Pairwise benchmark snapshot · Aug 17, 2026
In this head-to-head showdown, OpenAI: o1 delivers higher overall intelligence and human-preferred responses (Elo 1,512 vs 1,350), while Gemini 2.5 Pro leads in SWE-bench software engineering benchmarks (63.8%), while Gemini 2.5 Pro is more budget-friendly at $10/1M per 1M output tokens. Review the complete breakdown below to determine which model best fits your performance and budget requirements.
9 direct benchmark disciplines evaluated across capability, speed, and cost
Auto-discovered from OpenRouter (openai/o1). Preview until a second source matches.
Simulate accuracy gains vs added response time & token cost
Reasoning models “think before answering” by generating internal reasoning tokens. Higher effort improves math, coding, and logic accuracy, but increases response delay and token costs.
Δ 162 Arena Elo pts
95 tok/s
$10 / 1M output
Relative percentile scores computed across all active models in the benchmark catalog.
Comparing top Western standard models with China's leading frontier rival across 6 skill dimensions. Tap any spoke or dot to inspect.
Category wins across reasoning intelligence, generation speed, and token cost.
Preference Elo, Coding proficiency, SWE-bench & LiveBench accuracy
Generation throughput and time to first token responsiveness
Cost per million tokens and max context window length
| Benchmark | Gemini 2.5 Pro | OpenAI: o1 | Advantage Delta |
|---|---|---|---|
| Preference Elo | +162 | ||
| Coding Elo | — | — | |
| LiveBench | +8.3% | ||
| SWE-bench | +14.9% | ||
| GPQA Diamond | +1.6% | ||
| Time to first token | +210 ms | ||
| Output speed | 95 tok/s | 45 tok/s | +50 tok/s |
| Input price | $1.25/1M | +$13.75/1M | |
| Output price | +$50/1M | ||
| Context window | +849k |
Simulate monthly production API costs in USD (US Dollar).
Gemini 2.5 Pro is estimated to save $1,231.25/month ($14,775/year).
Higher SWE-bench (63.8%).
Lower output list price ($10/1M).
Lower TTFT (210 ms).
Larger window (1M).
Both accept images. Defaulting to the higher-Elo side (OpenAI: o1).
| Target Workload | Recommended Pick | Evaluation Rationale |
|---|---|---|
| Repo / coding agents | Gemini 2.5 Pro | Higher SWE-bench (63.8%). |
| High-volume chat | Gemini 2.5 Pro | Lower output list price ($10/1M). |
| Voice / low-latency UI | Gemini 2.5 Pro | Lower TTFT (210 ms). |
| Long-document RAG | Gemini 2.5 Pro | Larger window (1M). |
| Screenshots / vision | OpenAI: o1 | Both accept images. Defaulting to the higher-Elo side (OpenAI: o1). |
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