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Head-to-Head Model Comparison

o4-mini-deep-research vs Gemini Deep Research

Benchmarks, API Token Pricing, Context Window & Speed Comparison

GetInfoUs araştırma ekibi tarafından incelendiSon inceleme: October 2026Yayın ilkeleri
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AI CompareAI BenchmarkToken PricingModel CostModel SpecsSWE-bench CodingModel VersusWhich AI ModelLLM Speed & LatencyReasoning ModelsExtended ThinkingPrompt Caching ROI
o4-mini-deep-research vs Gemini Deep Research: Benchmarks, Pricing & Speed Comparison

OpenAI tarafından geliştirilen o4-mini-deep-research ve Google tarafından sunulan Gemini Deep Research, kendi sınıflarının öne çıkan yapay zeka modelleridir. o4-mini-deep-research, 200K token bağlam penceresi ve 1M token başına $2.00/$8.00 fiyat sunarken; Gemini Deep Research, 1.05M token bağlam penceresi ve $10.00/$40.00 fiyatla gelir. Aşağıda tüm benchmark, hız ve maliyet detaylarını inceleyebilirsiniz.

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OpenAI

o4-mini-deep-research

Derin Akıl Yürütme Motoru

OpenAI tarafından geliştirilen o4-mini-deep-research; derin mantıksal akıl yürütme, ileri matematik ve çok adımlı bilimsel analiz için tasarlanmış olup 200K bağlam penceresi, 70 token/sn hız, 48/100 zeka indeksi ve 1M token başına $2/$8 fiy

Intelligence Index48 / 100
Input Token:

$2.00 / 1M

Output Token:

$8.00 / 1M

Context Window:

200K tokens

SWE-bench Verified:

48.5%

Google

Gemini Deep Research

Otonom Ajan ve Araç Modeli

Google tarafından geliştirilen Gemini Deep Research; otonom ajan iş akışları, araç çağırma (tool calling) ve çok adımlı otomasyon için tasarlanmış olup 1.0M bağlam penceresi, 60 token/sn hız, 91/100 zeka indeksi ve 1M token başına $10/$40 f

Intelligence Index91 / 100
Input Token:

$10.00 / 1M

Output Token:

$40.00 / 1M

Context Window:

1.05M tokens

SWE-bench Verified:

N/A

Bir Bakışta Temel Farklar

  • o4-mini-deep-research is 5.0x cheaper for API usage (input + output tokens combined).
  • Gemini Deep Research has a larger context window (1M vs 200K tokens).
  • o4-mini-deep-research is faster at 70 tok/s vs 60 tok/s.
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
Featureo4-mini-deep-researchGemini Deep Research
Intelligence Index
Composite reasoning & knowledge score (0-100)
4891
Provider
OpenAIGoogle
Input Price
Cost per million input tokens
$2.00 / 1M$10.00 / 1M
Output Price
Cost per million output tokens
$8.00 / 1M$40.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$1.55 / 1M$7.75 / 1M
Context Window
Maximum input + output tokens
200K tokens~300 A4 pages of text1.05M tokens~1,573 A4 pages of text
Max Output Tokens
Per single request
100K66K
Throughput Speed
Tokens generated per second
70 tok/s60 tok/s
SWE-bench Verified
Real-world software engineering
48.5%N/A
GPQA Diamond
Graduate-level reasoning
68%85%
Cached Input Price
Prompt caching discount per 1M tokens
$0.50 / 1M$2.50 / 1M

Hangi Alanda Kim Kazanıyor?

At-a-glance decision framework
Coding

Evaluations ongoing

Cost
o4-mini-deep-research
5.0x cheaper monthly runtime
Speed
o4-mini-deep-research
+17% faster generation
Context
Gemini Deep Research
1.05M tokens window

Doğrulanmış Benchmark Puanları

Official evaluation metrics verified by independent third-party research labs.

o4-mini-deep-researchGemini Deep Research
SWE-bench Verified (Autonomous Coding)

Industry benchmark evaluating real-world GitHub issue resolution and multi-file debugging.

48.5%vsN/A
GPQA Diamond (Doctorate-Level Science & Math)

Challenging questions created by domain experts to test complex PhD-level reasoning.

68%vs85%
MMLU-Pro (Multi-task Language Understanding)

Hardened reasoning and academic knowledge benchmark with reduced lucky-guess probability.

80.5%vs89.5%
LMSYS Chatbot Arena Elo

Crowdsourced human preference evaluation based on blind, head-to-head model battles.

