Gemini 3 Pro vs GPT-5 Pro
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (12)
Gemini 3 Pro by Google and GPT-5 Pro by OpenAI represent two of the frontier AI models analyzed in our comprehensive 2026 AI benchmark and LLM comparison. In this head-to-head evaluation, we examine API token pricing, context window specifications, inference speed (tokens per second), and empirical reasoning performance. From a pure economic perspective, Gemini 3 Pro holds a notable pricing advantage for token ingestion. On output generation, Gemini 3 Pro is more economical per million generated tokens. In data-heavy architectures requiring extensive repository or document analysis, Gemini 3 Pro provides an expanded memory horizon with 2,000K tokens. In latency-sensitive production environments, Gemini 3 Pro leads in tokens-per-second throughput, making it ideal for real-time conversational agents and high-concurrency workflows. Below is the complete empirical head-to-head breakdown across cost, speed, context, and capability matrices.
İstediğiniz Modelleri Seçin ve Karşılaştırın
Select any AI models from our verified benchmark database to generate live side-by-side matrices.
Gemini 3 Pro
Derin Akıl Yürütme ModeliGoogle tarafından geliştirilen Gemini 3 Pro, 2M token bağlam penceresi ve 1M girdi başına $2, 1M çıktı başına $12 API fiyatlandırmasıyla yazılım geliştirme, analiz ve kurumsal otomasyon için tasarlanmıştır.
$2.00 / 1M
$12.00 / 1M
2M tokens
76.2%
GPT-5 Pro
Derin Akıl Yürütme ModeliOpenAI tarafından geliştirilen GPT-5 Pro, 400K token bağlam penceresi ve 1M girdi başına $15, 1M çıktı başına $120 API fiyatlandırmasıyla yazılım geliştirme, analiz ve kurumsal otomasyon için tasarlanmıştır.
$15.00 / 1M
$120.00 / 1M
400K tokens
78.5%
Bir Bakışta Temel Farklar
- Gemini 3 Pro is 9.4x cheaper for API usage (input + output tokens combined).
- Gemini 3 Pro has a larger context window (2M vs 400K tokens).
- Gemini 3 Pro is faster at 118 tok/s vs 55 tok/s.
- GPT-5 Pro leads on SWE-bench coding (78.5% vs 76.2%).
| Feature | Gemini 3 Pro | GPT-5 Pro |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 62 | 62 |
Provider | OpenAI | |
Input Price Cost per million input tokens | $2.00 / 1M | $15.00 / 1M |
Output Price Cost per million output tokens | $12.00 / 1M | $120.00 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $1.74 / 1M | $16.05 / 1M |
Context Window Maximum input + output tokens | 2M tokens~3,000 A4 pages of text | 400K tokens~600 A4 pages of text |
Max Output Tokens Per single request | 66K | 272K |
Throughput Speed Tokens generated per second | 118 tok/s | 55 tok/s |
SWE-bench Verified Real-world software engineering | 76.2% | 78.5% |
GPQA Diamond Graduate-level reasoning | 73.5% | 87.2% |
Cached Input Price Prompt caching discount per 1M tokens | $0.20 / 1M | $1.50 / 1M |
Hangi Alanda Kim Kazanıyor?
At-a-glance decision frameworkDoğrulanmış Benchmark Puanları
Official evaluation metrics verified by independent third-party research labs.
Industry benchmark evaluating real-world GitHub issue resolution and multi-file debugging.
Challenging questions created by domain experts to test complex PhD-level reasoning.
Hardened reasoning and academic knowledge benchmark with reduced lucky-guess probability.
Crowdsourced human preference evaluation based on blind, head-to-head model battles.
Extremely difficult, closed-ended questions spanning the frontier of human expert knowledge.
Autonomous multi-step tasks executed inside a real command-line terminal environment.
Research-grade coding problems drawn from real scientific and numerical workloads.
Contamination-free competitive programming problems collected continuously over time.
American Invitational Mathematics Examination — multi-step Olympiad-level reasoning.
Accuracy when reasoning over very large inputs that fill the model context window.
Tokens emitted per second during active generation streaming.
