LLMnex-agi

Nex AGI: Nex-N2-Pro (free)

Nex-N2-Pro is an agentic mixture-of-experts model from Nex AGI, with 17B active parameters out of 397B total. Built on the Qwen3.5 architecture, it accepts text and image input and produces...

Anyone in the Space can @-mention Nex AGI: Nex-N2-Pro (free) with the team's shared context - pooled credits, one chat, one memory.

All models

Starter is free forever - 1 Space, 100 credits/month, 1 MCP. No card.

Verdict

Nex-N2-Pro offers a 262K context window with vision capabilities at zero cost, making it compelling for teams testing multimodal workflows or processing long documents without budget constraints. The lack of public benchmarks means performance is unproven against established models—expect to validate outputs carefully. This is the model to reach for when you need generous context and vision support for prototyping or non-critical tasks where cost elimination matters more than guaranteed quality.

Best for

  • Budget-constrained document analysis projects
  • Prototyping multimodal applications
  • Long-context experimentation without usage fees
  • Screenshot and image understanding tasks
  • High-volume testing environments

Strengths

The 262K token context window handles substantial documents, codebases, or conversation histories in a single pass. Vision support enables screenshot analysis, diagram interpretation, and image-text workflows without switching models. Zero pricing removes cost as a barrier for experimentation, high-volume testing, or educational use cases. The combination of long context and multimodal input at no charge creates a unique position for teams exploring capabilities before committing to paid infrastructure.

Trade-offs

No public benchmark data means quality is unverified against peers like GPT-4o, Claude, or Gemini—you're testing blind. Proprietary licensing limits transparency into training data, safety measures, or model architecture. Free tier models often impose rate limits, availability constraints, or deprioritized inference that can disrupt production workflows. Without established performance metrics, you'll need to run your own validation suite before trusting outputs for anything beyond experimentation.

Specifications

Provider
nex-agi
Category
llm
Context length
262,144 tokens
Max output
262,144 tokens
Modalities
text, image
License
proprietary
Released
2026-06-08

Pricing

Input
$0.00/Mtok
Output
$0.00/Mtok
Model ID
nex-agi/nex-n2-pro:free

Per-token prices show what the model costs upstream. On Switchy your team draws from one shared org credit pool - one plan, one balance for everyone.

Team cost calculator

Estimated monthly spend
Freeno token cost
17.6M tokens / month
5 seats · 80 msgs/day

Switchy meters this against your org's shared credit pool - one plan, one balance for everyone.

Providers

ProviderContextInputOutputP50 latencyThroughput30d uptime
nex-agi262k$0.00/Mtok$0.00/Mtok

Performance

Performance snapshots are collected daily. Check back after the next ingestion run.

Benchmarks

Public benchmark scores are not available yet for this model. Check back after the next ingestion run.

Works well with

Top MCPs

Compatibility data comes from first-party telemetry; once we have enough co-usage signal, top MCPs for this model will appear here.

How Switchy teams use it

Not enough Spaces have used this model yet to share anonymised team stats. We wait for at least 50 distinct Spaces per week before publishing any aggregate.

Starter prompts

Long Document Summary

Read this entire document and provide a structured summary with: (1) main thesis, (2) three key findings, (3) methodology used, and (4) limitations mentioned by the authors.
Open in a Space →

Screenshot Debugging

Analyze this screenshot of an application error. Identify what went wrong, suggest the likely cause, and recommend specific debugging steps.
Open in a Space →

Codebase Context Analysis

Here are five files from a Python project. Explain how the modules interact, identify any circular dependencies, and suggest refactoring opportunities.
Open in a Space →

Diagram Interpretation

Examine this system architecture diagram and describe: (1) main components, (2) data flow between services, (3) potential bottlenecks, and (4) missing redundancy.
Open in a Space →

Multi-Turn Conversation

I'm going to describe a complex business scenario in stages. After each stage, summarize what you understand so far and ask clarifying questions before I continue.
Open in a Space →
Data last verified 2 hours ago.Sources aggregated hourly to weekly. See docs/architecture/model-directory.md.