1318ptsvs1495pts
Humanity's Last Exam (Frontier Expert Knowledge)

Extremely difficult, closed-ended questions spanning the frontier of human expert knowledge.

11.8%vs17.5%
Terminal-Bench (Agentic Coding & Terminal Use)

Autonomous multi-step tasks executed inside a real command-line terminal environment.

33.5%vsN/A
SciCode (Scientific Computing)

Research-grade coding problems drawn from real scientific and numerical workloads.

35%vsN/A
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

60%vsN/A
AIME (Advanced Math Competition)

American Invitational Mathematics Examination — multi-step Olympiad-level reasoning.

85%vsN/A
Long-Context Reasoning

Accuracy when reasoning over very large inputs that fill the model context window.

76%vsN/A
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

70 tok/s vs60 tok/s

Gecikme Süresi ve Yanıt Hızı

Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.

Time to First Token (TTFT)Lower is better
o4-mini-deep-research2.40s
Gemini Deep Research1.50s
Est. End-to-End Response (500 tokens)TTFT + generation time
o4-mini-deep-research9.54s
Gemini Deep Research9.83s

Gerçek Zamanlı Token Maliyet Simülatörü

Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.

100K / day
10K500K1M
30K / day
5K150K300K
50% cached
0% (Cold)50%90% (Warm)
o4-mini-deep-research Monthly API Bill
$10.95 / month
$2/1M in · $8/1M out
Gemini Deep Research Monthly API Bill
$54.75 / month
$10/1M in · $40/1M out
o4-mini-deep-research saves approximately $43.80 / month (80%) under this workload.5.0x Savings

o4-mini-deep-research · Strengths & Key Advantages

  • 200K bağlam penceresi ve yanıt başına maksimum 100K çıktı tokenı kapasitesi (SWE-bench Verified 48.5% · GPQA Diamond 68%)
  • Sadece 2400 ms ilk token gecikmesi (TTFT) ile saniyede 70 token yüksek üretim hızı
  • İstem önbellekleme (Prompt Caching), araç çağırma ve yapılandırılmış JSON çıktısını destekleyen rekabetçi API ekonomisi (1M token başına $2/$8 fiyatlandırma)
Considerations & Trade-offs
  • Kapalı ağırlıklı bulut modelidir; çevrimdışı yerel sunuculara indirilerek çalıştırılamaz
  • Yüksek hacimli üretim trafiğinde maliyetleri optimize etmek için Prompt Caching ve Batch API kullanımı önerilir

Gemini Deep Research · Strengths & Key Advantages

  • 1.0M bağlam penceresi ve yanıt başına maksimum 66K çıktı tokenı kapasitesi (GPQA Diamond 85% · MMLU-Pro 89.5%)
  • Sadece 1500 ms ilk token gecikmesi (TTFT) ile saniyede 60 token yüksek üretim hızı
  • İstem önbellekleme (Prompt Caching), araç çağırma ve yapılandırılmış JSON çıktısını destekleyen rekabetçi API ekonomisi (1M token başına $10/$40 fiyatlandırma)
Considerations & Trade-offs
  • Kapalı ağırlıklı bulut modelidir; çevrimdışı yerel sunuculara indirilerek çalıştırılamaz
  • Yüksek hacimli üretim trafiğinde maliyetleri optimize etmek için Prompt Caching ve Batch API kullanımı önerilir

Token Use & Task Economics

Estimated cost and token consumption to complete one representative agentic task.

Metrico4-mini-deep-researchGemini Deep Research
Cost per Task
Estimated USD to finish one task
$1.10$8.50
Output Tokens / Task
Tokens generated per task
75K50K
Reasoning Tokens / Task
Thinking tokens burned per task
30K35K

Teknik Özellikler

Architecture, release timeline, capabilities, and modalities.

