Model comparison
Gemini 2.5 Flash-Lite vs GPT-6.1 Sol
GPT-6.1 Sol is the stronger model overall, scoring 65.6 to 37.0 on the Noometry Index. Gemini 2.5 Flash-Lite costs 23× less per token, which makes it the better buy when GPT-6.1 Sol's lead doesn't matter for your workload.
Last verified . 14 shared benchmarks.
GoogleSummary
- They share 14 benchmarks with published results for both. Gemini 2.5 Flash-Lite scores higher in 0 categories and GPT-6.1 Sol in 10 categories; 10 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where GPT-6.1 Sol leads 81.9 to 22.2.
- Gemini 2.5 Flash-Lite is cheaper at $0.10 / $0.40 per million input/output tokens, against $2 / $10 for GPT-6.1 Sol.
- GPT-6.1 Sol accepts more context: 1.05M tokens versus 1.05M.
Side by side
| Gemini 2.5 Flash-Lite | GPT-6.1 Sol | |
|---|---|---|
| Provider | OpenAI | |
| Noometry Index | 37.0 | 65.6 |
| Released | 2025-06-17 | 2026-09-29 |
| Weights | Proprietary | Proprietary |
| Context window | 1.05M | 1.05M |
| Max output | 66K | 128K |
| Input $ / M tokens | $0.10 | $2 |
| Output $ / M tokens | $0.40 | $10 |
| Results tracked | 33 | 34 |
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Category by category
Coding GPT-6.1 Sol leads
Gemini 2.5 Flash-Lite: 38.5 (#173), GPT-6.1 Sol: 63.2 (#8)
| Benchmark | Gemini 2.5 Flash-Lite | GPT-6.1 Sol |
|---|---|---|
| LMArena Coding | 1373 | 1487 |
| DeepSWE | — | 75.2% |
| FrontierCode | — | 50.2% |
| LMArena WebDev | — | 1755 |
| SciCode | — | 55.8% |
| WeirdML | 35.2% | — |
| ALE-Bench | 325.9 | — |
Agentic & Tool Use GPT-6.1 Sol leads
Gemini 2.5 Flash-Lite: 28.0 (#96), GPT-6.1 Sol: 39.6 (#26)
| Benchmark | Gemini 2.5 Flash-Lite | GPT-6.1 Sol |
|---|---|---|
| APEX-Agents | — | 60% |
| Berkeley Function Calling Leaderboard | 36.9% | — |
| GDP.pdf | — | 32% |
Reasoning GPT-6.1 Sol leads
Gemini 2.5 Flash-Lite: 22.2 (#205), GPT-6.1 Sol: 81.9 (#2)
| Benchmark | Gemini 2.5 Flash-Lite | GPT-6.1 Sol |
|---|---|---|
| LMArena Hard Prompts | 1377 | 1466 |
| Epoch Capabilities Index | 133.94 | 166.09 |
| ARC-AGI-2 | — | 94.2% |
| Kagi LLM Benchmark | 40.5% | — |
| NYT Connections (extended) | — | 95.5% |
| ARC-AGI-1 | — | 98.5% |
| CritPt | — | 31.7% |
| Chess Puzzles | — | 61% |
| EBR-Bench | — | 54.3% |
| Mystery Game Puzzles | — | 80% |
| DTBench | 62.8% | — |
| LMCA | 18.1% | — |
Math GPT-6.1 Sol leads
Gemini 2.5 Flash-Lite: 38.0 (#144), GPT-6.1 Sol: 93.7 (#1)
| Benchmark | Gemini 2.5 Flash-Lite | GPT-6.1 Sol |
|---|---|---|
| LMArena Math | 1373 | 1464 |
| FrontierMath (Tiers 1-3) | — | 93.7% |
| FrontierMath Tier 4 | — | 100% |
| OTIS Mock AIME 2024-2025 | — | 100% |
| ProofBench | — | 99% |
| Omni-MATH | 48% | — |
Knowledge GPT-6.1 Sol leads
