Gemini 3.5 Flash-Lite vs Grok 4.6
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (12)
Gemini 3.5 Flash-Lite da Google e Grok 4.6 da xAI são dois modelos de IA de destaque. O Gemini 3.5 Flash-Lite oferece uma janela de contexto de 1.05M tokens a $0.40/$2.00 por milhão de tokens, enquanto o Grok 4.6 oferece 500K tokens de contexto a $2.00/$6.00 por milhão de tokens. Veja abaixo a comparação completa de benchmarks, latência e custos.
Troque e Compare Qualquer Modelo
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Gemini 3.5 Flash-Lite
Inferência UltrarrápidaO Gemini 3.5 Flash-Lite da Google é um modelo de IA projetado para respostas em tempo real com latência ultrabaixa e roteamento de alto volume, oferecendo janela de contexto de 1.0M, velocidade de 240 tokens/s, índice de inteligência de 69/
$0.40 / 1M
$2.00 / 1M
1.05M tokens
N/A
Grok 4.6
Modelo Principal de FronteiraO Grok 4.6 da xAI é um modelo de IA projetado para raciocínio corporativo de fronteira, programação avançada e cargas de produção, oferecendo janela de contexto de 500K, velocidade de 115 tokens/s, índice de inteligência de 77/100 e tarifa
$2.00 / 1M
$6.00 / 1M
500K tokens
75.8%
Principais Diferenças em Resumo
- Gemini 3.5 Flash-Lite is 3.6x cheaper for API usage (input + output tokens combined).
- Gemini 3.5 Flash-Lite has a larger context window (1M vs 500K tokens).
- Gemini 3.5 Flash-Lite is faster at 240 tok/s vs 115 tok/s.
| Feature | Gemini 3.5 Flash-Lite | Grok 4.6 |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 69 | 77 |
Provider | xAI | |
Input Price Cost per million input tokens | $0.40 / 1M | $2.00 / 1M |
Output Price Cost per million output tokens | $2.00 / 1M | $6.00 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $0.35 / 1M | $1.35 / 1M |
Context Window Maximum input + output tokens | 1.05M tokens~1,573 A4 pages of text | 500K tokens~750 A4 pages of text |
Max Output Tokens Per single request | 33K | 66K |
Throughput Speed Tokens generated per second | 240 tok/s | 115 tok/s |
SWE-bench Verified Real-world software engineering | N/A | 75.8% |
GPQA Diamond Graduate-level reasoning | N/A | 77.2% |
Cached Input Price Prompt caching discount per 1M tokens | $0.10 / 1M | $0.50 / 1M |
Quem vence em cada categoria?
At-a-glance decision frameworkEvaluations ongoing
Pontuações de Benchmarks Verificadas
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.
Latência e Tempo de Resposta
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
Simulador Interativo de Custo de Tokens
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
Gemini 3.5 Flash-Lite · Strengths & Key Advantages
- Janela de contexto de 1.0M com limite máximo de saída de 33K tokens (MMLU-Pro 81.2% · Arena Elo 1375)
- Taxa de transferência rápida de 240 tokens/segundo com latência inicial (TTFT) de 290 ms
- Economia de API competitiva ($0.4/$2 por 1M de tokens) com suporte a cache de prompts e saídas JSON estruturadas
Considerations & Trade-offs
- Modelo proprietário em nuvem; não permite download dos pesos para execução local offline
- Em derivações científicas extremas, modelos pesados dedicados exclusivamente ao raciocínio oferecem maior profundidade
Grok 4.6 · Strengths & Key Advantages
- Janela de contexto de 500K com limite máximo de saída de 66K tokens (SWE-bench Verified 75.8% · GPQA Diamond 77.2%)
- Taxa de transferência rápida de 115 tokens/segundo com latência inicial (TTFT) de 580 ms
- Economia de API competitiva ($2/$6 por 1M de tokens) com suporte a cache de prompts e saídas JSON estruturadas
Considerations & Trade-offs
- Modelo proprietário em nuvem; não permite download dos pesos para execução local offline
- Para alto volume de requisições, recomenda-se ativar o cache de prompts e a Batch API para reduzir custos
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | Gemini 3.5 Flash-Lite | Grok 4.6 |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.55 | $0.65 |
Output Tokens / Task Tokens generated per task | 18K | 45K |
Reasoning Tokens / Task Thinking tokens burned per task | 7K | 22K |
Especificações Técnicas
Architecture, release timeline, capabilities, and modalities.
