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Nex-N1-TechReport.pdf

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+version https://git-lfs.github.com/spec/v1
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README.md

@@ -6,6 +6,14 @@ license: apache-2.0
 <img src="./figures/NEX_logo.svg" width="20%"/>
 </div>
 
+---
+
+<div align="center">
+🏠 <a href="https://nex.sii.edu.cn"><b>Home&nbspPage</b></a>&nbsp&nbsp | &nbsp&nbsp
+🤗 <a href="https://hf.co/collections/nex-agi/nex-n1"><b>Model</b></a>&nbsp&nbsp | &nbsp&nbsp
+🤗 <a href="https://huggingface.co/datasets/nex-agi/agent-sft"><b>Data</b></a>&nbsp&nbsp | &nbsp&nbsp
+📑 <a href="https://github.com/nex-agi/Nex-N1/blob/main/Nex-N1-TechReport.pdf"><b>Tech&nbspReport</b></a>&nbsp&nbsp
+</div>
 
 # Nex-N1
 
@@ -14,6 +22,7 @@ DeepSeek-V3.1-Nex-N1 is the flagship release of the Nex-N1 series — a post-tra
 We are committed to making it easier than ever to build and deploy AI agents by offering researchers and entrepreneurs a high-performance, reliable, and cost-effective "out-of-the-box" agent system.
 
 ## Highlights
+
 - **Full spectrum model matrix:** From 8B to 671B parameters, the Nex series covers everything from edge-friendly setups to frontier-scale deployments.
 - **Agent-focused performance:** Demonstrates industry-leading results on programming, tool-use, web-search, and other multi-hop reasoning tasks.
 - **Production-ready utility:** Excels at mini-app development, website authoring, slide creation, and immersive role-play—delivering immediate productivity
@@ -23,6 +32,7 @@ gains.
 training services are all openly available.
 
 ## Performance
+
 Nex-N1 is evaluated on six representative agentic benchmarks (general + professional). The model consistently ranks at or near the top across tool-using, web-search, and coding-heavy evaluations, showing strong readiness for real-world agent workflows.
 
 ![Nex-N1 Benchmark Overview](./figures/Nex-N1-Benchamrk-white.png)
@@ -43,16 +53,46 @@ Nex-N1 provides various size models from 8B to 671B for different usage scenario
 | [Qwen3-30B-A3B-Nex-N1](https://huggingface.co/nex-agi/Qwen3-30B-A3B-Nex-N1) | 11.3 | 65.3 | 29.7 | 8.3 | 13.6 | 51.9 |
 | [internlm3-8B-Nex-N1](https://huggingface.co/nex-agi/internlm3-8B-Nex-N1) | 8.6 | 63.0 | 20.3 | - | - | 44.5 |
 
+Nex-N1 demonstrates competitive performance across all evaluation scenarios, showing particularly strong results in practical coding and HTML generation tasks.
+
+<div align="center">
+  <img src="./figures/coding-eval.png" width="80%"/>
+  <div>Practical Coding Evaluation</div>
+</div>
+
+<div align="center">
+  <img src="./figures/html-eval.png" width="80%"/>
+  <div>HTML Generation Evaluation</div>
+</div>
+
+Refer to <https://huggingface.co/datasets/nex-agi/coding-eval> and  <https://huggingface.co/datasets/nex-agi/html-eval> for more details.
+
 ## Usage
 
 ### Local Deployment
+
 We recommend `sglang` for serving Nex-series models locally:
+
 ```bash
 python -m sglang.launch_server --model-path /path/to/your/model
 ```
 
 ### Function Calling
-Nex-series models support robust function-calling capabilities. To maximize the function-calling capabilities of the Nex-series models, we modified the tool parser of `qwen3_coder`, see: https://github.com/sgl-project/sglang/pull/13411. To enable this feature, simply add the `--tool-call-parser qwen3_coder` flag when launching the server:
+
+Nex-series models support robust function-calling capabilities. To maximize the function-calling capabilities of the Nex-series models, we modified the tool parser of `qwen3_coder`, see: <https://github.com/sgl-project/sglang/pull/13411>. To enable this feature, simply add the `--tool-call-parser qwen3_coder` flag when launching the server:
+
 ```bash
 python -m sglang.launch_server --model-path /path/to/your/model --tool-call-parser qwen3_coder
 ```
+
+### Mini Program Development
+
+Nex-N1 is optimized for mini program development. For optimal performance, we recommend using Claude Code configured with both `context7` and a search MCP.
+
+```shell
+claude mcp add --transport http context7 https://mcp.context7.com/mcp --header "CONTEXT7_API_KEY: [CONTEXT7_API_KEY]"
+
+claude mcp add --transport stdio serper-search --env SERPER_API_KEY=[SERPER_API_KEY]  -- npx -y serper-search-scrape-mcp-server
+```
+
+Refer to <https://github.com/upstash/context7> for more details on setting up `context7`.