Gecikme Süresi ve Yanıt Hızı
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
Gerçek Zamanlı Token Maliyet Simülatörü
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
Gemini 3 Pro · Strengths & Key Advantages
- Google imzalı gelişmiş Sparse Multimodal MoE mimarisi ve 2M token bağlam kapasitesi
- Dengeli API maliyeti ($2/1M girdi, $12/1M çıktı) ve yüksek yanıt hızı
- Kod üretimi, mantıksal çıkarım ve çok dilli görevlerde güçlü kıyaslama (benchmark) sonuçları
Considerations & Trade-offs
- Çok uzun bağlamlı sorgularda token maliyetlerinin dikkatli yönetilmesi gerekir
- Alan bazlı özel iş akışlarında en yüksek verim için doğru istem (prompt) tasarımı önerilir
GPT-5 Pro · Strengths & Key Advantages
- OpenAI imzalı gelişmiş Maximum-compute unified reasoning model mimarisi ve 400K token bağlam kapasitesi
- Dengeli API maliyeti ($15/1M girdi, $120/1M çıktı) ve yüksek yanıt hızı
- Kod üretimi, mantıksal çıkarım ve çok dilli görevlerde güçlü kıyaslama (benchmark) sonuçları
Considerations & Trade-offs
- Çok uzun bağlamlı sorgularda token maliyetlerinin dikkatli yönetilmesi gerekir
- Alan bazlı özel iş akışlarında en yüksek verim için doğru istem (prompt) tasarımı önerilir
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | Gemini 3 Pro | GPT-5 Pro |
|---|---|---|
Cost per Task Estimated USD to finish one task | $2.40 | $20.40 |
Output Tokens / Task Tokens generated per task | 60K | 72K |
Reasoning Tokens / Task Thinking tokens burned per task | 31K | 48K |
Teknik Özellikler
Architecture, release timeline, capabilities, and modalities.
| Feature | Gemini 3 Pro | GPT-5 Pro |
|---|---|---|
| Official API Model ID (SDK) | models/gemini-3-pro | gpt-5-pro |
| API Protocol | Google Gemini API (generateContent) + OpenAI-Compatible SDK | OpenAI Responses API & Chat Completions v1 |
| Release Date | 2025-11 | 2025-10 |
| Knowledge Cutoff | January 2025 | September 2024 |
| Architecture | Sparse Multimodal MoE | Maximum-compute unified reasoning model |
| Parameters | Confidential | Confidential |
| Enterprise Rate Limits (RPM / TPM) | 10,000 – 30,000 RPM (Tier 5 Enterprise) · 4,000,000 – 10,000,000 TPM | 10,000 – 30,000 RPM (Tier 5 Enterprise) · 800,000 – 2,000,000 TPM |
| Long-Context Tier (>128K/200K) | Standard rate up to 200K tokens; 2x input/output tier above 200K tokens | Flat rate ($15/1M in) across full 400K window |
| Prompt Cache Policy & TTL | Implicit + Explicit Context Caching at $0.2/1M with configurable TTL | Automatic prefix caching at $1.5/1M (no extra cache-write fee) |
| Computer Use / GUI Agent | Supported (Screen coordinate grounding, browser & desktop GUI action loops) | Supported (Screen coordinate grounding, browser & desktop GUI action loops) |
| MCP & Parallel Tool Calling | Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema | Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema |
| Web Search Grounding & Sandbox | Built-in Google Search Grounding + Managed Python Code Execution Sandbox | Native Web Search tool + Hosted Code Interpreter & File Search RAG |
| Official Fine-Tuning Support | Vertex AI Supervised Adapter Tuning & Context Distillation | Supervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT) |
| Multimodal Token Billing | Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) · Audio (~25–32 tokens/sec) · Video (~258–300 tokens/sec) | Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) |
| Quantization & Min GPU VRAM | Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API) | Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API) |
| Safety & Frontier Classification | Google DeepMind Frontier Safety Framework Verified | OpenAI Preparedness Framework Audited & System Card Published |
| Enterprise Compliance (ZDR/HIPAA/SOC2) | SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier | SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier |
| Input Modalities | text, vision, audio, video | text, vision |
| Output Modalities | text | text |
Gemini 3 Pro vs GPT-5 Pro: Hızlı Yanıtlar (SSS)
Which model is faster?
