwen3 30B A3B Instruct 250773.1%30.8s$0.20
Qwen: Qwen3 VL 8B Thinking70.8%79.4s$1.14
Qwen: Qwen-Turbo70.7%18.6s$0.13
Qwen: Qwen Plus 072870.0%49.2s$2.20
Qwen: Qwen3 235B A22B Instruct 250769.6%25.6s$0.27
Qwen: Qwen3 Coder Flash69.2%14.1s$0.90
Qwen: Qwen3 30B A3B Thinking 250765.8%45.6s$0.20
Qwen: Qwen-Max 65.8%12.7s$4.00
Qwen: Qwen2.5 VL 72B Instruct65.0%22.1s$0.38
Qwen: Qwen3 Coder 30B A3B Instruct63.6%30.8s$0.17
Qwen: Qwen3 VL 30B A3B Thinking63.1%83.6s$0.60
Qwen2.5 72B Instruct62.9%22.2s$0.26
Qwen: Qwen3 8B62.5%111.5s$0.15
Qwen: Qwen3 14B61.5%70.4s$0.14
Qwen: Qwen VL Max61.3%36.4s$2.00
Qwen: Qwen3 32B59.6%121.7s$0.16
Qwen: QwQ 32B59.2%143.6s$0.28
Qwen: Qwen VL Plus57.9%10.4s$0.42
Qwen: Qwen3 30B A3B57.7%149.8s$0.14
Qwen: Qwen3 VL 30B A3B Instruct57.5%38.3s$0.38
Qwen: Qwen3 VL 8B Instruct54.6%133.7s$0.29
Qwen2.5 Coder 32B Instruct52.7%19.7s$0.07
Qwen: Qwen2.5 VL 32B Instruct47.3%39.1s$0.14
Qwen: Qwen2.5-VL 7B Instruct31.3%20.7sFree
Qwen: Qwen2.5 7B Instruct30.8%12.6s$0.07
Qwen: Qwen2.5-VL 7B Instruct21.7%10.9s$0.20
Qwen: Qwen2.5 Coder 7B Instruct6.7%6.4s$0.06
Qwen: Qwen3 4B (free)Free

Benchmark Performance

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Quickstart

Get started with this model using OpenRouter

View on OpenRouter
import { OpenRouter } from "@openrouter/sdk";

const openrouter = new OpenRouter({
  apiKey: "<OPENROUTER_API_KEY>"
});

const completion = await openrouter.chat.completions.create({
  model: "qwen/qwen3-next-80b-a3b-instruct",
  messages: [
    {
      role: "user",
      content: "Hello!"
    }
  ]
});

console.log(completion.choices[0].message.content);

Get your API key at openrouter.ai/keys