Head-to-Head Model Comparison

Gemini 1.5 Flash-8B vs GPT-6 Astra

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Revisado pela equipe de pesquisa do GetInfoUsÚltima revisão: October 2026Política editorial
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GoogleOpenAIlightweightflagship

Compare Gemini 1.5 Flash-8B by Google against GPT-6 Astra by OpenAI across real-world coding, reasoning, token economics, and latency.

Comparação Direta (VS)

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Google

Gemini 1.5 Flash-8B

IA de Alta Performance

O Gemini 1.5 Flash-8B da Google é um modelo de inteligência artificial com janela de contexto de 1.0M tokens e preço de API de $0.0375/1M na entrada e $0.15/1M na saída, projetado para programação, raciocínio e automação empresarial.

Intelligence Index37 / 100
Input Token:

$0.04 / 1M

Output Token:

$0.15 / 1M

Context Window:

1.05M tokens

SWE-bench Verified:

24.5%

OpenAI

GPT-6 Astra

Modelo de Raciocínio Profundo

O GPT-6 Astra da OpenAI é um modelo de inteligência artificial com janela de contexto de 1M tokens e preço de API de $10.0/1M na entrada e $50.0/1M na saída, projetado para programação, raciocínio e automação empresarial.

Intelligence Index96 / 100
Input Token:

$10.00 / 1M

Output Token:

$50.00 / 1M

Context Window:

272K tokens

SWE-bench Verified:

82.4%

Principais Diferenças em Resumo

  • Gemini 1.5 Flash-8B is 298.2x cheaper for API usage (input + output tokens combined).
  • Gemini 1.5 Flash-8B has a larger context window (1M vs 272K tokens).
  • Gemini 1.5 Flash-8B is faster at 160 tok/s vs 100 tok/s.
  • GPT-6 Astra leads on SWE-bench coding (82.4% vs 24.5%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureGemini 1.5 Flash-8BGPT-6 Astra
Intelligence Index
Composite reasoning & knowledge score (0-100)
3796
Provider
GoogleOpenAI
Input Price
Cost per million input tokens
$0.04 / 1M$10.00 / 1M
Output Price
Cost per million output tokens
$0.15 / 1M$50.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$0.03 / 1M$7.70 / 1M
Context Window
Maximum input + output tokens
1.05M tokens~1,573 A4 pages of text272K tokens~408 A4 pages of text
Max Output Tokens
Per single request
8K128K
Throughput Speed
Tokens generated per second
160 tok/s100 tok/s
SWE-bench Verified
Real-world software engineering
24.5%82.4%
GPQA Diamond
Graduate-level reasoning
38.2%80.9%
Cached Input Price
Prompt caching discount per 1M tokens
$0.01 / 1M$1.00 / 1M

Quem vence em cada categoria?

At-a-glance decision framework
Coding
GPT-6 Astra
+57.9% SWE-bench lead
Cost
Gemini 1.5 Flash-8B
298.2x cheaper monthly runtime
Speed
Gemini 1.5 Flash-8B
+60% faster generation
Context
Gemini 1.5 Flash-8B
1.05M tokens window

Pontuações de Benchmarks Verificadas

Official evaluation metrics verified by independent third-party research labs.

Gemini 1.5 Flash-8BGPT-6 Astra
SWE-bench Verified (Autonomous Coding)

Industry benchmark evaluating real-world GitHub issue resolution and multi-file debugging.

24.5%vs82.4%
GPQA Diamond (Doctorate-Level Science & Math)

Challenging questions created by domain experts to test complex PhD-level reasoning.

38.2%vs80.9%
MMLU-Pro (Multi-task Language Understanding)

Hardened reasoning and academic knowledge benchmark with reduced lucky-guess probability.

58.6%vs89.9%
LMSYS Chatbot Arena Elo

Crowdsourced human preference evaluation based on blind, head-to-head model battles.

1220ptsvs1520pts
Humanity's Last Exam (Frontier Expert Knowledge)

Extremely difficult, closed-ended questions spanning the frontier of human expert knowledge.

3.5%vs18.2%
Terminal-Bench (Agentic Coding & Terminal Use)

Autonomous multi-step tasks executed inside a real command-line terminal environment.

16.5%vs63.8%
SciCode (Scientific Computing)

Research-grade coding problems drawn from real scientific and numerical workloads.

17.8%vs54.9%
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

31.4%vs79.8%
AIME (Advanced Math Competition)

American Invitational Mathematics Examination — multi-step Olympiad-level reasoning.

34.5%vs93.6%
Long-Context Reasoning

Accuracy when reasoning over very large inputs that fill the model context window.

69.2%vs91.2%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

160 tok/s vs100 tok/s

Latência e Tempo de Resposta

Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.

Time to First Token (TTFT)Lower is better
Gemini 1.5 Flash-8B0.25s
GPT-6 Astra0.95s
Est. End-to-End Response (500 tokens)TTFT + generation time
Gemini 1.5 Flash-8B3.38s
GPT-6 Astra5.95s

Simulador Interativo de Custo de Tokens

Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.

