Gemini 3 Flash vs Gemini 3 Pro
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (12)
Gemini 3 Flash by Google and Gemini 3 Pro by Google 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 Flash holds a notable pricing advantage for token ingestion. On output generation, Gemini 3 Flash 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 Flash 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.
بدّل وقارن بين أي نموذجين
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Gemini 3 Flash
نموذج استدلال عميقنموذج Gemini 3 Flash المقدم من Google يوفر نافذة سياق تصل إلى 1.0M رمز، بتكلفة $0.5 لكل مليون رمز إدخال و$3 لكل مليون رمز إخراج، ومصمم للبرمجة والاستدلال وتطبيقات الأعمال.
$0.50 / 1M
$3.00 / 1M
1.05M tokens
66.5%
Gemini 3 Pro
نموذج استدلال عميقنموذج Gemini 3 Pro المقدم من Google يوفر نافذة سياق تصل إلى 2M رمز، بتكلفة $2 لكل مليون رمز إدخال و$12 لكل مليون رمز إخراج، ومصمم للبرمجة والاستدلال وتطبيقات الأعمال.
$2.00 / 1M
$12.00 / 1M
2M tokens
76.2%
أهم الفروقات في لمحة
- Gemini 3 Flash is 3.9x cheaper for API usage (input + output tokens combined).
- Gemini 3 Pro has a larger context window (2M vs 1M tokens).
- Gemini 3 Flash is faster at 180 tok/s vs 118 tok/s.
- Gemini 3 Pro leads on SWE-bench coding (76.2% vs 66.5%).
| Feature | Gemini 3 Flash | Gemini 3 Pro |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 75 | 62 |
Provider | ||
Input Price Cost per million input tokens | $0.50 / 1M | $2.00 / 1M |
Output Price Cost per million output tokens | $3.00 / 1M | $12.00 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $0.49 / 1M | $1.74 / 1M |
Context Window Maximum input + output tokens | 1.05M tokens~1,573 A4 pages of text | 2M tokens~3,000 A4 pages of text |
Max Output Tokens Per single request | 66K | 66K |
Throughput Speed Tokens generated per second | 180 tok/s | 118 tok/s |
SWE-bench Verified Real-world software engineering | 66.5% | 76.2% |
GPQA Diamond Graduate-level reasoning | 79% | 73.5% |
Cached Input Price Prompt caching discount per 1M tokens | $0.13 / 1M | $0.20 / 1M |
من يتفوق في كل مجال؟
At-a-glance decision frameworkنتائج الاختبارات المعيارية الموثقة
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.
زمن الاستجابة والسرعة
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
محاكي تكلفة الرموز التفاعلي
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
Gemini 3 Flash · Strengths & Key Advantages
- بنية Next-gen sparse multimodal mixture-of-experts متطورة من Google مع سعة سياق تبلغ 1.0M رمز
- كفاءة عالية في التكلفة ($0.5/1M إدخال و$3/1M إخراج) وسرعة استجابة ممتازة
- أداء قوي في اختبارات البرمجة، الاستدلال المنطقي، ودعم اللغات المتعددة
Considerations & Trade-offs
- يتطلب إدارة دقيقة لاستهلاك الرموز عند استخدام نافذة السياق الكاملة
- قد يحتاج إلى ضبط دقيق للتعليمات (Prompt Engineering) في المهام التخصصية المعقدة
Gemini 3 Pro · Strengths & Key Advantages
- بنية Sparse Multimodal MoE متطورة من Google مع سعة سياق تبلغ 2M رمز
- كفاءة عالية في التكلفة ($2/1M إدخال و$12/1M إخراج) وسرعة استجابة ممتازة
- أداء قوي في اختبارات البرمجة، الاستدلال المنطقي، ودعم اللغات المتعددة
Considerations & Trade-offs
- يتطلب إدارة دقيقة لاستهلاك الرموز عند استخدام نافذة السياق الكاملة
- قد يحتاج إلى ضبط دقيق للتعليمات (Prompt Engineering) في المهام التخصصية المعقدة
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | Gemini 3 Flash | Gemini 3 Pro |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.95 | $2.40 |
Output Tokens / Task Tokens generated per task | 35K | 60K |
Reasoning Tokens / Task Thinking tokens burned per task | 16K | 31K |
المواصفات التقنية
Architecture, release timeline, capabilities, and modalities.
