Gemini 3.7 Flash vs GPT-6 Astra
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (4)
Compare Gemini 3.7 Flash by Google against GPT-6 Astra by OpenAI across real-world coding, reasoning, token economics, and latency.
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Live comparison: no in-depth editorial review has been published for this pair yet.
Gemini 3.7 Flash
Eficiencia ante todoagente-optimized Flash variant tuned para herramienta chains, sequential ejecución, y bajo error rates.
$0.75 / 1M
$3.75 / 1M
1.05M tokens
73.4%
GPT-6 Astra
Agente de SO autónomode OpenAI late-2026 insignia modelo fundacional con nativo uso de computadora agentes, dynamic UI orchestration, y profundo STEM razonamiento.
$10.00 / 1M
$50.00 / 1M
272K tokens
82.4%
Diferencias Clave de un Vistazo
- Gemini 3.7 Flash is 12.9x cheaper for API usage (input + output tokens combined).
- Gemini 3.7 Flash has a larger context window (1M vs 272K tokens).
- Gemini 3.7 Flash is faster at 180 tok/s vs 100 tok/s.
- GPT-6 Astra leads on SWE-bench coding (82.4% vs 73.4%).
| Característica | Gemini 3.7 Flash | GPT-6 Astra |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 85 | 96 |
Provider | OpenAI | |
Input Price Cost per million input tokens | $0.75 / 1M | $10.00 / 1M |
Output Price Cost per million output tokens | $3.75 / 1M | $50.00 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $0.66 / 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 | 66K | 128K |
Throughput Speed Tokens generated per second | 180 tok/s | 100 tok/s |
SWE-bench Verified Real-world software engineering | 73.4% | 82.4% |
GPQA Diamond Graduate-level reasoning | 83.1% | 80.9% |
Cached Input Price Prompt caching discount per 1M tokens | $0.19 / 1M | $1.00 / 1M |
¿Quién gana en cada área?
At-a-glance decision frameworkPuntuaciones 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 3.7 Flash · Strengths & Key Advantages
- excepcional multi-herramienta agentic reliability
- Substantially reduced herramienta invocation hallucinations
- rápido ejecución velocidad
Considerations & Trade-offs
- Pro nivel matemáticas proofs remain stronger
- requiere careful prompt conditioning para legacy herramientas
GPT-6 Astra · Strengths & Key Advantages
- Flawless OS-level navigation y uso de computadora automatización
- Seamless en tiempo real multimodal voz y visión interactivity
- Dynamic cadena de pensamiento que self-adjusts profundidad based en query difficulty
- enorme 1M ventana de contexto con instant prefix caching
Considerations & Trade-offs
- Strict seguridad filters puede occasionally throttle complejo penetration testing prompts
- Slightly mayor razonamiento latencia en alto-effort matemáticas queries
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | Gemini 3.7 Flash | GPT-6 Astra |
|---|---|---|
Cost per Task Estimated USD to finish one task | $1.15 | $2.15 |
Output Tokens / Task Tokens generated per task | 42K | 58K |
Reasoning Tokens / Task Thinking tokens burned per task | 20K | 32K |
Especificaciones Técnicas
Architecture, release timeline, capabilities, and modalities.
| Característica | Gemini 3.7 Flash | GPT-6 Astra |
|---|---|---|
| Official API Model ID (SDK) | models/gemini-3-7-flash | gpt-6-astra |
| API Protocol | Google Gemini API (generateContent) + OpenAI-Compatible SDK | OpenAI Responses API & Chat Completions v1 |
| Release Date | 2026-08 | 2026-09 |
| Knowledge Cutoff | May 2026 | June 2026 |
| Architecture | Agent-first adaptive 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 $0.1875/1M 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) · 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) |
| 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, audio |
| Output Modalities | text | text, audio |
Gemini 3.7 Flash vs GPT-6 Astra: Respuestas Rápidas (FAQ)
Which is more intelligent, Gemini 3.7 Flash or GPT-6 Astra?
GPT-6 Astra is more intelligent. It scores 96 compared with 85 on the composite Intelligence Index.
Which model is faster?
Gemini 3.7 Flash is faster, generating 180 tokens per second compared with 100 tokens per second.
Which model is cheaper to run?
Gemini 3.7 Flash is cheaper at $0.66 per 1M tokens blended, compared with $7.70 (7:2:1 cache:input:output ratio).
Which model has lower latency?
Gemini 3.7 Flash has lower latency, with a time to first token of 0.38s compared with 0.95s.
Which model has a larger context window?
Gemini 3.7 Flash has a larger context window, supporting 1.05M tokens compared with 272K tokens.
Veredicto
Choose Gemini 3.7 Flash for autónomo herramienta orchestration, devops canalizaciones, y api integrations, or choose GPT-6 Astra for autónomo browser/computer flujos de trabajo, en tiempo real voz agentes, y alto-difficulty matemático razonamiento.
Preguntas frecuentes
Which is cheaper: Gemini 3.7 Flash or GPT-6 Astra?+
Gemini 3.7 Flash costs $0.75/1M input and $3.75/1M output tokens, while GPT-6 Astra costs $10/1M input and $50/1M output tokens.
Which model has a larger context window: Gemini 3.7 Flash or GPT-6 Astra?+
Gemini 3.7 Flash 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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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: Google & OpenAI Official Documentation