Gemini 3.5 Flash-Lite vs GPT-6 Astra
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (4)
Compare Gemini 3.5 Flash-Lite by Google against GPT-6 Astra by OpenAI across real-world coding, reasoning, token economics, and latency.
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Gemini 3.5 Flash-Lite
Модель глубокого рассужденияGemini 3.5 Flash-Lite от Google — передовая модель искусственного интеллекта с контекстным окном 1.0M токенов и стоимостью API $0.4/1M входящих и $2/1M исходящих токенов для программирования, аналитики и автоматизации.
$0.40 / 1M
$2.00 / 1M
1.05M tokens
N/A
GPT-6 Astra
Модель глубокого рассужденияGPT-6 Astra от OpenAI — передовая модель искусственного интеллекта с контекстным окном 1M токенов и стоимостью API $10.0/1M входящих и $50.0/1M исходящих токенов для программирования, аналитики и автоматизации.
$10.00 / 1M
$50.00 / 1M
272K tokens
82.4%
Ключевые отличия кратко
- Gemini 3.5 Flash-Lite is 24.1x cheaper for API usage (input + output tokens combined).
- Gemini 3.5 Flash-Lite has a larger context window (1M vs 272K tokens).
- Gemini 3.5 Flash-Lite is faster at 240 tok/s vs 100 tok/s.
| Feature | Gemini 3.5 Flash-Lite | GPT-6 Astra |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 69 | 96 |
Provider | OpenAI | |
Input Price Cost per million input tokens | $0.40 / 1M | $10.00 / 1M |
Output Price Cost per million output tokens | $2.00 / 1M | $50.00 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $0.35 / 1M | $7.70 / 1M |
Context Window Maximum input + output tokens | 1.05M tokens~1,573 A4 pages of text | 272K tokens~408 A4 pages of text |
Max Output Tokens Per single request | 33K | 128K |
Throughput Speed Tokens generated per second | 240 tok/s | 100 tok/s |
SWE-bench Verified Real-world software engineering | N/A | 82.4% |
GPQA Diamond Graduate-level reasoning | N/A | 80.9% |
Cached Input Price Prompt caching discount per 1M tokens | $0.10 / 1M | $1.00 / 1M |
Кто лидирует в каждой категории?
At-a-glance decision frameworkEvaluations ongoing
Результаты проверенных бенчмарков
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.
Задержка и скорость ответа
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
Интерактивный калькулятор стоимости токенов
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
Gemini 3.5 Flash-Lite · Strengths & Key Advantages
- Современная архитектура Lightweight efficient multimodal transformer от Google с поддержкой до 1.0M токенов контекста
- Оптимальная стоимость использования ($0.4/1M вход, $2/1M выход) и высокая скорость генерации
- Высокие результаты в задачах написания кода, логического мышления и многоязычной обработки
Considerations & Trade-offs
- При работе с максимальным контекстом требуется контроль расхода токенов
- Для узкоспециализированных задач рекомендуется точная настройка системных промптов
GPT-6 Astra · Strengths & Key Advantages
- Современная архитектура Omni-Adaptive Autoregressive with Dynamic CoT от OpenAI с поддержкой до 1M токенов контекста
- Оптимальная стоимость использования ($10.0/1M вход, $50.0/1M выход) и высокая скорость генерации
- Высокие результаты в задачах написания кода, логического мышления и многоязычной обработки
Considerations & Trade-offs
- При работе с максимальным контекстом требуется контроль расхода токенов
- Для узкоспециализированных задач рекомендуется точная настройка системных промптов
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | Gemini 3.5 Flash-Lite | GPT-6 Astra |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.55 | $2.15 |
Output Tokens / Task Tokens generated per task | 18K | 58K |
Reasoning Tokens / Task Thinking tokens burned per task | 7K | 32K |
Технические характеристики
Architecture, release timeline, capabilities, and modalities.
| Feature | Gemini 3.5 Flash-Lite | GPT-6 Astra |
|---|---|---|
| Official API Model ID (SDK) | models/gemini-3-5-flash-lite | gpt-6-astra |
| API Protocol | Google Gemini API (generateContent) + OpenAI-Compatible SDK | OpenAI Responses API & Chat Completions v1 |
| Release Date | 2026-07 | 2026-09 |
| Knowledge Cutoff | March 2026 | June 2026 |
| Architecture | Lightweight efficient multimodal transformer | Omni-Adaptive Autoregressive with Dynamic CoT |
| 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 ($10/1M in) across full 272K window |
| Prompt Cache Policy & TTL | Implicit + Explicit Context Caching at $0.1/1M with configurable TTL | Automatic prefix caching at $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) | Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) · Audio (~25–32 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 | 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 | text, vision, audio |
| Output Modalities | text | text, audio |
Gemini 3.5 Flash-Lite vs GPT-6 Astra: Быстрые ответы (FAQ)
Which is more intelligent, Gemini 3.5 Flash-Lite or GPT-6 Astra?
GPT-6 Astra is more intelligent. It scores 96 compared with 69 on the composite Intelligence Index.
Which model is faster?
Gemini 3.5 Flash-Lite is faster, generating 240 tokens per second compared with 100 tokens per second.
Which model is cheaper to run?
Gemini 3.5 Flash-Lite is cheaper at $0.35 per 1M tokens blended, compared with $7.70 (7:2:1 cache:input:output ratio).
Which model has lower latency?
Gemini 3.5 Flash-Lite has lower latency, with a time to first token of 0.29s compared with 0.95s.
Which model has a larger context window?
Gemini 3.5 Flash-Lite has a larger context window, supporting 1.05M tokens compared with 272K tokens.
Вердикт
Choose Gemini 3.5 Flash-Lite for корпоративной автоматизации, разработки по, ии-агентов и продуктовых решений на базе google, or choose GPT-6 Astra for корпоративной автоматизации, разработки по, ии-агентов и продуктовых решений на базе openai.
Часто задаваемые вопросы (FAQ)
Which is cheaper: Gemini 3.5 Flash-Lite or GPT-6 Astra?+
Gemini 3.5 Flash-Lite costs $0.4/1M input and $2/1M output tokens, while GPT-6 Astra costs $10/1M input and $50/1M output tokens.
Which model has a larger context window: Gemini 3.5 Flash-Lite or GPT-6 Astra?+
Gemini 3.5 Flash-Lite supports 1.0M tokens whereas GPT-6 Astra supports 272K 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.
Официальные источники: Google & OpenAI Official Documentation