Model comparison
Gemini 2.5 Flash-Lite vs GPT-5.4 mini
GPT-5.4 mini is the stronger model overall, scoring 44.8 to 36.4 on the Noometry Index. Gemini 2.5 Flash-Lite costs 9.6× less per token, which makes it the better buy when GPT-5.4 mini's lead doesn't matter for your workload.
Last verified . 25 shared benchmarks.
GoogleSummary
- They share 25 benchmarks with published results for both. Gemini 2.5 Flash-Lite scores higher in 0 categories and GPT-5.4 mini in 10 categories; 10 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where GPT-5.4 mini leads 51.4 to 32.1.
- The biggest single-benchmark swing is WeirdML: 35.2% for Gemini 2.5 Flash-Lite and 60.3% for GPT-5.4 mini.
- Gemini 2.5 Flash-Lite is cheaper at $0.10 / $0.40 per million input/output tokens, against $0.75 / $4.50 for GPT-5.4 mini.
- Gemini 2.5 Flash-Lite accepts more context: 1.05M tokens versus 400K.
Side by side
| Gemini 2.5 Flash-Lite | GPT-5.4 mini | |
|---|---|---|
| Provider | OpenAI | |
| Noometry Index | 36.4 | 44.8 |
| Released | 2025-06-17 | 2026-03-17 |
| Weights | Proprietary | Proprietary |
| Context window | 1.05M | 400K |
| Max output | 66K | 128K |
| Input $ / M tokens | $0.10 | $0.75 |
| Output $ / M tokens | $0.40 | $4.50 |
| Results tracked | 33 | 46 |
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Category by category
Coding GPT-5.4 mini leads
Gemini 2.5 Flash-Lite: 38.0 (#167), GPT-5.4 mini: 45.0 (#67)
| Benchmark | Gemini 2.5 Flash-Lite | GPT-5.4 mini |
|---|---|---|
| WeirdML | 35.2% | 60.3% |
| LMArena Coding | 1373 | 1438 |
| ALE-Bench | 325.9 | 1,189 |
| FrontierCode | — | 27% |
| LMArena WebDev | — | 1397 |
| SciCode | — | 49.9% |
Agentic & Tool Use GPT-5.4 mini leads
Gemini 2.5 Flash-Lite: 27.8 (#89), GPT-5.4 mini: 29.6 (#74)
| Benchmark | Gemini 2.5 Flash-Lite | GPT-5.4 mini |
|---|---|---|
| Berkeley Function Calling Leaderboard | 36.9% | — |
| DeepResearch Bench | — | 36.3% |
Reasoning GPT-5.4 mini leads
Gemini 2.5 Flash-Lite: 21.5 (#196), GPT-5.4 mini: 30.3 (#77)
| Benchmark | Gemini 2.5 Flash-Lite | GPT-5.4 mini |
|---|---|---|
| Kagi LLM Benchmark | 40.5% | 37.9% |
| LMArena Hard Prompts | 1377 | 1424 |
| DTBench | 62.8% | 80% |
| LMCA | 18.1% | 40.8% |
| Epoch Capabilities Index | 133.93 | 148.83 |
| ARC-AGI-2 | — | 18.9% |
| NYT Connections (extended) | — | 61.8% |
| ARC-AGI-1 | — | 63.7% |
| CritPt | — | 10% |
| Chess Puzzles | — | 24% |
| Thematic Generalization | — | 61.7% |
| Mystery Game Puzzles | — | 11% |
| ForecastBench | — | 57 |
Math GPT-5.4 mini leads
Gemini 2.5 Flash-Lite: 35.5 (#144), GPT-5.4 mini: 45.4 (#63)
| Benchmark | Gemini 2.5 Flash-Lite | GPT-5.4 mini |
|---|---|---|
| LMArena Math | 1373 | 1418 |
| FrontierMath (Tiers 1-3) | — | 51.2% |
| FrontierMath Tier 4 | — | 9.8% |
| OTIS Mock AIME 2024-2025 | — | 88.9% |
| ProofBench | — | 21% |
| Omni-MATH | 48% | — |
