Model comparison
Gemini 3.1 Flash-Lite vs GPT-5.2
Head-to-head evidence from 14 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Gemini 3.1 Flash-Lite #111 (Supported); GPT-5.2 #64 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Gemini 3.1 Flash-Lite and GPT-5.2 share 14 comparable benchmark results. 1 of 8 categories are comparable. 6 results are unique to Gemini 3.1 Flash-Lite; 14 to GPT-5.2.
Updated July 20, 2026- Shared results
- 14
- Gemini 3.1 Flash-Lite only
- 6
- GPT-5.2 only
- 14
- Comparable categories
- 1 / 8
Pick GPT-5.2 if you want the stronger benchmark profile. Gemini 3.1 Flash-Lite only becomes the better choice if you want the cheaper token bill or you need the larger 1M context window.
Confidence note. This is a partial-evidence comparison with 14 shared benchmark results across 6 evidence categories; 1 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
GPT-5.2 is clearly ahead on the BenchAlign aggregate, 58.43 to 50.83. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-5.2's sharpest advantage is in multimodal & grounded, where it averages 80.4 against 73.2. The single biggest benchmark swing on the page is CharXiv, 73.2% to 82.1%.
GPT-5.2 is also the more expensive model on tokens at $1.75 input / $14.00 output per 1M tokens, versus $0.25 input / $1.50 output per 1M tokens for Gemini 3.1 Flash-Lite. That is roughly 9.3x on output cost alone. GPT-5.2 is the reasoning model in the pair, while Gemini 3.1 Flash-Lite is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use. Gemini 3.1 Flash-Lite gives you the larger context window at 1M, compared with 400K for GPT-5.2.
Category breakdown
Exact category averages are shown below. Not measured means BenchLM does not have enough sourced public coverage for that model and category.
| Category | Gemini 3.1 Flash-Lite | Δ | GPT-5.2 |
|---|---|---|---|
| Multimodal | Gemini 3.1 Flash-Lite73.2 | Margin→ 7.2 | GPT-5.280.4 |
| Agentic | Gemini 3.1 Flash-LiteNot measured | MarginNo overlap | GPT-5.255.7 |
| Coding | Gemini 3.1 Flash-LiteNot measured | MarginNo overlap | GPT-5.270.6 |
| Reasoning | Gemini 3.1 Flash-LiteNot measured | MarginNo overlap | GPT-5.252.9 |
| Knowledge | Gemini 3.1 Flash-LiteNot measured | MarginNo overlap | GPT-5.292.4 |
| Math | Gemini 3.1 Flash-LiteNot measured | MarginNo overlap | GPT-5.235.2 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
CharXiv
MultimodalA 73.2%B 82.1%Winner: GPT-5.2Δ 8.9CharXiv: Gemini 3.1 Flash-Lite scored 73.2%; GPT-5.2 scored 82.1%. GPT-5.2 wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Gemini 3.1 Flash-Lite | GPT-5.2 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Gemini 3.1 Flash-Lite$0.25 input / $1.5 output | GPT-5.2$1.75 input / $14 output | Gemini 3.1 Flash-Lite has the lower combined listed price. |
| Generation speedtokens per second | Gemini 3.1 Flash-Lite205 tok/s | GPT-5.273 tok/s | Gemini 3.1 Flash-Lite has the higher measured throughput. |
| First-answer latencyseconds to first token | Gemini 3.1 Flash-Lite7.50 s | GPT-5.2130.34 s | Gemini 3.1 Flash-Lite reaches the first token sooner. |
| Context windowmaximum listed tokens | Gemini 3.1 Flash-Lite1M | GPT-5.2400K | Gemini 3.1 Flash-Lite lists the larger context window. |
Benchmark Deep Dive
Agentic9 benchmarks
| Benchmark | Gemini 3.1 Flash-Lite | GPT-5.2 | Result |
|---|---|---|---|
| AA Agentic IndexSource | 6.2% | — | Not comparable |
| APEX-Agents-AASource | 12.2% | — | Not comparable |
| τ²-bench resultsSource | 31.3% | 84.8% | GPT-5.2 leads |
| GDPval-AASource | 7.1% | — | Not comparable |
| GDPval-AASource | 642 | — | Not comparable |
| Gert LabsSource | 38.46% | 46.54% | GPT-5.2 leads |
| BrowseCompSource | — | 65.8% | Not comparable |
| OSWorld-VerifiedSource | — | 47.3% | Not comparable |
| JobBenchSource | — | 34.3% | Not comparable |
Coding5 benchmarks
Reasoning3 benchmarks
Knowledge7 benchmarks
| Benchmark | Gemini 3.1 Flash-Lite | GPT-5.2 | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 25.0% | 42.2% | GPT-5.2 leads |
| AA-GPQA DiamondSource | 82.2% | 90.3% | GPT-5.2 leads |
| AA-HLESource | 16.2% | 35.4% | GPT-5.2 leads |
| AA-Omniscience IndexSource | -15.5% | -1.0% | GPT-5.2 leads |
| AA-Omniscience AccuracySource | 36.4% | 43.8% | GPT-5.2 leads |
| AA-Omniscience Hallucination RateSource | 81.6% | 79.7% | GPT-5.2 leads |
| GPQASource | — | 92.4% | Not comparable |
Math3 benchmarks
MultimodalGPT-5.2 wins6 benchmarks
Inst. Following1 benchmarks
| Benchmark | Gemini 3.1 Flash-Lite | GPT-5.2 | Result |
|---|---|---|---|
| AA-IFBenchSource | 77.2% | 75.4% | Gemini 3.1 Flash-Lite leads |
Frequently Asked Questions (2)
Which is better, Gemini 3.1 Flash-Lite or GPT-5.2?
GPT-5.2 is ahead on BenchLM's BenchAlign leaderboard, 58.43 to 50.83. The biggest single separator in this matchup is CharXiv, where the scores are 73.2% and 82.1%.
Which is better for multimodal and grounded tasks, Gemini 3.1 Flash-Lite or GPT-5.2?
GPT-5.2 has the edge for multimodal and grounded tasks in this comparison, averaging 80.4 versus 73.2. Inside this category, CharXiv is the benchmark that creates the most daylight between them.
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