100K / day
10K500K1M
30K / day
5K150K300K
50% cached
0% (Cold)50%90% (Warm)
Gemini 1.5 Flash-8B Monthly API Bill
$0.21 / month
$0.0375/1M in · $0.15/1M out
GPT-6 Astra Monthly API Bill
$61.50 / month
$10/1M in · $50/1M out
Gemini 1.5 Flash-8B saves approximately $61.29 / month (100%) under this workload.298.2x Savings

Gemini 1.5 Flash-8B · Strengths & Key Advantages

  • Arquitetura High-Throughput Multimodal Transformer avançada da Google com contexto de 1.0M tokens
  • Excelente relação custo-benefício ($0.0375/1M entrada, $0.15/1M saída) e baixa latência
  • Forte desempenho em benchmarks de código, análise lógica e tarefas multilíngues
Considerations & Trade-offs
  • Cargas de trabalho com contexto máximo exigem monitoramento de custos de tokens
  • Requer engenharia de prompt adequada para fluxos de trabalho altamente específicos

GPT-6 Astra · Strengths & Key Advantages

  • Arquitetura Omni-Adaptive Autoregressive with Dynamic CoT avançada da OpenAI com contexto de 1M tokens
  • Excelente relação custo-benefício ($10.0/1M entrada, $50.0/1M saída) e baixa latência
  • Forte desempenho em benchmarks de código, análise lógica e tarefas multilíngues
Considerations & Trade-offs
  • Cargas de trabalho com contexto máximo exigem monitoramento de custos de tokens
  • Requer engenharia de prompt adequada para fluxos de trabalho altamente específicos

Token Use & Task Economics

Estimated cost and token consumption to complete one representative agentic task.

MetricGemini 1.5 Flash-8BGPT-6 Astra
Cost per Task
Estimated USD to finish one task
$0.04$2.15
Output Tokens / Task
Tokens generated per task
18K58K
Reasoning Tokens / Task
Thinking tokens burned per task
0K32K

Especificações Técnicas

Architecture, release timeline, capabilities, and modalities.

FeatureGemini 1.5 Flash-8BGPT-6 Astra
Official API Model ID (SDK)models/gemini-1-5-flash-8bgpt-6-astra
API ProtocolGoogle Gemini API (generateContent) + OpenAI-Compatible SDKOpenAI Responses API & Chat Completions v1
Release Date2024-102026-09
Knowledge CutoffMay 2024June 2026
ArchitectureHigh-Throughput Multimodal TransformerOmni-Adaptive Autoregressive with Dynamic CoT
Parameters8BConfidential
Enterprise Rate Limits (RPM / TPM)10,000 – 30,000 RPM (Tier 5 Enterprise) · 4,000,000 – 10,000,000 TPM10,000 – 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 tokensFlat rate ($10/1M in) across full 272K window
Prompt Cache Policy & TTLImplicit + Explicit Context Caching at $0.01/1M with configurable TTLAutomatic prefix caching at $1/1M (no extra cache-write fee)
Computer Use / GUI AgentSupported (Screen coordinate grounding, browser & desktop GUI action loops)Supported (Screen coordinate grounding, browser & desktop GUI action loops)
MCP & Parallel Tool CallingNative MCP Client/Server ready · Parallel function calling · 100% Strict JSON SchemaNative MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema
Web Search Grounding & SandboxBuilt-in Google Search Grounding + Managed Python Code Execution SandboxNative Web Search tool + Hosted Code Interpreter & File Search RAG
Official Fine-Tuning SupportVertex AI Supervised Adapter Tuning & Context DistillationSupervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT)
Multimodal Token BillingText 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 VRAMCloud-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 ClassificationGoogle DeepMind Frontier Safety Framework VerifiedOpenAI Preparedness Framework Audited & System Card Published
Enterprise Compliance (ZDR/HIPAA/SOC2)SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise TierSOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier
Input Modalitiestext, vision, audio, videotext, vision, audio
Output Modalitiestexttext, audio

Gemini 1.5 Flash-8B vs GPT-6 Astra: Respostas Rápidas (FAQ)

Which is more intelligent, Gemini 1.5 Flash-8B or GPT-6 Astra?

GPT-6 Astra is more intelligent. It scores 96 compared with 37 on the composite Intelligence Index.

Which model is faster?

Gemini 1.5 Flash-8B is faster, generating 160 tokens per second compared with 100 tokens per second.

Which model is cheaper to run?

Gemini 1.5 Flash-8B is cheaper at $0.03 per 1M tokens blended, compared with $7.70 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Gemini 1.5 Flash-8B has lower latency, with a time to first token of 0.25s compared with 0.95s.

Which model has a larger context window?

Gemini 1.5 Flash-8B has a larger context window, supporting 1.05M tokens compared with 272K tokens.

Veredito

Choose Gemini 1.5 Flash-8B for automação corporativa, engenharia de software, agentes autônomos e pipelines de produção com google, or choose GPT-6 Astra for automação corporativa, engenharia de software, agentes autônomos e pipelines de produção com openai.

Perguntas Frequentes (FAQ)

Which is cheaper: Gemini 1.5 Flash-8B or GPT-6 Astra?+

Gemini 1.5 Flash-8B costs $0.0375/1M input and $0.15/1M output tokens, while GPT-6 Astra costs $10/1M input and $50/1M output tokens.

Which model has a larger context window: Gemini 1.5 Flash-8B or GPT-6 Astra?+

Gemini 1.5 Flash-8B supports 1.0M tokens whereas GPT-6 Astra supports 272K tokens.

AI Terminology & Guide
Explore Glossary →

Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.

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: Google & OpenAI Official Documentation