Gemini 3 Pro is faster, generating 118 tokens per second compared with 55 tokens per second.
Which model is cheaper to run?
Gemini 3 Pro is cheaper at $1.74 per 1M tokens blended, compared with $16.05 (7:2:1 cache:input:output ratio).
Which model has lower latency?
Gemini 3 Pro has lower latency, with a time to first token of 1.80s compared with 4.20s.
Which model has a larger context window?
Gemini 3 Pro has a larger context window, supporting 2M tokens compared with 400K tokens.
Sonuç
Verdict & Model Selection Recommendation: Choose Gemini 3 Pro if your priority is Long-document analysis, full-codebase reasoning, and multimodal tasks needing 500K+ tokens. Its performance in demanding tasks justifies its operational token cost. Choose GPT-5 Pro if your workflow prioritizes High-value, low-volume analysis and code review. For large-scale batch processing or customer-facing conversational interfaces, its balance of speed and economics delivers superior ROI.
Sıkça Sorulan Sorular (SSS)
How does Gemini 3 Pro compare to GPT-5 Pro in API token pricing and cost per token?+
Gemini 3 Pro costs $2.00 per 1M input tokens and $12.00 per 1M output tokens, whereas GPT-5 Pro costs $15.00 input and $120.00 output. Overall, Gemini 3 Pro is the more cost-effective model for high-volume API pipelines. Both models support prompt caching discounts of up to 90% for repeated prompt prefixes.
Which model has a larger context window: Gemini 3 Pro or GPT-5 Pro?+
Gemini 3 Pro supports a context window of 2,000K tokens (~1,500k words), while GPT-5 Pro supports 400K tokens (~300k words). Therefore, Gemini 3 Pro can process more textual data and document context in a single prompt.
Which AI model is better for software engineering and coding: Gemini 3 Pro or GPT-5 Pro?+
Gemini 3 Pro scores 76.2% on SWE-bench Verified while GPT-5 Pro scores 78.5%. For autonomous software engineering and multi-file debugging, GPT-5 Pro holds the verified benchmark lead.
What is the difference in reasoning capability and extended thinking between Gemini 3 Pro and GPT-5 Pro?+
Gemini 3 Pro features native chain-of-thought extended thinking mode with configurable reasoning effort. In contrast, GPT-5 Pro provides chain-of-thought reasoning depth for complex math and science.
How does inference speed (tokens per second) compare between Gemini 3 Pro and GPT-5 Pro?+
Gemini 3 Pro generates approximately 118 tokens per second, while GPT-5 Pro delivers 55 tokens per second. In latency-sensitive production environments, Gemini 3 Pro provides faster time-to-first-token (TTFT) and higher streaming response velocity.
Can you implement a tiered LLM routing setup combining Gemini 3 Pro and GPT-5 Pro to optimize costs?+
Yes! High-efficiency architectures route high-frequency routine classification and conversational tasks to Gemini 3 Pro to save operational costs, and dynamically escalate complex architectural queries or reasoning tasks to GPT-5 Pro. This tiered routing pattern cuts overall API bills by up to 70%.
Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.
Related reading
- Claude Fable 5.1 vs Gemini 3 Pro: Benchmarks, Pricing & Speed ComparisonKarşılaştır
- Gemini 3 Flash vs Gemini 3 Pro: Benchmarks, Pricing & Speed ComparisonKarşılaştır
- Gemini 3 Pro vs GPT-5.1: Benchmarks, Pricing & Speed ComparisonKarşılaştır
- GPT-5.1 Chat vs Gemini 3 Pro: Benchmarks, Pricing & Speed ComparisonKarşılaştır
- GPT-5.1 Chat vs GPT-5 Pro: Benchmarks, Pricing & Speed ComparisonKarşılaştır
- GPT-5 Pro vs Claude Opus 5: Benchmarks, Pricing & Speed ComparisonKarşılaştır
Benchmark scores, token prices, and rate limits evolve rapidly as AI labs release model updates. Always verify current specifications and pricing on the official provider documentation.
Resmi kaynaklar: GetInfoUs Independent AI Benchmarks & Official API Specs