Nex-N2-Pro vs Grok 4.5
Head-to-head specifications
| Metric | Nex-N2-Pro | Grok 4.5 | Difference |
|---|---|---|---|
| Intelligence Index | 41.0 | 54.0 | -24.1% |
| Coding Index | 59.1 | 72.4 | -18.4% |
| Agentic Index | 31.0 | 45.7 | — |
| Context window | 400K tokens | 922K tokens | — |
| Blended price ($/1M tokens) | $0.43 | $0.87 | -50.6% |
| Output speed (tokens/s) | 142 | 118 | +20.3% |
| Access | Open weights | Proprietary API | — |
- Grok 4.5 leads overall capability (Intelligence Index 54.0 vs 41.0).
- Nex-N2-Pro is the cheaper model to run at $0.43/1M blended tokens — about 2.0× cheaper.
- Grok 4.5 offers the larger context window (922K tokens), useful for long documents and codebases.
Verdict: Nex-N2-Pro or Grok 4.5?
Nex-N2-Pro advantages
- Affordability (+51%)
- Output speed (+17%)
Grok 4.5 advantages
- General intelligence (+24%)
- Coding ability (+18%)
- Agentic task performance (+32%)
- Context window (+57%)
Which should you choose?
- Choose the Nex-N2-Pro if you want the lowest cost per token at scale.
- Choose the Grok 4.5 if you need the strongest overall reasoning and accuracy.
- Choose the Nex-N2-Pro if low latency and fast generation matter for your application.
Value for money
Nex-N2-Pro offers more intelligence per dollar (1.5× the Intelligence-Index-per-cost of the alternative), making it the stronger value for high-volume use. It is also open-weight, so self-hosting can reduce costs further at scale.
Nex-N2-Pro vs Grok 4.5: which should you choose?
Nex-N2-Pro — Nex multimodal model with an Intelligence Index of 41, a 400K-token context window and a blended price of $0.43/1M tokens (open weights).
Grok 4.5 — xAI multimodal model with an Intelligence Index of 54, a 922K-token context window and a blended price of $0.87/1M tokens.
Nex-N2-Pro vs Grok 4.5: Grok 4.5 scores higher on the Intelligence Index. Grok 4.5 leads overall capability (Intelligence Index 54.0 vs 41.0). Nex-N2-Pro is the cheaper model to run at $0.43/1M blended tokens — about 2.0× cheaper.
Capability: intelligence, coding and agentic work
On the composite Intelligence Index the Grok 4.5 scores 54.0 versus 41.0. For software development, the Coding Index puts Grok 4.5 ahead (72.4 vs 59.1). On agentic, multi-step tool-use tasks, Grok 4.5 measures stronger. Composite indices summarize many evaluations, but always test on your own workload before committing.
Context window and speed
The Grok 4.5 accepts up to 922K tokens per request, which sets how much documentation, transcript or code it can reason over at once. In measured throughput, Nex-N2-Pro generates faster (142 vs 118 tokens/s), which matters for interactive apps and high-volume pipelines.
Pricing and access
At blended per-token rates, Nex-N2-Pro is the cheaper model to run ($0.43 vs $0.87 per 1M tokens). Nex-N2-Pro is open weights and Grok 4.5 is proprietary api. Open-weight models can be self-hosted, trading per-call cost for infrastructure you manage; for production also weigh rate limits, throughput and data-residency requirements.
The verdict
Both are credible choices in the ai model comparison space; the specification table above lays out every metric so you can weigh the trade-offs that matter to you. Pick the one whose strengths line up with how you will actually use it.
Frequently asked questions
Is the Nex-N2-Pro better than the Grok 4.5?
Grok 4.5 takes the overall edge, though Nex-N2-Pro wins in specific areas worth weighing. Grok 4.5 leads overall capability (Intelligence Index 54.0 vs 41.0).
What is the main difference between the Nex-N2-Pro and the Grok 4.5?
Grok 4.5 leads overall capability (Intelligence Index 54.0 vs 41.0). Nex-N2-Pro is the cheaper model to run at $0.43/1M blended tokens — about 2.0× cheaper.
Which is better value?
Nex-N2-Pro offers more intelligence per dollar (1.5× the Intelligence-Index-per-cost of the alternative), making it the stronger value for high-volume use. It is also open-weight, so self-hosting can reduce costs further at scale.
Which should I choose?
Choose the Nex-N2-Pro if you want the lowest cost per token at scale. Choose the Grok 4.5 if you need the strongest overall reasoning and accuracy.
Methodology
Large language models are compared on independent leaderboard metrics: an Intelligence Index (a composite of reasoning and knowledge evaluations), Coding and Agentic indices where measured, community arena Elo, maximum context window, a blended API price per million tokens (weighted across cache-hit, input and output rates), and measured output speed in tokens per second. Where a model ships multiple reasoning-effort variants, we report its strongest variant. Benchmarks capture only part of real-world quality, which also depends on tool use, latency, safety and task fit — and this space moves quickly, so figures reflect the leaderboard snapshot on the page date.