--- title: Qwen3 Next 80B A3B Instruct FP8 — Efficient LLM | Model... description: Deploy Qwen3 Next 80B A3B Instruct FP8 for 262K context and 3B active params. Generate complex responses via API now. url: https://modelslab.com/qwen3-next-80b-a3b-instruct-fp8 canonical: https://modelslab.com/qwen3-next-80b-a3b-instruct-fp8 type: website component: Seo/ModelPage generated_at: 2026-04-15T02:06:21.388985Z --- Available now on ModelsLab · Language Model Qwen3 Next 80B A3b Instruct Fp8 80B Power 3B Speed --- [Try Qwen3 Next 80B A3b Instruct Fp8](/models/together_ai/Qwen-Qwen3-Next-80B-A3B-Instruct-FP8) [API Documentation](https://docs.modelslab.com) Activate Sparse Efficiency --- Hybrid Attention ### Gated DeltaNet Boost Combines Gated DeltaNet and Attention for 262K context handling in Qwen3 Next 80B A3B Instruct FP8. MoE Sparsity ### 3B Active Params Activates 3B of 80B params per token in Qwen3 Next 80B A3B Instruct FP8 model for 10x throughput. FP8 Precision ### Memory Optimized FP8 quantization cuts memory 50% versus FP16 in Qwen3 Next 80B A3B Instruct FP8 API. Examples See what Qwen3 Next 80B A3b Instruct Fp8 can create --- Copy any prompt below and try it yourself in the [playground](/models/together_ai/Qwen-Qwen3-Next-80B-A3B-Instruct-FP8). Code Review “Review this Python function for efficiency and suggest optimizations: def fibonacci(n): if n <= 1: return n else: return fibonacci(n-1) + fibonacci(n-2)” Tech Summary “Summarize key advancements in hybrid attention mechanisms for LLMs like Qwen3 Next 80B A3B Instruct FP8.” Data Analysis “Analyze this dataset on renewable energy trends from 2020-2025 and predict 2030 growth based on patterns.” Doc Translation “Translate this technical spec sheet on GPU architectures from English to Spanish, preserving all terms.” For Developers A few lines of code. Inference. Three lines. --- ModelsLab handles the infrastructure: fast inference, auto-scaling, and a developer-friendly API. No GPU management needed. - **Serverless:** scales to zero, scales to millions - **Pay per token,** no minimums - **Python and JavaScript SDKs,** plus REST API [API Documentation ](https://docs.modelslab.com) PythonJavaScriptcURL Copy ```

import requests

response = requests.post(
    "https://modelslab.com/api/v7/llm/chat/completions",
    json={
  "key": "YOUR_API_KEY",
  "prompt": "",
  "model_id": ""
}
)
print(response.json())

``` FAQ Common questions about Qwen3 Next 80B A3b Instruct Fp8 --- [Read the docs ](https://docs.modelslab.com) ### What is Qwen3 Next 80B A3B Instruct FP8? ### How does Qwen3 Next 80B A3B Instruct FP8 API perform? ### What makes Qwen3 Next 80B A3B Instruct FP8 model efficient? ### Is Qwen3 Next 80B A3B Instruct FP8 a good alternative? ### What context length supports qwen3 next 80b a3b instruct fp8? ### How to use qwen3 next 80b a3b instruct fp8 API? Ready to create? --- Start generating with Qwen3 Next 80B A3b Instruct Fp8 on ModelsLab. [Try Qwen3 Next 80B A3b Instruct Fp8](/models/together_ai/Qwen-Qwen3-Next-80B-A3B-Instruct-FP8) [API Documentation](https://docs.modelslab.com) --- *This markdown version is optimized for AI agents and LLMs.* **Links:** - [Website](https://modelslab.com) - [API Documentation](https://docs.modelslab.com) - [Blog](https://modelslab.com/blog) --- *Generated by ModelsLab - 2026-04-15*