Featureo4-mini-deep-researchGemini Deep Research
Official API Model ID (SDK)o4-mini-deep-researchmodels/gemini-deep-research
API ProtocolOpenAI Responses API & Chat Completions v1Google Gemini API (generateContent) + OpenAI-Compatible SDK
Release Date2025-062026-04
Knowledge CutoffJune 2024Real-time Google Search Integration
ArchitectureCompact agentic reasoning transformerAgentic recursive research and synthesis engine
ParametersConfidentialConfidential
Enterprise Rate Limits (RPM / TPM)10,000 – 30,000 RPM (Tier 5 Enterprise) · 800,000 – 2,000,000 TPM10,000 – 30,000 RPM (Tier 5 Enterprise) · 4,000,000 – 10,000,000 TPM
Long-Context Tier (>128K/200K)Flat rate ($2/1M in) across full 200K windowStandard rate up to 200K tokens; 2x input/output tier above 200K tokens
Prompt Cache Policy & TTLAutomatic prefix caching at $0.5/1M (no extra cache-write fee)Implicit + Explicit Context Caching at $2.5/1M with configurable TTL
Computer Use / GUI AgentSupported (Screen coordinate grounding, browser & desktop GUI action loops)Supported (Screen coordinate grounding, browser & desktop GUI action loops)
MCP & Parallel Tool CallingNative MCP Client/Server ready · Parallel function calling · 100% Strict JSON SchemaNative MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema
Web Search Grounding & SandboxNative Web Search tool + Hosted Code Interpreter & File Search RAGBuilt-in Google Search Grounding + Managed Python Code Execution Sandbox
Official Fine-Tuning SupportSupervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT)Vertex AI Supervised Adapter Tuning & Context Distillation
Multimodal Token BillingText BPE (~4 chars/token) · Vision (~258–765 tokens per image tile)Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile)
Quantization & Min GPU VRAMCloud-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 ClassificationOpenAI Preparedness Framework Audited & System Card PublishedGoogle DeepMind Frontier Safety Framework Verified
Enterprise Compliance (ZDR/HIPAA/SOC2)SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise TierSOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier
Input Modalitiestext, visiontext, vision
Output Modalitiestexttext

o4-mini-deep-research vs Gemini Deep Research: Hızlı Yanıtlar (SSS)

Which is more intelligent, o4-mini-deep-research or Gemini Deep Research?

Gemini Deep Research is more intelligent. It scores 91 compared with 48 on the composite Intelligence Index.

Which model is faster?

o4-mini-deep-research is faster, generating 70 tokens per second compared with 60 tokens per second.

Which model is cheaper to run?

o4-mini-deep-research is cheaper at $1.55 per 1M tokens blended, compared with $7.75 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Gemini Deep Research has lower latency, with a time to first token of 1.50s compared with 2.40s.

Which model has a larger context window?

Gemini Deep Research has a larger context window, supporting 1.05M tokens compared with 200K tokens.

Sonuç

Hem o4-mini-deep-research (derin mantıksal akıl yürütme, ileri matematik ve çok adımlı bilimsel analiz, kurumsal RAG mimarileri ve ölçeklenebilir üretim API entegrasyonları için idealdir.) hem de Gemini Deep Research (otonom ajan iş akışları, araç çağırma (tool calling) ve çok adımlı otomasyon, kurumsal RAG mimarileri ve ölçeklenebilir üretim API entegrasyonları için idealdir.) güçlü üretim seçenekleridir: Gemini Deep Research karmaşık akıl yürütme ve kodlama testlerinde öne çıkarken, o4-mini-deep-research daha yüksek üretim hızı sağlar; o4-mini-deep-research ise yüksek hacimli API kullanımlarında daha ekonomiktir.

Sıkça Sorulan Sorular (SSS)

Kodlama ve akıl yürütme için o4-mini-deep-research mi yoksa Gemini Deep Research mi daha iyi?+

Bileşik zeka endeksi ve yazılım testlerinde Gemini Deep Research önde yer alıyor. Detaylı karşılaştırma için yukarıdaki SWE-bench ve GPQA tablolarına göz atabilirsiniz.

o4-mini-deep-research ve Gemini Deep Research API fiyatları nasıl karşılaştırılır?+

o4-mini-deep-research 1M giriş/çıkış tokeni başına $2.00 / $8.00 ücretlendirilirken, Gemini Deep Research $10.00 / $40.00 seviyesindedir. Karma maliyette o4-mini-deep-research daha avantajlıdır.

Hangi modelin bağlam penceresi daha geniş ve hızı daha yüksek?+

o4-mini-deep-research 200K token bağlam penceresi sunarken Gemini Deep Research 1.05M token kapasiteye sahiptir. Saniyedeki token üretim hızında ise o4-mini-deep-research öndedir.

AI Terminology & Guide
Explore Glossary →

Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.

Tokens & PricingContext WindowAI BenchmarksReasoning ModelsTool CallingModel Context Protocol (MCP)

Related reading

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: OpenAI ve Google resmi API dokümantasyonu, sistem kartları ve bağımsız benchmark testleri (2026).