Model comparison
Gemini 2.5 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 2.5 Pro #70 (Supported); GPT-5 (high) #63 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Gemini 2.5 Pro and GPT-5 (high) share 18 comparable benchmark results. 0 of 8 categories are comparable. 6 results are unique to Gemini 2.5 Pro; 2 to GPT-5 (high).
Updated July 20, 2026- Shared results
- 18
- Gemini 2.5 Pro only
- 6
- GPT-5 (high) only
- 2
- Comparable categories
- 0 / 8
Benchmark data for Gemini 2.5 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 2.5 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 2.5 Pro | Δ | GPT-5 (high) |
|---|---|---|---|
| Coding | Gemini 2.5 Pro63.8 | MarginNo overlap | GPT-5 (high)Not measured |
| Knowledge | Gemini 2.5 Pro27.4 | MarginNo overlap | GPT-5 (high)Not measured |
| Math | Gemini 2.5 Pro11.6 | 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 2.5 Pro | GPT-5 (high) | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Gemini 2.5 Pro$1.25 input / $10 output | GPT-5 (high)$1.25 input / $10 output | Listed prices are equal. |
| Generation speedtokens per second | Gemini 2.5 Pro117 tok/s | GPT-5 (high)83 tok/s | Gemini 2.5 Pro has the higher measured throughput. |
| First-answer latencyseconds to first token | Gemini 2.5 Pro21.19 s | GPT-5 (high)36.28 s | Gemini 2.5 Pro reaches the first token sooner. |
| Context windowmaximum listed tokens | Gemini 2.5 Pro1M | GPT-5 (high)128K | Gemini 2.5 Pro lists the larger context window. |
Benchmark Deep Dive
Agentic6 benchmarks
Coding4 benchmarks
Reasoning2 benchmarks
Knowledge8 benchmarks
| Benchmark | Gemini 2.5 Pro | GPT-5 (high) | Result |
|---|---|---|---|
| GPQASource | 83% | — | Not comparable |
| HLESource | 18.8% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 25.8% | 34.7% | GPT-5 (high) leads |
| AA-GPQA DiamondSource | 84.4% | 85.4% | GPT-5 (high) leads |
| AA-HLESource | 21.1% | 26.5% | GPT-5 (high) leads |
| AA-Omniscience IndexSource | -14.3% | -8.1% | GPT-5 (high) leads |
| AA-Omniscience AccuracySource | 39.0% | 40.7% | GPT-5 (high) leads |
| AA-Omniscience Hallucination RateSource | 87.4% | 82.1% | GPT-5 (high) leads |
Math3 benchmarks
Multimodal2 benchmarks
Inst. Following1 benchmarks
| Benchmark | Gemini 2.5 Pro | GPT-5 (high) | Result |
|---|---|---|---|
| AA-IFBenchSource | 48.7% | 73.1% | GPT-5 (high) leads |
Frequently Asked Questions (3)
Can I compare Gemini 2.5 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 2.5 Pro and GPT-5 (high) today?
Gemini 2.5 Pro: $1.25 input / $10.00 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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