Model comparison
Gemini 3.1 Pro vs GPT-5 (high)
Head-to-head evidence from 18 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Gemini 3.1 Pro #83 (Estimated); GPT-5 (high) #63 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Gemini 3.1 Pro and GPT-5 (high) share 18 comparable benchmark results. 0 of 8 categories are comparable. 29 results are unique to Gemini 3.1 Pro; 2 to GPT-5 (high).
Updated July 20, 2026- Shared results
- 18
- Gemini 3.1 Pro only
- 29
- GPT-5 (high) only
- 2
- Comparable categories
- 0 / 8
Benchmark data for Gemini 3.1 Pro and GPT-5 (high) is coming soon on BenchLM.
Confidence note. This is a partial-evidence comparison with 18 shared benchmark results across 6 evidence categories; 0 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
BenchLM has partial data for these models, but not enough overlapping benchmark coverage to produce a fair score-level comparison yet.
Gemini 3.1 Pro is priced at $2.00 input / $12.00 output per 1M tokens, versus $1.25 input / $10.00 output per 1M tokens for GPT-5 (high). Gemini 3.1 Pro has the larger context window at 1M, compared with 128K for GPT-5 (high).
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 Pro | Δ | GPT-5 (high) |
|---|---|---|---|
| Reasoning | Gemini 3.1 Pro77.1 | MarginNo overlap | GPT-5 (high)Not measured |
| Math | Gemini 3.1 Pro31.8 | MarginNo overlap | GPT-5 (high)Not measured |
| Multimodal | Gemini 3.1 Pro82.6 | MarginNo overlap | GPT-5 (high)Not measured |
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Gemini 3.1 Pro | GPT-5 (high) | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Gemini 3.1 Pro$2 input / $12 output | GPT-5 (high)$1.25 input / $10 output | GPT-5 (high) has the lower combined listed price. |
| Generation speedtokens per second | Gemini 3.1 Pro109 tok/s | GPT-5 (high)83 tok/s | Gemini 3.1 Pro has the higher measured throughput. |
| First-answer latencyseconds to first token | Gemini 3.1 Pro29.71 s | GPT-5 (high)36.28 s | Gemini 3.1 Pro reaches the first token sooner. |
| Context windowmaximum listed tokens | Gemini 3.1 Pro1M | GPT-5 (high)128K | Gemini 3.1 Pro lists the larger context window. |
Benchmark Deep Dive
Agentic17 benchmarks
| Benchmark | Gemini 3.1 Pro | GPT-5 (high) | Result |
|---|---|---|---|
| Claw-EvalSource | 57.8% | — | Not comparable |
| DeepSearchQASource | 69.7% | — | Not comparable |
| τ²-bench resultsSource | 95.6% | 84.8% | Gemini 3.1 Pro leads |
| AA Agentic IndexSource | 21.4% | 25.7% | GPT-5 (high) leads |
| APEX-Agents-AASource | 32.0% | — | Not comparable |
| GDPval-AASource | 23.2% | 28.7% | GPT-5 (high) leads |
| GDPval-AASource | 965 | 1075 | GPT-5 (high) leads |
| Gert LabsSource | 56.87% | — | Not comparable |
| ResearchClawBenchSource | 13.3% | — | Not comparable |
| AA AutomationBenchSource | 37.5% | — | Not comparable |
| AA EnterpriseOps-GymSource | 42.2% | — | Not comparable |
| AA Harvey LABSource | 0.0% | — | Not comparable |
| AA ITBenchSource | 30.3% | — | Not comparable |
| AA Tau3 BankingSource | 16.5% | — | Not comparable |
| terminalBenchHardSource | 53.8% | — | Not comparable |
| aaTerminalBench21Source | 73.8% | — | Not comparable |
| JobBenchSource | — | 8.5% | Not comparable |
Coding5 benchmarks
Reasoning3 benchmarks
Knowledge10 benchmarks
| Benchmark | Gemini 3.1 Pro | GPT-5 (high) | Result |
|---|---|---|---|
| GPQA-DSource | 94.3% | — | Not comparable |
| HLE w/o toolsSource | 45.4% | — | Not comparable |
| HealthBench HardSource | 20.6% | — | Not comparable |
| MedXpertQA (Text)Source | 71.5% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 46.5% | 34.7% | Gemini 3.1 Pro leads |
| AA-GPQA DiamondSource | 94.1% | 85.4% | Gemini 3.1 Pro leads |
| AA-HLESource | 44.7% | 26.5% | Gemini 3.1 Pro leads |
| AA-Omniscience IndexSource | 32.9% | -8.1% | Gemini 3.1 Pro leads |
| AA-Omniscience AccuracySource | 55.3% | 40.7% | Gemini 3.1 Pro leads |
| AA-Omniscience Hallucination RateSource | 49.9% | 82.1% | Gemini 3.1 Pro leads |
Math3 benchmarks
Multilingual1 benchmarks
| Benchmark | Gemini 3.1 Pro | GPT-5 (high) | Result |
|---|---|---|---|
| AA Global-MMLU-LiteSource | 93.2% | — | Not comparable |
Multimodal9 benchmarks
| Benchmark | Gemini 3.1 Pro | GPT-5 (high) | Result |
|---|---|---|---|
| MMMU-ProSource | 83.9% | — | Not comparable |
| CharXivSource | 80.2% | — | Not comparable |
| ERQASource | 69.4% | — | Not comparable |
| SimpleVQASource | 72.4% | — | Not comparable |
| ScreenSpot ProSource | 84.4% | — | Not comparable |
| ZeroBenchSource | 29.0% | — | Not comparable |
| MedXpertQA (MM)Source | 81.3% | — | Not comparable |
| AA-MMMU-ProSource | 82.4% | 74.2% | Gemini 3.1 Pro leads |
| Design Arena WebsiteSource | 1284 | 1217 | Gemini 3.1 Pro leads |
Inst. Following1 benchmarks
| Benchmark | Gemini 3.1 Pro | GPT-5 (high) | Result |
|---|---|---|---|
| AA-IFBenchSource | 77.1% | 73.1% | Gemini 3.1 Pro leads |
Frequently Asked Questions (3)
Can I compare Gemini 3.1 Pro and GPT-5 (high) on BenchLM yet?
Not fully yet. BenchLM is tracking both models, but the sourced benchmark breakdown for this comparison is still coming soon.
Why does this comparison show “coming soon”?
BenchLM only shows category winners and benchmark-level calls when we have sourced results that can be compared fairly. For these models, the public benchmark coverage is not complete enough yet.
What data is available for Gemini 3.1 Pro and GPT-5 (high) today?
Gemini 3.1 Pro: $2.00 input / $12.00 output per 1M tokens GPT-5 (high): $1.25 input / $10.00 output per 1M tokens Both model pages still include creator, context window, reasoning mode, and other metadata while benchmark coverage fills in.
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