Model comparison
Gemini 2.5 Flash-Lite vs GPT-5 Mini
GPT-5 Mini is the stronger model overall, scoring 41.7 to 36.4 on the Noometry Index. Gemini 2.5 Flash-Lite costs 3.9× less per token, which makes it the better buy when GPT-5 Mini's lead doesn't matter for your workload.
Last verified . 33 shared benchmarks.
GoogleSummary
- They share 33 benchmarks with published results for both. Gemini 2.5 Flash-Lite scores higher in 2 categories and GPT-5 Mini in 8 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where GPT-5 Mini leads 45.5 to 32.1.
- The biggest single-benchmark swing is GPQA (HELM): 30.9% for Gemini 2.5 Flash-Lite and 75.6% for GPT-5 Mini.
- Gemini 2.5 Flash-Lite is cheaper at $0.10 / $0.40 per million input/output tokens, against $0.25 / $2 for GPT-5 Mini.
- Gemini 2.5 Flash-Lite accepts more context: 1.05M tokens versus 400K.
Side by side
| Gemini 2.5 Flash-Lite | GPT-5 Mini | |
|---|---|---|
| Provider | OpenAI | |
| Noometry Index | 36.4 | 41.7 |
| Released | 2025-06-17 | 2025-08-07 |
| Weights | Proprietary | Proprietary |
| Context window | 1.05M | 400K |
| Max output | 66K | 128K |
| Input $ / M tokens | $0.10 | $0.25 |
| Output $ / M tokens | $0.40 | $2 |
| Results tracked | 33 | 60 |
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Category by category
Coding GPT-5 Mini leads
Gemini 2.5 Flash-Lite: 38.0 (#167), GPT-5 Mini: 40.0 (#134)
| Benchmark | Gemini 2.5 Flash-Lite | GPT-5 Mini |
|---|---|---|
| WeirdML | 35.2% | 52.7% |
| LMArena Coding | 1373 | 1406 |
| ALE-Bench | 325.9 | 799.77 |
| SWE-bench Verified | — | 64.7% |
| SWE-bench Verified (bash only) | — | 59.8% |
| SWE-bench Multilingual | — | 39.7% |
| SciCode | — | 39.2% |
| AlgoTune | — | 1.38 |
Agentic & Tool Use GPT-5 Mini leads
Gemini 2.5 Flash-Lite: 27.8 (#89), GPT-5 Mini: 31.0 (#64)
| Benchmark | Gemini 2.5 Flash-Lite | GPT-5 Mini |
|---|---|---|
| Berkeley Function Calling Leaderboard | 36.9% | 55.5% |
| Terminal-Bench | — | 34.8% |
| Vending-Bench 2 | — | -31.18 |
Reasoning GPT-5 Mini leads
Gemini 2.5 Flash-Lite: 21.5 (#196), GPT-5 Mini: 24.1 (#153)
| Benchmark | Gemini 2.5 Flash-Lite | GPT-5 Mini |
|---|---|---|
| Kagi LLM Benchmark | 40.5% | 70.3% |
| LMArena Hard Prompts | 1377 | 1380 |
| DTBench | 62.8% | 80.5% |
| LMCA | 18.1% | 34.2% |
| Epoch Capabilities Index | 133.93 | 145.51 |
| ARC-AGI-2 | — | 4.4% |
| ARC-AGI-1 | — | 54.3% |
| CritPt | — | 0% |
| Chess Puzzles | — | 30% |
| EnigmaEval | — | 8.2% |
| Mystery Game Puzzles | — | 10% |
| ForecastBench | — | 61 |
Math GPT-5 Mini leads
Gemini 2.5 Flash-Lite: 35.5 (#144), GPT-5 Mini: 46.3 (#59)
| Benchmark | Gemini 2.5 Flash-Lite | GPT-5 Mini |
|---|---|---|
| Omni-MATH | 48% | 72.2% |
| LMArena Math | 1373 | 1377 |
| FrontierMath (Tiers 1-3) | — | 46.7% |
| FrontierMath Tier 4 | — | 12.2% |
| OTIS Mock AIME 2024-2025 | — | 86.7% |
