GPT-5.4 vs Gemini 3.5 Flash
Side-by-side comparison of pricing, context window, modalities, licensing, and strengths — with practical guidance on which model fits which workload.
| Spec | GPT-5.4 | Gemini 3.5 Flash |
|---|---|---|
| Provider | OpenAI | |
| Context window | 1M tokens | 1M tokens |
| Input price (per 1M tokens) | $2.50 | $1.50 |
| Output price (per 1M tokens) | $15.00 | $9.00 |
| Example workload (10M in + 2M out) | $55.00 / month | $33.00 / month |
| Modalities | text, image, code | text, image, audio, video, code |
| Knowledge cutoff | Not disclosed | Not disclosed |
| Release date | 2026 | 2026 |
| License | Proprietary | Proprietary |
| Strengths | Coding, Tool search, Structured output, Price-performance | Agentic coding, Speed, Long context, Value |
| Open weights | No | No |
Verdict
Two different answers to “fast and affordable”. Gemini 3.5 Flash is cheaper ($1.50/$9 vs $2.50/$15) and accepts video and audio, making it the multimodal-value pick. GPT-5.4 is the stronger reasoner and coder of the pair and brings tool search — efficient use of large tool libraries — plus OpenAI’s structured-output stack. Both offer roughly 1M-token contexts, though GPT-5.4 bills long prompts (>272K tokens) at double input rates.
When to choose GPT-5.4
Pick GPT-5.4 for harder reasoning and coding, apps with many tools, and strict structured outputs.
When to choose Gemini 3.5 Flash
Pick Gemini 3.5 Flash for video/audio pipelines, long-context summarisation at flat pricing, and lower cost overall.
Prices and specs reflect published provider information and change frequently — always confirm on the provider's pricing page before committing to a workload.
Frequently asked questions
Which is cheaper: GPT-5.4 or Gemini 3.5 Flash?
Gemini 3.5 Flash is cheaper per token: $1.50 input / $9.00 output per 1M tokens, versus $2.50 / $15.00 for GPT-5.4. Actual costs depend on your input-to-output ratio — try the AI cost calculator for your own numbers.
Which has the larger context window?
GPT-5.4 supports 1M tokens versus 1M for Gemini 3.5 Flash — roughly 1.0× more room for documents, code, and conversation history.
Can I self-host either model?
No — both models are proprietary and available only through their providers' APIs or cloud platforms.
How should I test which model is better for my use case?
Benchmarks are a starting point, not an answer. Run both models on 20–50 examples of your real task and compare outputs blind. Use our token counter to estimate prompt sizes and the cost calculator to project monthly spend before committing.