GPT-5.4 nano vs Qwen3.5 Omni Plus
Head-to-head specifications
| Metric | GPT-5.4 nano | Qwen3.5 Omni Plus | Difference |
|---|---|---|---|
| Intelligence Index | 38.0 | 32.0 | +18.8% |
| Context window | 922K tokens | 400K tokens | — |
| Blended price ($/1M tokens) | $0.18 | $0.63 | -71.4% |
| Output speed (tokens/s) | 157 | 53 | +196.2% |
| Access | Proprietary API | Open weights | — |
- GPT-5.4 nano leads overall capability (Intelligence Index 38.0 vs 32.0).
- GPT-5.4 nano is the cheaper model to run at $0.18/1M blended tokens — about 3.5× cheaper.
- GPT-5.4 nano offers the larger context window (922K tokens), useful for long documents and codebases.
Verdict: GPT-5.4 nano or Qwen3.5 Omni Plus?
GPT-5.4 nano advantages
- General intelligence (+16%)
- Context window (+57%)
- Affordability (+71%)
- Output speed (+66%)
Qwen3.5 Omni Plus advantages
- No decisive advantage on the tracked metrics.
Which should you choose?
- Choose the GPT-5.4 nano if you need the strongest overall reasoning and accuracy.
- Choose the GPT-5.4 nano if you work with long documents or large codebases.
Value for money
GPT-5.4 nano offers more intelligence per dollar (4.2× the Intelligence-Index-per-cost of the alternative), making it the stronger value for high-volume use.
GPT-5.4 nano vs Qwen3.5 Omni Plus: which should you choose?
GPT-5.4 nano — OpenAI multimodal model with an Intelligence Index of 38, a 922K-token context window and a blended price of $0.18/1M tokens.
Qwen3.5 Omni Plus — Alibaba multimodal model with an Intelligence Index of 32, a 400K-token context window and a blended price of $0.63/1M tokens (open weights).
GPT-5.4 nano vs Qwen3.5 Omni Plus: GPT-5.4 nano scores higher on the Intelligence Index. GPT-5.4 nano leads overall capability (Intelligence Index 38.0 vs 32.0). GPT-5.4 nano is the cheaper model to run at $0.18/1M blended tokens — about 3.5× cheaper.
Capability: intelligence, coding and agentic work
On the composite Intelligence Index the GPT-5.4 nano scores 38.0 versus 32.0. Composite indices summarize many evaluations, but always test on your own workload before committing.
Context window and speed
The GPT-5.4 nano accepts up to 922K tokens per request, which sets how much documentation, transcript or code it can reason over at once. In measured throughput, GPT-5.4 nano generates faster (157 vs 53 tokens/s), which matters for interactive apps and high-volume pipelines.
Pricing and access
At blended per-token rates, GPT-5.4 nano is the cheaper model to run ($0.18 vs $0.63 per 1M tokens). GPT-5.4 nano is proprietary api and Qwen3.5 Omni Plus is open weights. 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 GPT-5.4 nano better than the Qwen3.5 Omni Plus?
GPT-5.4 nano is the clearly stronger overall choice, winning most of the dimensions that matter. GPT-5.4 nano leads overall capability (Intelligence Index 38.0 vs 32.0).
What is the main difference between the GPT-5.4 nano and the Qwen3.5 Omni Plus?
GPT-5.4 nano leads overall capability (Intelligence Index 38.0 vs 32.0). GPT-5.4 nano is the cheaper model to run at $0.18/1M blended tokens — about 3.5× cheaper.
Which is better value?
GPT-5.4 nano offers more intelligence per dollar (4.2× the Intelligence-Index-per-cost of the alternative), making it the stronger value for high-volume use.
Which should I choose?
Choose the GPT-5.4 nano if you need the strongest overall reasoning and accuracy. Choose the GPT-5.4 nano if you work with long documents or large codebases.
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.