| ProofBench | — | 9% |
| MATH Level 5 | — | 97.8% |
| FrontierMath (Feb 2025 set) | — | 27.2% |
| FrontierMath Tier 4 (v1) | — | 6.3% |
Knowledge GPT-5 Mini leads
Gemini 2.5 Flash-Lite: 32.1 (#206), GPT-5 Mini: 45.5 (#80)
| Benchmark | Gemini 2.5 Flash-Lite | GPT-5 Mini |
|---|---|---|
| MMLU-Pro | 53.7% | 83.5% |
| Vectara Hallucination Rate | 3.3% | 12.9% |
| GPQA (HELM) | 30.9% | 75.6% |
| LMArena Expert | 1373 | 1377 |
| GPQA Diamond | — | 75% |
| Humanity's Last Exam | — | 19.4% |
| SimpleQA Verified | — | 21.6% |
| Confabulations | — | 13.3% |
Multimodal GPT-5 Mini leads
Gemini 2.5 Flash-Lite: 28.6 (#109), GPT-5 Mini: 35.0 (#80)
| Benchmark | Gemini 2.5 Flash-Lite | GPT-5 Mini |
|---|---|---|
| LMArena Vision | 1198 | 1202 |
| VPCT | 30% | 40.2% |
Multilingual Too close to call
Gemini 2.5 Flash-Lite: 49.5 (#129), GPT-5 Mini: 49.1 (#131)
| Benchmark | Gemini 2.5 Flash-Lite | GPT-5 Mini |
|---|---|---|
| LMArena Non-English | 1369 | 1363 |
| LMArena Chinese | 1404 | 1387 |
| LMArena French | 1388 | 1385 |
| LMArena German | 1390 | 1366 |
| LMArena Japanese | 1359 | 1342 |
| LMArena Korean | 1358 | 1306 |
| LMArena Russian | 1373 | 1362 |
| LMArena Spanish | 1396 | 1355 |
Instruction Following GPT-5 Mini leads
Gemini 2.5 Flash-Lite: 70.2 (#163), GPT-5 Mini: 76.4 (#43)
| Benchmark | Gemini 2.5 Flash-Lite | GPT-5 Mini |
|---|---|---|
| IFEval | 81% | 92.7% |
| LMArena Instruction Following | 1366 | 1357 |
Long Context GPT-5 Mini leads
Gemini 2.5 Flash-Lite: 33.3 (#257), GPT-5 Mini: 41.9 (#127)
| Benchmark | Gemini 2.5 Flash-Lite | GPT-5 Mini |
|---|---|---|
| Fiction.LiveBench | 47.2% | 69.4% |
| LMArena Longer Query | 1373 | 1355 |
Writing & Preference Gemini 2.5 Flash-Lite leads
Gemini 2.5 Flash-Lite: 57.0 (#130), GPT-5 Mini: 55.4 (#143)
| Benchmark | Gemini 2.5 Flash-Lite | GPT-5 Mini |
|---|---|---|
| LMArena Text | 1379 | 1373 |
| LMArena Creative Writing | 1366 | 1325 |
| WildBench | 81.8% | 85.5% |
| LMArena Multi-Turn | 1367 | 1363 |
| Short-Story Creative Writing | — | 83.1% |
| EQ-Bench Creative Writing | — | 1313 |
Frequently asked questions
Is Gemini 2.5 Flash-Lite better than GPT-5 Mini?
GPT-5 Mini is the stronger model overall, scoring 41.7 to 36.4 on the Noometry Index. Gemini 2.5 Flash-Lite costs 3.9× less per token, which makes it the better buy when GPT-5 Mini's lead doesn't matter for your workload.
Which is cheaper, Gemini 2.5 Flash-Lite or GPT-5 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 Mini lists at $0.25 and $2.
Is Gemini 2.5 Flash-Lite or GPT-5 Mini better for coding?
GPT-5 Mini scores higher on coding benchmarks: 40.0 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 Mini share?
33 benchmarks have published results for both models. Gemini 2.5 Flash-Lite has 33 scored results on Noometry and GPT-5 Mini has 60.