Gemma 4 31B Instruct is Google DeepMind's 30.7B dense multimodal model supporting text and image input with text output. Features a 256K token context window, configurable thinking/reasoning mode, native function...
Model details →Google: Gemma 4 31B vs Nex AGI: Nex-N2-Pro
Google: Gemma 4 31B wins on 2 of 6 axes — pricing and capability skew in its favour for most workloads.
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...
Model details →Side-by-side comparison
| Capability | Google: Gemma 4 31B | Nex AGI: Nex-N2-Pro | Winner |
|---|---|---|---|
| Context window Maximum number of input tokens the model can attend to in a single request. | 262K | 262K | Tie |
| Input price (per 1M) Cost per million input tokens billed by the provider. | $0.10 | $0.25 | 🏆 Google: Gemma 4 31B |
| Output price (per 1M) Cost per million output tokens billed by the provider. | $0.34 | $1.00 | 🏆 Google: Gemma 4 31B |
| Tool / function calling First-class support for emitting structured tool calls. | Yes | Yes | Tie |
| Vision input Accepts image inputs alongside text. | Yes | Yes | Tie |
| Reasoning mode Internal chain-of-thought / extended-thinking support. | Yes | Yes | Tie |
Frequently asked questions
Is Google: Gemma 4 31B better than Nex AGI: Nex-N2-Pro?
Google: Gemma 4 31B wins on 2 of 6 axes — pricing and capability skew in its favour for most workloads.
What's the price difference between Google: Gemma 4 31B and Nex AGI: Nex-N2-Pro?
Input: $0.10 vs $0.25 per 1M tokens. Output: $0.34 vs $1.00 per 1M tokens.
What context windows do Google: Gemma 4 31B and Nex AGI: Nex-N2-Pro support?
Google: Gemma 4 31B supports up to 262K tokens. Nex AGI: Nex-N2-Pro supports up to 262K tokens.
Do both Google: Gemma 4 31B and Nex AGI: Nex-N2-Pro support tool calling?
Google: Gemma 4 31B: yes. Nex AGI: Nex-N2-Pro: yes.
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