Model comparison
Gemini 2.5 Flash-Lite vs GPT-5 Pro
GPT-5 Pro is the stronger model overall, scoring 46.4 to 37.0 on the Noometry Index. Gemini 2.5 Flash-Lite costs 236× less per token, which makes it the better buy when GPT-5 Pro's lead doesn't matter for your workload.
Last verified . 3 shared benchmarks.
GoogleSummary
- They share 3 benchmarks with published results for both. Gemini 2.5 Flash-Lite scores higher in 0 categories and GPT-5 Pro in 4 categories; 4 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where GPT-5 Pro leads 56.7 to 32.5.
- The biggest single-benchmark swing is Kagi LLM Benchmark: 40.5% for Gemini 2.5 Flash-Lite and 76.8% for GPT-5 Pro.
- Gemini 2.5 Flash-Lite is cheaper at $0.10 / $0.40 per million input/output tokens, against $15 / $120 for GPT-5 Pro.
- Gemini 2.5 Flash-Lite accepts more context: 1.05M tokens versus 400K.
Side by side
| Gemini 2.5 Flash-Lite | GPT-5 Pro | |
|---|---|---|
| Provider | OpenAI | |
| Noometry Index | 37.0 | 46.4 |
| Released | 2025-06-17 | 2025-10-06 |
| Weights | Proprietary | Proprietary |
| Context window | 1.05M | 400K |
| Max output | 66K | 272K |
| Input $ / M tokens | $0.10 | $15 |
| Output $ / M tokens | $0.40 | $120 |
| Results tracked | 33 | 12 |
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Category by category
Coding GPT-5 Pro leads
Gemini 2.5 Flash-Lite: 38.5 (#173), GPT-5 Pro: 44.0 (#80)
| Benchmark | Gemini 2.5 Flash-Lite | GPT-5 Pro |
|---|---|---|
| WeirdML | 35.2% | 60.4% |
| LMArena Coding | 1373 | — |
| ALE-Bench | 325.9 | — |
| AlgoTune | — | 1.31 |
Agentic & Tool Use Not comparable
Gemini 2.5 Flash-Lite: 28.0 (#96), GPT-5 Pro: —
| Benchmark | Gemini 2.5 Flash-Lite | GPT-5 Pro |
|---|---|---|
| Berkeley Function Calling Leaderboard | 36.9% | — |
Reasoning GPT-5 Pro leads
Gemini 2.5 Flash-Lite: 22.2 (#205), GPT-5 Pro: 38.9 (#62)
| Benchmark | Gemini 2.5 Flash-Lite | GPT-5 Pro |
|---|---|---|
| Kagi LLM Benchmark | 40.5% | 76.8% |
| Epoch Capabilities Index | 133.94 | 150.28 |
| ARC-AGI-2 | — | 18.3% |
| SimpleBench | — | 61.6% |
| ARC-AGI-1 | — | 70.2% |
| EnigmaEval | — | 18.8% |
| LMArena Hard Prompts | 1377 | — |
| DTBench | 62.8% | — |
| LMCA | 18.1% | — |
Math GPT-5 Pro leads
Gemini 2.5 Flash-Lite: 38.0 (#144), GPT-5 Pro: 48.5 (#63)
| Benchmark | Gemini 2.5 Flash-Lite | GPT-5 Pro |
|---|---|---|
| FrontierMath (Tiers 1-3) | — | 55.8% |
| FrontierMath Tier 4 | — | 19.5% |
| Omni-MATH | 48% | — |
| LMArena Math | 1373 | — |
| FrontierMath Tier 4 (v1) | — | 14.6% |
Knowledge GPT-5 Pro leads
Gemini 2.5 Flash-Lite: 32.5 (#210), GPT-5 Pro: 56.7 (#42)
| Benchmark | Gemini 2.5 Flash-Lite | GPT-5 Pro |
|---|---|---|
| Humanity's Last Exam | — | 31.6% |
| MMLU-Pro | 53.7% | — |
| Vectara Hallucination Rate | 3.3% | — |
| GPQA (HELM) | 30.9% | — |
| LMArena Expert | 1373 | — |
Multimodal Not comparable
Gemini 2.5 Flash-Lite: 29.1 (#114), GPT-5 Pro: —
| Benchmark | Gemini 2.5 Flash-Lite | GPT-5 Pro |
|---|---|---|
| LMArena Vision | 1198 | — |
| VPCT | 30% | — |
Multilingual Not comparable
Gemini 2.5 Flash-Lite: 49.3 (#134), GPT-5 Pro: —
| Benchmark | Gemini 2.5 Flash-Lite | GPT-5 Pro |
|---|---|---|
| LMArena Non-English | 1369 | — |
| LMArena Chinese | 1404 | — |
| LMArena French | 1388 | — |
| LMArena German | 1389 | — |
| LMArena Japanese | 1359 | — |
| LMArena Korean | 1360 | — |
| LMArena Russian | 1373 | — |
| LMArena Spanish | 1396 | — |
Instruction Following Not comparable
Gemini 2.5 Flash-Lite: 70.0 (#168), GPT-5 Pro: —
| Benchmark | Gemini 2.5 Flash-Lite | GPT-5 Pro |
|---|---|---|
| IFEval | 81% | — |
| LMArena Instruction Following | 1367 | — |
Long Context Not comparable
Gemini 2.5 Flash-Lite: 33.3 (#262), GPT-5 Pro: —
| Benchmark | Gemini 2.5 Flash-Lite | GPT-5 Pro |
|---|---|---|
| Fiction.LiveBench | 47.2% | — |
| LMArena Longer Query | 1373 | — |
Writing & Preference Not comparable
Gemini 2.5 Flash-Lite: 56.8 (#135), GPT-5 Pro: —
| Benchmark | Gemini 2.5 Flash-Lite | GPT-5 Pro |
|---|---|---|
| LMArena Text | 1379 | — |
| LMArena Creative Writing | 1367 | — |
| WildBench | 81.8% | — |
| LMArena Multi-Turn | 1366 | — |
Frequently asked questions
Is Gemini 2.5 Flash-Lite better than GPT-5 Pro?
GPT-5 Pro is the stronger model overall, scoring 46.4 to 37.0 on the Noometry Index. Gemini 2.5 Flash-Lite costs 236× less per token, which makes it the better buy when GPT-5 Pro's lead doesn't matter for your workload.
Which is cheaper, Gemini 2.5 Flash-Lite or GPT-5 Pro?
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 Pro lists at $15 and $120.
Is Gemini 2.5 Flash-Lite or GPT-5 Pro better for coding?
GPT-5 Pro scores higher on coding benchmarks: 44.0 versus 38.5 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 Pro share?
3 benchmarks have published results for both models. Gemini 2.5 Flash-Lite has 33 scored results on Noometry and GPT-5 Pro has 12.