Model Comparison
Google's Gemini 2.0 Flash costs less per intelligence point, even though OpenAI's GPT-4.1 scores higher.
Data last updated March 4, 2026
Gemini 2.0 Flash delivers more intelligence per dollar, while GPT-4.1 leads on raw benchmark scores. Gemini 2.0 Flash costs $0.0009 per request vs $0.018 for GPT-4.1 (at 5K input / 1K output tokens). GPT-4.1 scores proportionally higher on mathematical reasoning (AIME: 0.44), while Gemini 2.0 Flash's scores skew toward general knowledge (MMLU-Pro: 0.78). The question is whether GPT-4.1's higher scores justify the 20x price premium.
| Metric | Gemini 2.0 Flash | GPT-4.1 |
|---|---|---|
| Intelligence IndexComposite score from MMLU-Pro, GPQA, and AIME. Higher is better. | 18.5 | 26.3 |
| MMLU-ProGeneral knowledge and reasoning. Higher is better. | 0.8 | 0.8 |
| GPQAGraduate-level science questions. Higher is better. | 0.6 | 0.7 |
| AIMEMathematical problem solving. Higher is better. | 0.3 | 0.4 |
| Context windowMax tokens per request. Larger handles more text. | 1,000,000 | 1,047,576 |
List prices as published by the provider. Not adjusted for token efficiency.
| Metric | Gemini 2.0 Flash | GPT-4.1 |
|---|---|---|
| Input price / 1M tokens | $0.10 | $2.00 |
| Output price / 1M tokens | $0.40 | $8.00 |
| Cache hit price / 1M tokens | $0.02 | $0.50 |
Cost per IQ point based on a typical request of 5,000 input and 1,000 output tokens.
Cheaper (list price)
Gemini 2.0 Flash
Higher Benchmarks
GPT-4.1
Better Value ($/IQ point)
Gemini 2.0 Flash
Gemini 2.0 Flash
$0.000049 / IQ point
GPT-4.1
$0.0007 / IQ point
Gemini 2.0 Flash is dramatically cheaper — 20x less per request than GPT-4.1. Gemini 2.0 Flash is cheaper on both input ($0.1/M vs $2.0/M) and output ($0.4/M vs $8.0/M). At a fraction of the cost, Gemini 2.0 Flash saves significantly in production workloads. This comparison assumes a typical request of 5,000 input and 1,000 output tokens (5:1 ratio). Actual ratios vary by workload — chat and completion tasks typically run 2:1, code review around 3:1, document analysis and summarization 10:1 to 50:1, and embedding workloads are pure input with no output tokens.
GPT-4.1 scores higher overall (26.3 vs 18.5). GPT-4.1 leads on GPQA (0.67 vs 0.62) and AIME (0.44 vs 0.33), with both within 5% on MMLU-Pro. GPT-4.1 scores proportionally higher on AIME (mathematical reasoning) relative to its MMLU-Pro, while Gemini 2.0 Flash's scores are more weighted toward general knowledge. If mathematical reasoning matters, GPT-4.1's AIME score of 0.44 gives it an edge.
GPT-4.1 has a 5% larger context window at 1,047,576 tokens vs Gemini 2.0 Flash at 1,000,000 tokens. That's roughly 1,396 vs 1,333 pages of text. The extra context capacity in GPT-4.1 matters for document analysis and long conversations.
Gemini 2.0 Flash offers dramatically better value — $0.000049 per intelligence point vs GPT-4.1 at $0.0007. Gemini 2.0 Flash is cheaper, which offsets GPT-4.1's higher benchmark scores to deliver more value per dollar. If raw benchmark scores matter less than cost for your use case, Gemini 2.0 Flash is the efficient choice.
With prompt caching, Gemini 2.0 Flash is dramatically cheaper — 20x less per request than GPT-4.1. Caching saves 42% on Gemini 2.0 Flash and 42% on GPT-4.1 compared to standard input prices. Both models benefit from caching at similar rates, so the uncached price comparison holds.
Pricing verified against official vendor documentation. Updated daily. See our methodology.
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