Nova 2.0 Lite vs GPT-5.1 Codex mini
Head-to-head specifications
| Metric | Nova 2.0 Lite | GPT-5.1 Codex mini | Difference |
|---|---|---|---|
| Intelligence Index | 24.0 | 32.0 | -25.0% |
| Context window | 1M tokens | 922K tokens | — |
| Blended price ($/1M tokens) | $0.43 | $0.37 | +16.2% |
| Output speed (tokens/s) | 146 | 205 | -28.8% |
| Access | Proprietary API | Proprietary API | — |
- GPT-5.1 Codex mini leads overall capability (Intelligence Index 32.0 vs 24.0).
- GPT-5.1 Codex mini is the cheaper model to run at $0.37/1M blended tokens — about 1.2× cheaper.
- Nova 2.0 Lite offers the larger context window (1M tokens), useful for long documents and codebases.
Verdict: Nova 2.0 Lite or GPT-5.1 Codex mini?
Nova 2.0 Lite advantages
- Context window (+8%)
GPT-5.1 Codex mini advantages
- General intelligence (+25%)
- Affordability (+14%)
- Output speed (+29%)
Which should you choose?
- Choose the Nova 2.0 Lite if you work with long documents or large codebases.
- Choose the GPT-5.1 Codex mini if you need the strongest overall reasoning and accuracy.
Value for money
GPT-5.1 Codex mini offers more intelligence per dollar (1.5× the Intelligence-Index-per-cost of the alternative), making it the stronger value for high-volume use.
Nova 2.0 Lite vs GPT-5.1 Codex mini: which should you choose?
Nova 2.0 Lite — Amazon multimodal model with an Intelligence Index of 24, a 1M-token context window and a blended price of $0.43/1M tokens.
GPT-5.1 Codex mini — OpenAI multimodal model with an Intelligence Index of 32, a 922K-token context window and a blended price of $0.37/1M tokens.
Nova 2.0 Lite vs GPT-5.1 Codex mini: GPT-5.1 Codex mini scores higher on the Intelligence Index. GPT-5.1 Codex mini leads overall capability (Intelligence Index 32.0 vs 24.0). GPT-5.1 Codex mini is the cheaper model to run at $0.37/1M blended tokens — about 1.2× cheaper.
Capability: intelligence, coding and agentic work
On the composite Intelligence Index the GPT-5.1 Codex mini scores 32.0 versus 24.0. Composite indices summarize many evaluations, but always test on your own workload before committing.
Context window and speed
The Nova 2.0 Lite accepts up to 1 million tokens per request, which sets how much documentation, transcript or code it can reason over at once. In measured throughput, GPT-5.1 Codex mini generates faster (205 vs 146 tokens/s), which matters for interactive apps and high-volume pipelines.
Pricing and access
At blended per-token rates, GPT-5.1 Codex mini is the cheaper model to run ($0.37 vs $0.43 per 1M tokens). Nova 2.0 Lite is proprietary api and GPT-5.1 Codex mini 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 Nova 2.0 Lite better than the GPT-5.1 Codex mini?
GPT-5.1 Codex mini is the clearly stronger overall choice, winning most of the dimensions that matter. GPT-5.1 Codex mini leads overall capability (Intelligence Index 32.0 vs 24.0).
What is the main difference between the Nova 2.0 Lite and the GPT-5.1 Codex mini?
GPT-5.1 Codex mini leads overall capability (Intelligence Index 32.0 vs 24.0). GPT-5.1 Codex mini is the cheaper model to run at $0.37/1M blended tokens — about 1.2× cheaper.
Which is better value?
GPT-5.1 Codex mini offers more intelligence per dollar (1.5× the Intelligence-Index-per-cost of the alternative), making it the stronger value for high-volume use.
Which should I choose?
Choose the Nova 2.0 Lite if you work with long documents or large codebases. Choose the GPT-5.1 Codex mini 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.