Model comparison
Gemini 3.1 Flash-Lite vs GPT-5.6 Sol
Head-to-head evidence from 16 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-5.6 Sol #3 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Gemini 3.1 Flash-Lite and GPT-5.6 Sol share 16 comparable benchmark results. 1 of 8 categories are comparable. 4 results are unique to Gemini 3.1 Flash-Lite; 30 to GPT-5.6 Sol.
Updated July 23, 2026- Shared results
- 16
- Gemini 3.1 Flash-Lite only
- 4
- GPT-5.6 Sol only
- 30
- Comparable categories
- 1 / 8
Pick GPT-5.6 Sol 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 would rather avoid the extra latency and token burn of a reasoning model.
Confidence note. This is a partial-evidence comparison with 16 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-5.6 Sol is clearly ahead on the BenchAlign aggregate, 81.96 to 50.83. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-5.6 Sol's sharpest advantage is in multimodal & grounded, where it averages 83 against 73.2.
GPT-5.6 Sol is also the more expensive model on tokens at $5.00 input / $30.00 output per 1M tokens, versus $0.25 input / $1.50 output per 1M tokens for Gemini 3.1 Flash-Lite. That is roughly 20.0x on output cost alone. GPT-5.6 Sol 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.
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-5.6 Sol |
|---|---|---|---|
| Multimodal | Gemini 3.1 Flash-Lite73.2 | Margin→ 9.8 | GPT-5.6 Sol83.0 |
| Agentic | Gemini 3.1 Flash-LiteNot measured | MarginNo overlap | GPT-5.6 Sol92.0 |
| Coding | Gemini 3.1 Flash-LiteNot measured | MarginNo overlap | GPT-5.6 Sol64.6 |
| Knowledge | Gemini 3.1 Flash-LiteNot measured | MarginNo overlap | GPT-5.6 Sol94.6 |
| Math | Gemini 3.1 Flash-LiteNot measured | MarginNo overlap | GPT-5.6 Sol87.5 |
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Gemini 3.1 Flash-Lite | GPT-5.6 Sol | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Gemini 3.1 Flash-Lite$0.25 input / $1.5 output | GPT-5.6 Sol$5 input / $30 output | Gemini 3.1 Flash-Lite has the lower combined listed price. |
| Generation speedtokens per second | Gemini 3.1 Flash-Lite205 tok/s | GPT-5.6 SolNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Gemini 3.1 Flash-Lite7.50 s | GPT-5.6 SolNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Gemini 3.1 Flash-Lite1M | GPT-5.6 Sol1M | Listed context windows are equal. |
Benchmark Deep Dive
Agentic19 benchmarks
| Benchmark | Gemini 3.1 Flash-Lite | GPT-5.6 Sol | Result |
|---|---|---|---|
| AA Agentic IndexSource | 6.2% | 54.0% | GPT-5.6 Sol leads |
| APEX-Agents-AASource | 12.2% | — | Not comparable |
| τ²-bench resultsSource | 31.3% | 85.1% | GPT-5.6 Sol leads |
| GDPval-AASource | 7.1% | 61.8% | GPT-5.6 Sol leads |
| GDPval-AASource | 642 | 1736 | GPT-5.6 Sol leads |
| Gert LabsSource | 38.46% | — | Not comparable |
| Terminal-Bench 2.0Source | — | 91.9% | Not comparable |
| BrowseCompSource | — | 92.2% | Not comparable |
| OSWorld 2.0Source | — | 62.6% | Not comparable |
| CyberGymSource | — | 84.5% | Not comparable |
| ExploitGymSource | — | 33.7% | Not comparable |
| ToolathlonSource | — | 58% | Not comparable |
| AA BriefcaseSource | — | 1501 | Not comparable |
| AA ITBenchSource | — | 56.2% | Not comparable |
| AA Tau3 BankingSource | — | 33.0% | Not comparable |
| AA AutomationBenchSource | — | 51.2% | Not comparable |
| AA Harvey LABSource | — | 87.2% | Not comparable |
| terminalBenchHardSource | — | 65.9% | Not comparable |
| aaTerminalBench21Source | — | 88% | Not comparable |
Coding9 benchmarks
| Benchmark | Gemini 3.1 Flash-Lite | GPT-5.6 Sol | Result |
|---|---|---|---|
| Vibe Code BenchSource | 0.00% | — | Not comparable |
| AA Coding IndexSource | 34.7% | 77.4% | GPT-5.6 Sol leads |
| AA-SciCodeSource | 41.9% | 56.1% | GPT-5.6 Sol leads |
| SWE-bench ProSource | — | 64.6% | Not comparable |
| Terminal-Bench 2.0Source | — | 91.9% | Not comparable |
| deepSweSource | — | 72.7% | Not comparable |
| FrontierCode 1.1 ExtendedSource | — | 60.6% | Not comparable |
| cursorBench32Source | — | 67.2% | Not comparable |
| VulcanBench v3Source | — | 87.0% | Not comparable |
Reasoning4 benchmarks
Knowledge10 benchmarks
| Benchmark | Gemini 3.1 Flash-Lite | GPT-5.6 Sol | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 25.0% | 58.9% | GPT-5.6 Sol leads |
| AA-GPQA DiamondSource | 82.2% | 94.1% | GPT-5.6 Sol leads |
| AA-HLESource | 16.2% | 47.2% | GPT-5.6 Sol leads |
| AA-Omniscience IndexSource | -15.5% | 21.7% | GPT-5.6 Sol leads |
| AA-Omniscience AccuracySource | 36.4% | 58.5% | GPT-5.6 Sol leads |
| AA-Omniscience Hallucination RateSource | 81.6% | 88.8% | Gemini 3.1 Flash-Lite leads |
| GPQASource | — | 94.6% | Not comparable |
| GPQA-DSource | — | 94.6% | Not comparable |
| HealthBench ProfessionalSource | — | 60.5% | Not comparable |
| HealthBench HardSource | — | 33.1% | Not comparable |
Math3 benchmarks
MultimodalGPT-5.6 Sol wins4 benchmarks
Inst. Following1 benchmarks
| Benchmark | Gemini 3.1 Flash-Lite | GPT-5.6 Sol | Result |
|---|---|---|---|
| AA-IFBenchSource | 77.2% | 72.7% | Gemini 3.1 Flash-Lite leads |
Frequently Asked Questions (2)
Which is better, Gemini 3.1 Flash-Lite or GPT-5.6 Sol?
GPT-5.6 Sol is ahead on BenchLM's BenchAlign leaderboard, 81.96 to 50.83.
Which is better for multimodal and grounded tasks, Gemini 3.1 Flash-Lite or GPT-5.6 Sol?
GPT-5.6 Sol has the edge for multimodal and grounded tasks in this comparison, averaging 83 versus 73.2. Inside this category, AA-MMMU-Pro is the benchmark that creates the most daylight between them.
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