| FrontierMath (Feb 2025 set) | — | 28.3% |
| FrontierMath Tier 4 (v1) | — | 2.1% |
Knowledge GPT-5.4 mini leads
Gemini 2.5 Flash-Lite: 32.1 (#206), GPT-5.4 mini: 51.4 (#62)
| Benchmark | Gemini 2.5 Flash-Lite | GPT-5.4 mini |
|---|---|---|
| Vectara Hallucination Rate | 3.3% | 5.5% |
| LMArena Expert | 1373 | 1434 |
| GPQA Diamond | — | 86.9% |
| SimpleQA Verified | — | 29.4% |
| MMLU-Pro | 53.7% | — |
| GPQA (HELM) | 30.9% | — |
Multimodal GPT-5.4 mini leads
Gemini 2.5 Flash-Lite: 28.6 (#109), GPT-5.4 mini: 39.0 (#51)
| Benchmark | Gemini 2.5 Flash-Lite | GPT-5.4 mini |
|---|---|---|
| LMArena Vision | 1198 | 1245 |
| VPCT | 30% | — |
Multilingual GPT-5.4 mini leads
Gemini 2.5 Flash-Lite: 49.5 (#129), GPT-5.4 mini: 52.1 (#94)
| Benchmark | Gemini 2.5 Flash-Lite | GPT-5.4 mini |
|---|---|---|
| LMArena Non-English | 1369 | 1405 |
| LMArena Chinese | 1404 | 1446 |
| LMArena French | 1388 | 1440 |
| LMArena German | 1390 | 1407 |
| LMArena Japanese | 1359 | 1375 |
| LMArena Korean | 1358 | 1369 |
| LMArena Russian | 1373 | 1417 |
| LMArena Spanish | 1396 | 1403 |
Instruction Following GPT-5.4 mini leads
Gemini 2.5 Flash-Lite: 70.2 (#163), GPT-5.4 mini: 74.3 (#99)
| Benchmark | Gemini 2.5 Flash-Lite | GPT-5.4 mini |
|---|---|---|
| LMArena Instruction Following | 1366 | 1405 |
| IFEval | 81% | — |
Long Context GPT-5.4 mini leads
Gemini 2.5 Flash-Lite: 33.3 (#257), GPT-5.4 mini: 42.9 (#107)
| Benchmark | Gemini 2.5 Flash-Lite | GPT-5.4 mini |
|---|---|---|
| LMArena Longer Query | 1373 | 1407 |
| Fiction.LiveBench | 47.2% | — |
Writing & Preference GPT-5.4 mini leads
Gemini 2.5 Flash-Lite: 57.0 (#130), GPT-5.4 mini: 64.2 (#56)
| Benchmark | Gemini 2.5 Flash-Lite | GPT-5.4 mini |
|---|---|---|
| LMArena Text | 1379 | 1411 |
| LMArena Creative Writing | 1366 | 1370 |
| LMArena Multi-Turn | 1367 | 1429 |
| EQ-Bench Creative Writing | — | 1665 |
| WildBench | 81.8% | — |
Frequently asked questions
Is Gemini 2.5 Flash-Lite better than GPT-5.4 mini?
GPT-5.4 mini is the stronger model overall, scoring 44.8 to 36.4 on the Noometry Index. Gemini 2.5 Flash-Lite costs 9.6× less per token, which makes it the better buy when GPT-5.4 mini's lead doesn't matter for your workload.
Which is cheaper, Gemini 2.5 Flash-Lite or GPT-5.4 mini?
Gemini 2.5 Flash-Lite is cheaper. It lists at $0.10 per million input tokens and $0.40 per million output tokens; GPT-5.4 mini lists at $0.75 and $4.50.
Is Gemini 2.5 Flash-Lite or GPT-5.4 mini better for coding?
GPT-5.4 mini scores higher on coding benchmarks: 45.0 versus 38.0 in the Noometry coding category.
Which has the bigger context window?
Gemini 2.5 Flash-Lite does, with 1.05M tokens against 400K.
How many benchmarks do Gemini 2.5 Flash-Lite and GPT-5.4 mini share?
25 benchmarks have published results for both models. Gemini 2.5 Flash-Lite has 33 scored results on Noometry and GPT-5.4 mini has 46.