| Feature | Gemini 3.5 Flash-Lite | Grok 4.6 |
|---|---|---|
| Official API Model ID (SDK) | models/gemini-3-5-flash-lite | grok-4-6-latest |
| API Protocol | Google Gemini API (generateContent) + OpenAI-Compatible SDK | xAI REST API (OpenAI-Compatible) |
| Release Date | 2026-07 | 2026-08 |
| Knowledge Cutoff | March 2026 | April 2026 |
| Architecture | Lightweight efficient multimodal transformer | 1.5T Colossus Sparse MoE |
| Parameters | Confidential | 1.5T (MoE) |
| Enterprise Rate Limits (RPM / TPM) | 10,000 – 30,000 RPM (Tier 5 Enterprise) · 4,000,000 – 10,000,000 TPM | 5,000 – 15,000 RPM (Production Tier) · 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 ($2/1M in) across full 500K window |
| Prompt Cache Policy & TTL | Implicit + Explicit Context Caching at $0.1/1M with configurable TTL | Cached input at $0.5/1M tokens |
| Computer Use / GUI Agent | Supported (Screen coordinate grounding, browser & desktop GUI action loops) | API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop) |
| 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 | Real-time Web & X (Twitter) Search Grounding + Code Execution |
| Official Fine-Tuning Support | Vertex AI Supervised Adapter Tuning & Context Distillation | API Prompt Engineering & RAG Distillation |
| 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) |
| 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 | xAI Production Safety & Alignment 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 | text, vision |
| Output Modalities | text | text |
Gemini 3.5 Flash-Lite vs Grok 4.6: Respostas Rápidas (FAQ)
Which is more intelligent, Gemini 3.5 Flash-Lite or Grok 4.6?
Grok 4.6 is more intelligent. It scores 77 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 115 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 $1.35 (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 0.58s.
Which model has a larger context window?
Gemini 3.5 Flash-Lite has a larger context window, supporting 1.05M tokens compared with 500K tokens.
Veredito
Tanto Gemini 3.5 Flash-Lite (Indicado para respostas em tempo real com latência ultrabaixa e roteamento de alto volume, arquiteturas RAG corporativas e integração escalável via API.) quanto Grok 4.6 (Indicado para raciocínio corporativo de fronteira, programação avançada e cargas de produção, arquiteturas RAG corporativas e integração escalável via API.) entregam excelente desempenho: Grok 4.6 lidera em inteligência geral e programação, Gemini 3.5 Flash-Lite oferece geração mais rápida e Gemini 3.5 Flash-Lite apresenta o melhor custo-benefício em produção.
Perguntas Frequentes (FAQ)
Qual é melhor para programação e raciocínio, Gemini 3.5 Flash-Lite ou Grok 4.6?+
Nas avaliações de inteligência e código, Grok 4.6 leva vantagem. Confira os gráficos SWE-bench e GPQA acima para detalhes.
Qual modelo tem a API mais barata, Gemini 3.5 Flash-Lite ou Grok 4.6?+
O Gemini 3.5 Flash-Lite custa $0.40 / $2.00 por 1M de tokens (entrada/saída) e o Grok 4.6 custa $2.00 / $6.00. No custo combinado, Gemini 3.5 Flash-Lite é mais econômico.
Qual modelo possui maior janela de contexto e velocidade?+
O Gemini 3.5 Flash-Lite suporta 1.05M tokens de contexto contra 500K tokens do Grok 4.6, enquanto Gemini 3.5 Flash-Lite entrega maior velocidade de geração.
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.
Fontes oficiais: Documentação oficial de API da Google e xAI e benchmarks independentes (2026).