Model comparison
Gemini 2.5 Flash-Lite vs GPT-4o mini
Gemini 2.5 Flash-Lite is the stronger model overall, scoring 37.0 to 25.5 on the Noometry Index.
Last verified . 29 shared benchmarks.
GoogleSummary
- They share 29 benchmarks with published results for both. Gemini 2.5 Flash-Lite scores higher in 9 categories and GPT-4o mini in 1 category; 9 gaps are clear of the uncertainty.
- The widest gap is in math, where Gemini 2.5 Flash-Lite leads 38.0 to 10.4.
- The biggest single-benchmark swing is WeirdML: 35.2% for Gemini 2.5 Flash-Lite and 11.8% for GPT-4o mini.
- Gemini 2.5 Flash-Lite is cheaper at $0.10 / $0.40 per million input/output tokens, against $0.15 / $0.60 for GPT-4o mini.
- Gemini 2.5 Flash-Lite accepts more context: 1.05M tokens versus 128K.
Side by side
| Gemini 2.5 Flash-Lite | GPT-4o mini | |
|---|---|---|
| Provider | OpenAI | |
| Noometry Index | 37.0 | 25.5 |
| Released | 2025-06-17 | 2024-07-18 |
| Weights | Proprietary | Proprietary |
| Context window | 1.05M | 128K |
| Max output | 66K | 16K |
| Input $ / M tokens | $0.10 | $0.15 |
| Output $ / M tokens | $0.40 | $0.60 |
| Results tracked | 33 | 60 |
Sponsored placements are available on pages like this one. Advertise on Noometry
Category by category
Coding Gemini 2.5 Flash-Lite leads
Gemini 2.5 Flash-Lite: 38.5 (#173), GPT-4o mini: 22.0 (#335)
| Benchmark | Gemini 2.5 Flash-Lite | GPT-4o mini |
|---|---|---|
| WeirdML | 35.2% | 11.8% |
| LMArena Coding | 1373 | 1290 |
| Aider Polyglot | — | 3.6% |
| BigCodeBench Instruct | — | 46.1% |
| LiveBench Coding | — | 43.1% |
| BigCodeBench Complete | — | 57.4% |
| ALE-Bench | 325.9 | — |
| HumanEval+ | — | 83.5% |
| MBPP+ | — | 72.2% |
Agentic & Tool Use Too close to call
Gemini 2.5 Flash-Lite: 28.0 (#96), GPT-4o mini: 27.5 (#101)
| Benchmark | Gemini 2.5 Flash-Lite | GPT-4o mini |
|---|---|---|
| Berkeley Function Calling Leaderboard | 36.9% | — |
| BALROG | — | 17.4% |
Reasoning Gemini 2.5 Flash-Lite leads
Gemini 2.5 Flash-Lite: 22.2 (#205), GPT-4o mini: 8.7 (#347)
| Benchmark | Gemini 2.5 Flash-Lite | GPT-4o mini |
|---|---|---|
| Kagi LLM Benchmark | 40.5% | 28.8% |
| LMArena Hard Prompts | 1377 | 1267 |
| DTBench | 62.8% | 54.4% |
| LMCA | 18.1% | 10.4% |
| Epoch Capabilities Index | 133.94 | 126.56 |
| ARC-AGI-2 | — | 0% |
| SimpleBench | — | 10.7% |
| Chess Puzzles | — | 0% |
| LiveBench Reasoning | — | 32.8% |
| Mystery Game Puzzles | — | 12% |
| LiveBench Data Analysis | — | 50% |
| LiveBench | — | 41.3% |
| PIQA | — | 88.7% |
Math Gemini 2.5 Flash-Lite leads
Gemini 2.5 Flash-Lite: 38.0 (#144), GPT-4o mini: 10.4 (#314)
| Benchmark | Gemini 2.5 Flash-Lite | GPT-4o mini |
|---|---|---|
| Omni-MATH | 48% | 28% |
| LMArena Math | 1373 | 1267 |
| FrontierMath (Tiers 1-3) | — | 0.7% |
| OTIS Mock AIME 2024-2025 | — | 6.9% |
| LiveBench Math | — | 36.3% |
| MATH Level 5 | — | 52.6% |
| GSM8K | — | 91.3% |