| Feature | Gemini 3 Flash | Gemini 3 Pro |
|---|---|---|
| Official API Model ID (SDK) | models/gemini-3-flash | models/gemini-3-pro |
| API Protocol | Google Gemini API (generateContent) + OpenAI-Compatible SDK | Google Gemini API (generateContent) + OpenAI-Compatible SDK |
| Release Date | 2025-12 | 2025-11 |
| Knowledge Cutoff | September 2025 | January 2025 |
| Architecture | Next-gen sparse multimodal mixture-of-experts | Sparse Multimodal MoE |
| 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 | Standard rate up to 200K tokens; 2x input/output tier above 200K tokens |
| Prompt Cache Policy & TTL | Implicit + Explicit Context Caching at $0.125/1M with configurable TTL | Implicit + Explicit Context Caching at $0.2/1M with configurable TTL |
| 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 | Built-in Google Search Grounding + Managed Python Code Execution Sandbox |
| Official Fine-Tuning Support | Vertex AI Supervised Adapter Tuning & Context Distillation | Vertex AI Supervised Adapter Tuning & Context Distillation |
| 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) · Audio (~25–32 tokens/sec) · Video (~258–300 tokens/sec) |
| 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 | Google DeepMind Frontier Safety Framework Verified |
| 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, audio, video |
| Output Modalities | text | text |
Gemini 3 Flash vs Gemini 3 Pro: إجابات سريعة (FAQ)
Which is more intelligent, Gemini 3 Flash or Gemini 3 Pro?
Gemini 3 Flash is more intelligent. It scores 75 compared with 62 on the composite Intelligence Index.
Which model is faster?
Gemini 3 Flash is faster, generating 180 tokens per second compared with 118 tokens per second.
Which model is cheaper to run?
Gemini 3 Flash is cheaper at $0.49 per 1M tokens blended, compared with $1.74 (7:2:1 cache:input:output ratio).
Which model has lower latency?
Gemini 3 Flash has lower latency, with a time to first token of 0.40s compared with 1.80s.
Which model has a larger context window?
Gemini 3 Pro has a larger context window, supporting 2M tokens compared with 1.05M tokens.
الحكم النهائي
Verdict & Model Selection Recommendation: Choose Gemini 3 Flash if your priority is Production multimodal software agents and real-time interactive intelligence. Its performance in demanding tasks justifies its operational token cost. Choose Gemini 3 Pro if your workflow prioritizes Long-document analysis, full-codebase reasoning, and multimodal tasks needing 500K+ tokens. For large-scale batch processing or customer-facing conversational interfaces, its balance of speed and economics delivers superior ROI.
الأسئلة الشائعة (FAQ)
How does Gemini 3 Flash compare to Gemini 3 Pro in API token pricing and cost per token?+
Gemini 3 Flash costs $0.50 per 1M input tokens and $3.00 per 1M output tokens, whereas Gemini 3 Pro costs $2.00 input and $12.00 output. Overall, Gemini 3 Flash 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 Flash or Gemini 3 Pro?+
Gemini 3 Flash supports a context window of 1,049K tokens (~786k words), while Gemini 3 Pro supports 2,000K tokens (~1,500k 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 Flash or Gemini 3 Pro?+
Gemini 3 Flash scores 66.5% on SWE-bench Verified while Gemini 3 Pro scores 76.2%. For autonomous software engineering and multi-file debugging, Gemini 3 Pro holds the verified benchmark lead.
What is the difference in reasoning capability and extended thinking between Gemini 3 Flash and Gemini 3 Pro?+
Gemini 3 Flash features native chain-of-thought extended thinking mode with configurable reasoning effort. In contrast, Gemini 3 Pro provides chain-of-thought reasoning depth for complex math and science.
How does inference speed (tokens per second) compare between Gemini 3 Flash and Gemini 3 Pro?+
Gemini 3 Flash generates approximately 180 tokens per second, while Gemini 3 Pro delivers 118 tokens per second. In latency-sensitive production environments, Gemini 3 Flash provides faster time-to-first-token (TTFT) and higher streaming response velocity.
Can you implement a tiered LLM routing setup combining Gemini 3 Flash and Gemini 3 Pro to optimize costs?+
Yes! High-efficiency architectures route high-frequency routine classification and conversational tasks to Gemini 3 Flash to save operational costs, and dynamically escalate complex architectural queries or reasoning tasks to Gemini 3 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
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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.
المصادر الرسمية: GetInfoUs Independent AI Benchmarks & Official API Specs