Gemini 2.5 Flash-Lite: 32.5 (#210), GPT-6.1 Sol: 71.8 (#4)
| Benchmark | Gemini 2.5 Flash-Lite | GPT-6.1 Sol |
|---|---|---|
| LMArena Expert | 1373 | 1502 |
| GPQA Diamond | — | 95.4% |
| SimpleQA Verified | — | 73.9% |
| MMLU-Pro | 53.7% | — |
| Vectara Hallucination Rate | 3.3% | — |
| GPQA (HELM) | 30.9% | — |
Multimodal GPT-6.1 Sol leads
Gemini 2.5 Flash-Lite: 29.1 (#114), GPT-6.1 Sol: 52.7 (#5)
| Benchmark | Gemini 2.5 Flash-Lite | GPT-6.1 Sol |
|---|---|---|
| LMArena Vision | 1198 | 1288 |
| VPCT | 30% | — |
| Furniture Assembly | — | 80% |
Multilingual GPT-6.1 Sol leads
Gemini 2.5 Flash-Lite: 49.3 (#134), GPT-6.1 Sol: 54.3 (#46)
| Benchmark | Gemini 2.5 Flash-Lite | GPT-6.1 Sol |
|---|---|---|
| LMArena Non-English | 1369 | 1438 |
| LMArena Chinese | 1404 | 1477 |
| LMArena Russian | 1373 | 1455 |
| LMArena French | 1388 | — |
| LMArena German | 1389 | — |
| LMArena Japanese | 1359 | — |
| LMArena Korean | 1360 | — |
| LMArena Spanish | 1396 | — |
Instruction Following GPT-6.1 Sol leads
Gemini 2.5 Flash-Lite: 70.0 (#168), GPT-6.1 Sol: 77.0 (#29)
| Benchmark | Gemini 2.5 Flash-Lite | GPT-6.1 Sol |
|---|---|---|
| LMArena Instruction Following | 1367 | 1468 |
| IFEval | 81% | — |
Long Context GPT-6.1 Sol leads
Gemini 2.5 Flash-Lite: 33.3 (#262), GPT-6.1 Sol: 44.9 (#54)
| Benchmark | Gemini 2.5 Flash-Lite | GPT-6.1 Sol |
|---|---|---|
| LMArena Longer Query | 1373 | 1465 |
| Fiction.LiveBench | 47.2% | — |
Writing & Preference GPT-6.1 Sol leads
Gemini 2.5 Flash-Lite: 56.8 (#135), GPT-6.1 Sol: 63.6 (#63)
| Benchmark | Gemini 2.5 Flash-Lite | GPT-6.1 Sol |
|---|---|---|
| LMArena Text | 1379 | 1447 |
| LMArena Creative Writing | 1367 | 1432 |
| LMArena Multi-Turn | 1366 | 1449 |
| WildBench | 81.8% | — |
Frequently asked questions
Is Gemini 2.5 Flash-Lite better than GPT-6.1 Sol?
GPT-6.1 Sol is the stronger model overall, scoring 65.6 to 37.0 on the Noometry Index. Gemini 2.5 Flash-Lite costs 23× less per token, which makes it the better buy when GPT-6.1 Sol's lead doesn't matter for your workload.
Which is cheaper, Gemini 2.5 Flash-Lite or GPT-6.1 Sol?
Gemini 2.5 Flash-Lite is cheaper. It lists at $0.10 per million input tokens and $0.40 per million output tokens; GPT-6.1 Sol lists at $2 and $10.
Is Gemini 2.5 Flash-Lite or GPT-6.1 Sol better for coding?
GPT-6.1 Sol scores higher on coding benchmarks: 63.2 versus 38.5 in the Noometry coding category.
Which has the bigger context window?
GPT-6.1 Sol does, with 1.05M tokens against 1.05M.
How many benchmarks do Gemini 2.5 Flash-Lite and GPT-6.1 Sol share?
14 benchmarks have published results for both models. Gemini 2.5 Flash-Lite has 33 scored results on Noometry and GPT-6.1 Sol has 34.