Knowledge Gemini 2.5 Flash-Lite leads
Gemini 2.5 Flash-Lite: 32.5 (#210), GPT-4o mini: 17.7 (#284)
| Benchmark | Gemini 2.5 Flash-Lite | GPT-4o mini |
|---|---|---|
| MMLU-Pro | 53.7% | 60.3% |
| GPQA (HELM) | 30.9% | 36.8% |
| LMArena Expert | 1373 | 1235 |
| GPQA Diamond | — | 37.7% |
| SimpleQA Verified | — | 8.3% |
| Confabulations | — | 37.2% |
| Vectara Hallucination Rate | 3.3% | — |
| BoolQ | — | 88.7% |
| MMLU | — | 81.8% |
Multimodal Gemini 2.5 Flash-Lite leads
Gemini 2.5 Flash-Lite: 29.1 (#114), GPT-4o mini: 25.9 (#122)
| Benchmark | Gemini 2.5 Flash-Lite | GPT-4o mini |
|---|---|---|
| LMArena Vision | 1198 | 1066 |
| VPCT | 30% | 34% |
| Video-MME | — | 64.8% |
| GeoBench | — | 64% |
Multilingual Gemini 2.5 Flash-Lite leads
Gemini 2.5 Flash-Lite: 49.3 (#134), GPT-4o mini: 42.0 (#199)
| Benchmark | Gemini 2.5 Flash-Lite | GPT-4o mini |
|---|---|---|
| LMArena Non-English | 1369 | 1266 |
| LMArena Chinese | 1404 | 1265 |
| LMArena French | 1388 | 1297 |
| LMArena German | 1389 | 1272 |
| LMArena Japanese | 1359 | 1216 |
| LMArena Korean | 1360 | 1195 |
| LMArena Russian | 1373 | 1275 |
| LMArena Spanish | 1396 | 1276 |
Instruction Following Gemini 2.5 Flash-Lite leads
Gemini 2.5 Flash-Lite: 70.0 (#168), GPT-4o mini: 61.9 (#239)
| Benchmark | Gemini 2.5 Flash-Lite | GPT-4o mini |
|---|---|---|
| IFEval | 81% | 78.2% |
| LMArena Instruction Following | 1367 | 1258 |
| LiveBench Instruction Following | — | 56.8% |
Long Context GPT-4o mini leads
Gemini 2.5 Flash-Lite: 33.3 (#262), GPT-4o mini: 39.1 (#186)
| Benchmark | Gemini 2.5 Flash-Lite | GPT-4o mini |
|---|---|---|
| LMArena Longer Query | 1373 | 1289 |
| Fiction.LiveBench | 47.2% | — |
Writing & Preference Gemini 2.5 Flash-Lite leads
Gemini 2.5 Flash-Lite: 56.8 (#135), GPT-4o mini: 39.5 (#248)
| Benchmark | Gemini 2.5 Flash-Lite | GPT-4o mini |
|---|---|---|
| LMArena Text | 1379 | 1286 |
| LMArena Creative Writing | 1367 | 1268 |
| WildBench | 81.8% | 79.1% |
| LMArena Multi-Turn | 1366 | 1285 |
| Short-Story Creative Writing | — | 67.2% |
| EQ-Bench Creative Writing | — | 873 |
| LiveBench Language | — | 28.6% |
Frequently asked questions
Is Gemini 2.5 Flash-Lite better than GPT-4o mini?
Gemini 2.5 Flash-Lite is the stronger model overall, scoring 37.0 to 25.5 on the Noometry Index.
Which is cheaper, Gemini 2.5 Flash-Lite or GPT-4o 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-4o mini lists at $0.15 and $0.60.
Is Gemini 2.5 Flash-Lite or GPT-4o mini better for coding?
Gemini 2.5 Flash-Lite scores higher on coding benchmarks: 38.5 versus 22.0 in the Noometry coding category.
Which has the bigger context window?
Gemini 2.5 Flash-Lite does, with 1.05M tokens against 128K.
How many benchmarks do Gemini 2.5 Flash-Lite and GPT-4o mini share?
29 benchmarks have published results for both models. Gemini 2.5 Flash-Lite has 33 scored results on Noometry and GPT-4o mini has 60.