Compare/GPT-5.1 (high) vs Gemini 2.5 Pro

GPT-5.1 (high)vsGemini 2.5 Pro

Side-by-side comparison of pricing, 12 benchmarks, and generation speed.

OpenAI

GPT-5.1 (high)

Input
$1.25/M
Output
$10/M
Speed
112 tok/s
TTFT
28.41s
Google

Gemini 2.5 Pro

Input
$1.25/M
Output
$10/M
Speed
133 tok/s
TTFT
20.46s

Winner by Category

Cheaper
Tie
Faster (tok/s)
Gemini 2.5 Pro
Lower Latency
Gemini 2.5 Pro
Benchmarks (2-0)
GPT-5.1 (high)

Pricing Comparison

MetricGPT-5.1 (high)Gemini 2.5 Pro
Input ($/M tokens)$1.25$1.25
Output ($/M tokens)$10$10
Cost for 1M input + 100K output tokens:
GPT-5.1 (high)$2.25
Gemini 2.5 Pro$2.25

Speed Comparison

Output Speed (tokens/s) — higher is better
GPT-5.1 (high)
112 tok/s
Gemini 2.5 Pro
133 tok/s
Time to First Token (seconds) — lower is better
GPT-5.1 (high)
28.41s
Gemini 2.5 Pro
20.46s

Editorial Analysis

Verdict. GPT-5.1 (high) wins the overall benchmark matchup 2–0 across 2 overlapping categories, but raw benchmark score is only one input to the decision.

Pricing. Both models sit in the mid-tier bracket for output-token pricing. At 1.0× the per-million-token cost, Gemini 2.5 Pro is meaningfully cheaper if your traffic is output-heavy (long completions, document generation, agent loops). Gemini 2.5 Pro makes more sense when output volume is low and absolute reasoning quality justifies the premium.

Strengths. GPT-5.1 (high) is strongest on Coding Index (49.4), Intelligence Index (37.5). Gemini 2.5 Pro leads on Coding Index (33.3), Intelligence Index (25.9).

Speed. Throughput is comparable — 112 tok/s vs 133 tok/s — so generation speed shouldn't drive your choice here. Look at the per-benchmark wins instead.

Provider. OpenAI and Google sell to overlapping but distinct developer audiences: OpenAI tends to ship frontier reasoning models with premium positioning, while Google often prices more aggressively. Your existing vendor relationships, billing, and SLA preferences may matter as much as the raw numbers above.

Workload cost. Workload scenarios (per million requests at 30M input + 15M output tokens): GPT-5.1 (high) costs $187.50 ($2250/year); Gemini 2.5 Pro costs $187.50 ($2250/year). At a smaller 5M-input/2M-output scale (single-developer tool or prototype): GPT-5.1 (high) ≈ $26.25/run, Gemini 2.5 Pro ≈ $26.25/run. At agent/realtime scale (200M input / 100M output per million requests): GPT-5.1 (high) ≈ $1250/run, Gemini 2.5 Pro ≈ $1250/run.

Recommendation. Both models have legitimate use cases — the right answer depends on whether you are optimizing for benchmark ceiling, latency, or unit cost. Start with the cheaper / faster model, evaluate against your specific task, and only switch if the upgrade shows a meaningful lift.

Benchmark Comparison

Data from Artificial Analysis API — 12 benchmarks

Intelligence Index
37.525.9
Coding Index
49.433.3
Math Index
GPQA Diamond
MMLU-Pro
LiveCodeBench
AIME 2025
MATH-500
Humanity's Last Exam
SciCode
IFBench
TerminalBench
GPT-5.1 (high)2 wins
0 winsGemini 2.5 Pro

Frequently Asked Questions

Which is cheaper, GPT-5.1 (high) or Gemini 2.5 Pro?

Both models have similar pricing. Check the detailed breakdown above for input vs output token costs.

Which model performs better on benchmarks?

GPT-5.1 (high) wins 2 out of 12 benchmarks compared to 0 for Gemini 2.5 Pro. See the detailed benchmark chart above for per-category results.

Which is faster for real-time applications?

Gemini 2.5 Pro generates tokens faster at 133 tok/s vs 112 tok/s. However, Gemini 2.5 Pro has lower time-to-first-token (20.46s vs 28.41s).

When should I use GPT-5.1 (high) vs Gemini 2.5 Pro?

Choose based on your priorities: both are similarly priced, GPT-5.1 (high) for stronger benchmark performance, and Gemini 2.5 Pro for faster generation. For latency-sensitive apps, check the TTFT comparison above.