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Gemini 3.6 Flash (high) vs GPT-5 nano (high): The Ultimate Performance & Pricing Comparison

Deep dive into reasoning, benchmarks, and latency insights.

The Final Verdict in the Gemini 3.6 Flash (high) vs GPT-5 nano (high) Showdown

The current catalog does not contain complete performance evidence for both models, so this page does not declare an overall winner. Use the available fields as comparison signals and validate the models on your own workload.

Model Snapshot

Key decision metrics at a glance.

Gemini 3.6 Flash (high)GPT-5 nano (high)
6.0
Reasoning
8.0
7.0
Coding
6.0
4.0
Multimodal
2.0
6.0
Long Context
2.0
$3
Blended Price / 1M tokens
$0.138
P95 Latency
230.958
Tokens per second

Machine-readable comparison data

ModelMetricValueUnitSource / snapshot
Gemini 3.6 Flash (high)Reasoning6.0benchmark or capability scoreArtificial Analysis · current catalog
GPT-5 nano (high)Reasoning8.0benchmark or capability scoreArtificial Analysis · current catalog
Gemini 3.6 Flash (high)Coding7.0benchmark or capability scoreArtificial Analysis · current catalog
GPT-5 nano (high)Coding6.0benchmark or capability scoreArtificial Analysis · current catalog
Gemini 3.6 Flash (high)Multimodal4.0benchmark or capability scoreArtificial Analysis · current catalog
GPT-5 nano (high)Multimodal2.0benchmark or capability scoreArtificial Analysis · current catalog
Gemini 3.6 Flash (high)Long Context6.0benchmark or capability scoreArtificial Analysis · current catalog
GPT-5 nano (high)Long Context2.0benchmark or capability scoreArtificial Analysis · current catalog
Gemini 3.6 Flash (high)Blended Price / 1M tokens$3USD per 1M tokensArtificial Analysis · current catalog
GPT-5 nano (high)Blended Price / 1M tokens$0.138USD per 1M tokensArtificial Analysis · current catalog
Gemini 3.6 Flash (high)P95 LatencymillisecondsArtificial Analysis · current catalog
GPT-5 nano (high)P95 LatencymillisecondsArtificial Analysis · current catalog
Gemini 3.6 Flash (high)Tokens per second230.958tokens per secondArtificial Analysis · current catalog
GPT-5 nano (high)Tokens per secondtokens per secondArtificial Analysis · current catalog

Data provided by Artificial Analysis; live values use the current catalog.

Overall Capabilities

This radar chart visually maps the core capabilities (reasoning, coding, math proxy, multimodal, long context) of `Gemini 3.6 Flash (high)` vs `GPT-5 nano (high)`.

IntelligenceCodingMathMultimodalLong Context
Gemini 3.6 Flash (high)GPT-5 nano (high)

Benchmark Breakdown

This grouped bar chart provides a side-by-side comparison for each benchmark metric.

Gemini 3.6 Flash (high)GPT-5 nano (high)

Speed & Latency

Lower time to first token is better; higher tokens per second is better.

Time to First Token · Gemini 3.6 Flash (high)
Time to First Token · GPT-5 nano (high)
Tokens per Second · Gemini 3.6 Flash (high)
230.958
Tokens per Second · GPT-5 nano (high)
Head to the playground to validate these results yourself

The Economics of Gemini 3.6 Flash (high) vs GPT-5 nano (high)

Pricing Breakdown

Compare input and output pricing in USD per 1M tokens.

Gemini 3.6 Flash (high)GPT-5 nano (high)

Real-World Cost Scenario

Per run: 1M input tokens + 250k output tokens

Gemini 3.6 Flash (high)$3.375

GPT-5 nano (high)$0.15

GPT-5 nano (high) costs $3.225 less per run

Review the complete pricing and packaging strategy

Your Questions about the Gemini 3.6 Flash (high) vs GPT-5 nano (high) Comparison

Is `Gemini 3.6 Flash (high)` a direct replacement for `GPT-5 nano (high)`?

The current Gemini 3.6 Flash (high) vs GPT-5 nano (high) data does not establish a universal replacement. Compare the available metrics, then validate quality, latency, reliability, and cost on your own workload.

For coding, which is better in the `Gemini 3.6 Flash (high) vs GPT-5 nano (high)` debate?

The current catalog does not contain comparable coding benchmark values for both models, so this page does not declare a coding winner.

How was this `Gemini 3.6 Flash (high) vs GPT-5 nano (high)` comparison conducted?

Our Gemini 3.6 Flash (high) vs GPT-5 nano (high) comparison uses published benchmark, pricing, speed, and latency fields provided by Artificial Analysis. Missing values remain unavailable, and the result should be checked against your workload.