Gemini 1.5 Flash vs GPT-6.1 Sol
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (4)
Compare Gemini 1.5 Flash by Google against GPT-6.1 Sol by OpenAI across real-world coding, reasoning, token economics, and latency.
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Gemini 1.5 Flash
Ultra Hızlı Düşük GecikmeGoogle tarafından geliştirilen Gemini 1.5 Flash; ultra düşük gecikmeli gerçek zamanlı sohbet ve yüksek hacimli yönlendirme için tasarlanmış olup 1.0M bağlam penceresi, 180 token/sn hız, 38/100 zeka indeksi ve 1M token başına $0.075/$0.3 fiy
$0.07 / 1M
$0.30 / 1M
1.05M tokens
20%
GPT-6.1 Sol
Amiral Gemisi Öncü ModelOpenAI tarafından geliştirilen GPT-6.1 Sol; öncü kurumsal akıl yürütme, yazılım geliştirme ve üretim ölçekli AI iş akışları için tasarlanmış olup 1M bağlam penceresi, 120 token/sn hız, 94/100 zeka indeksi ve 1M token başına $2/$10 fiyatland
$2.00 / 1M
$10.00 / 1M
1M tokens
82.3%
Bir Bakışta Temel Farklar
- Gemini 1.5 Flash is 29.6x cheaper for API usage (input + output tokens combined).
- Gemini 1.5 Flash has a larger context window (1M vs 1M tokens).
- Gemini 1.5 Flash is faster at 180 tok/s vs 120 tok/s.
- GPT-6.1 Sol leads on SWE-bench coding (82.3% vs 20.0%).
| Feature | Gemini 1.5 Flash | GPT-6.1 Sol |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 38 | 94 |
Provider | OpenAI | |
Input Price Cost per million input tokens | $0.07 / 1M | $2.00 / 1M |
Output Price Cost per million output tokens | $0.30 / 1M | $10.00 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $0.06 / 1M | $1.47 / 1M |
Context Window Maximum input + output tokens | 1.05M tokens~1,573 A4 pages of text | 1M tokens~1,500 A4 pages of text |
Max Output Tokens Per single request | 8K | 128K |
Throughput Speed Tokens generated per second | 180 tok/s | 120 tok/s |
SWE-bench Verified Real-world software engineering | 20% | 82.3% |
GPQA Diamond Graduate-level reasoning | 42.1% | 80.8% |
Cached Input Price Prompt caching discount per 1M tokens | $0.02 / 1M | $0.10 / 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 1.5 Flash · Strengths & Key Advantages
- 1.0M bağlam penceresi ve yanıt başına maksimum 8K çıktı tokenı kapasitesi (SWE-bench Verified 20% · GPQA Diamond 42.1%)
- Sadece 320 ms ilk token gecikmesi (TTFT) ile saniyede 180 token yüksek üretim hızı
- İstem önbellekleme (Prompt Caching), araç çağırma ve yapılandırılmış JSON çıktısını destekleyen rekabetçi API ekonomisi (1M token başına $0.075/$0.3 fiyatlandırma)
Considerations & Trade-offs
- Kapalı ağırlıklı bulut modelidir; çevrimdışı yerel sunuculara indirilerek çalıştırılamaz
- Çok karmaşık akademik ve bilimsel çıkarımlarda üst düzey ağır akıl yürütme modelleri daha derin sonuçlar verebilir
GPT-6.1 Sol · Strengths & Key Advantages
- 1M bağlam penceresi ve yanıt başına maksimum 128K çıktı tokenı kapasitesi (SWE-bench Verified 82.3% · GPQA Diamond 80.8%)
- Sadece 1120 ms ilk token gecikmesi (TTFT) ile saniyede 120 token yüksek üretim hızı
- İstem önbellekleme (Prompt Caching), araç çağırma ve yapılandırılmış JSON çıktısını destekleyen rekabetçi API ekonomisi (1M token başına $2/$10 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.
| Metric | Gemini 1.5 Flash | GPT-6.1 Sol |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.20 | $2.05 |
Output Tokens / Task Tokens generated per task | 24K | 62K |
Reasoning Tokens / Task Thinking tokens burned per task | 0K | 36K |
Teknik Özellikler
Architecture, release timeline, capabilities, and modalities.
| Feature | Gemini 1.5 Flash | GPT-6.1 Sol |
|---|---|---|
| Official API Model ID (SDK) | models/gemini-1-5-flash | gpt-6-1-sol |
| API Protocol | Google Gemini API (generateContent) + OpenAI-Compatible SDK | OpenAI Responses API & Chat Completions v1 |
| Release Date | 2024-05 | 2026-09 |
| Knowledge Cutoff | May 2024 | April 2026 |
| Architecture | Distilled Sparse MoE Multimodal | Near-Astra 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) · 4,000,000 – 10,000,000 TPM |
| Long-Context Tier (>128K/200K) | Standard rate up to 200K tokens; 2x input/output tier above 200K tokens | Flat rate ($2/1M in) across full 1000K window |
| Prompt Cache Policy & TTL | Implicit + Explicit Context Caching at $0.01875/1M with configurable TTL | Automatic prefix caching at $0.1/1M (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 1.5 Flash vs GPT-6.1 Sol: Hızlı Yanıtlar (SSS)
Which is more intelligent, Gemini 1.5 Flash or GPT-6.1 Sol?
GPT-6.1 Sol is more intelligent. It scores 94 compared with 38 on the composite Intelligence Index.
Which model is faster?
Gemini 1.5 Flash is faster, generating 180 tokens per second compared with 120 tokens per second.
Which model is cheaper to run?
Gemini 1.5 Flash is cheaper at $0.06 per 1M tokens blended, compared with $1.47 (7:2:1 cache:input:output ratio).
Which model has lower latency?
Gemini 1.5 Flash has lower latency, with a time to first token of 0.32s compared with 1.12s.
Which model has a larger context window?
Gemini 1.5 Flash has a larger context window, supporting 1.05M tokens compared with 1M tokens.
Sonuç
Choose Gemini 1.5 Flash for ultra düşük gecikmeli gerçek zamanlı sohbet ve yüksek hacimli yönlendirme, kurumsal rag mimarileri ve ölçeklenebilir üretim api entegrasyonları için idealdir., or choose GPT-6.1 Sol for öncü kurumsal akıl yürütme, yazılım geliştirme ve üretim ölçekli ai iş akışları, kurumsal rag mimarileri ve ölçeklenebilir üretim api entegrasyonları için idealdir..
Sıkça Sorulan Sorular (SSS)
Which is cheaper: Gemini 1.5 Flash or GPT-6.1 Sol?+
Gemini 1.5 Flash costs $0.075/1M input and $0.3/1M output tokens, while GPT-6.1 Sol costs $2/1M input and $10/1M output tokens.
Which model has a larger context window: Gemini 1.5 Flash or GPT-6.1 Sol?+
Gemini 1.5 Flash supports 1.0M tokens whereas GPT-6.1 Sol supports 1M tokens.
Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.
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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: Google & OpenAI Official Documentation