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 by Google and Grok 4.6 by xAI 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 3.5 Flash-Lite holds a notable pricing advantage for token ingestion. On output generation, Gemini 3.5 Flash-Lite is more economical per million generated tokens. In data-heavy architectures requiring extensive repository or document analysis, Gemini 3.5 Flash-Lite provides an expanded memory horizon with 1,049K tokens. In latency-sensitive production environments, Gemini 3.5 Flash-Lite 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.
Cambia y Compara Cualquier Modelo
Select any AI models from our verified benchmark database to generate live side-by-side matrices.
Gemini 3.5 Flash-Lite
Flash eficientesub-dollar multimodal razonamiento motor tuned para masivo empresarial traffic y en tiempo real subagents.
$0.40 / 1M
$2.00 / 1M
1.05M tokens
N/A
Grok 4.6
Base más grande1.5 billones parámetro Colossus-trained modelo fundacional ofreciendo reinforced codificación y profundo multi-hop razonamiento.
$2.00 / 1M
$6.00 / 1M
500K tokens
75.8%
Diferencias Clave de un Vistazo
- 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.
| Característica | 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 |
¿Quién gana en cada área?
At-a-glance decision frameworkEvaluations ongoing
Puntuaciones 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.
Latencia y Tiempo de Respuesta
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
Simulador Interactivo de Costos de Tokens
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
Gemini 3.5 Flash-Lite · Strengths & Key Advantages
- Economical alto-volumen precios
- rápido ejecución con bajo latencia
- 1M ventana de contexto
Considerations & Trade-offs
- menos adept un profundo matemático proofs
- texto y visión solo (no audio entrada)
Grok 4.6 · Strengths & Key Advantages
- masivo 1.5T parámetro capacidad proporcionando broader real-mundo knowledge y matiz
- Preserves el attractive $2/$6 por millones token precio point
- Notable improvements en completo-stack codificación y multifarchivo system arquitectura
Considerations & Trade-offs
- Quickly succeeded por el 2.1T parámetro Grok 4.7 upgrade
- ventana de contexto capped un 500K tokens
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 |
Especificaciones Técnicas
Architecture, release timeline, capabilities, and modalities.
| Característica | 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: Respuestas 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.
Veredicto
Verdict & Model Selection Recommendation: Choose Gemini 3.5 Flash-Lite if your priority is Autonomous subagent loops, summarization, and data transformation. Its performance in demanding tasks justifies its operational token cost. Choose Grok 4.6 if your workflow prioritizes Medium-to-large software engineering tasks, data synthesis, and complex analysis. For large-scale batch processing or customer-facing conversational interfaces, its balance of speed and economics delivers superior ROI.
Preguntas frecuentes
How does Gemini 3.5 Flash-Lite compare to Grok 4.6 in API token pricing and cost per token?+
Gemini 3.5 Flash-Lite costs $0.40 per 1M input tokens and $2.00 per 1M output tokens, whereas Grok 4.6 costs $2.00 input and $6.00 output. Overall, Gemini 3.5 Flash-Lite 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 3.5 Flash-Lite or Grok 4.6?+
Gemini 3.5 Flash-Lite supports a context window of 1,049K tokens (~786k words), while Grok 4.6 supports 500K tokens (~375k words). Therefore, Gemini 3.5 Flash-Lite can process more textual data and document context in a single prompt.
Which AI model is better for software engineering and coding: Gemini 3.5 Flash-Lite or Grok 4.6?+
Gemini 3.5 Flash-Lite scores at the frontier of coding benchmarks, while Grok 4.6 scores 75.8%. For complex autonomous debugging and agentic engineering, Grok 4.6 provides robust code generation and tool calling.
What is the difference in reasoning capability and extended thinking between Gemini 3.5 Flash-Lite and Grok 4.6?+
Gemini 3.5 Flash-Lite features native chain-of-thought extended thinking mode with configurable reasoning effort. In contrast, Grok 4.6 provides chain-of-thought reasoning depth for complex math and science.
How does inference speed (tokens per second) compare between Gemini 3.5 Flash-Lite and Grok 4.6?+
Gemini 3.5 Flash-Lite generates approximately 240 tokens per second, while Grok 4.6 delivers 115 tokens per second. In latency-sensitive production environments, Gemini 3.5 Flash-Lite provides faster time-to-first-token (TTFT) and higher streaming response velocity.
Can you implement a tiered LLM routing setup combining Gemini 3.5 Flash-Lite and Grok 4.6 to optimize costs?+
Yes! High-efficiency architectures route high-frequency routine classification and conversational tasks to Gemini 3.5 Flash-Lite to save operational costs, and dynamically escalate complex architectural queries or reasoning tasks to Grok 4.6. 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
- Gemini 3.6 Flash vs Gemini 3.5 Flash-Lite: Benchmarks, Pricing & Speed ComparisonComparar
- GPT-5.6 Luna vs Gemini 3.5 Flash-Lite: Benchmarks, Pricing & Speed ComparisonComparar
- Grok 4.6 vs Grok-4: Benchmarks, Pricing & Speed ComparisonComparar
- Aion-3.0 vs Aion-Mini: Benchmarks, Pricing & Speed ComparisonComparar
- Aion-3.0 vs Gemini 3.6 Flash: Benchmarks, Pricing & Speed ComparisonComparar
- Aion-Mini vs Laguna XS 2.1: Benchmarks, Pricing & Speed ComparisonComparar
Las puntuaciones de benchmarks, precios por token y límites de tasa evolucionan rápidamente. Verifique siempre las especificaciones actuales en la documentación oficial del proveedor.
Fuentes: GetInfoUs Independent AI Benchmarks & Official API Specs