Head-to-Head Model Comparison

Llama 3 (8B) vs Llama 3 (70B)

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Revisado pela equipe de pesquisa do GetInfoUsÚltima revisão: October 2026Política editorial
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AI CompareAI BenchmarkToken PricingModel CostModel SpecsSWE-bench CodingModel VersusWhich AI ModelLLM Speed & LatencyReasoning ModelsExtended ThinkingPrompt Caching ROI
Llama 3 (8B) vs Llama 3 (70B): Benchmarks, Pricing & Speed Comparison

Llama 3 (8B) da Meta e Llama 3 (70B) da Meta são dois modelos de IA de destaque. O Llama 3 (8B) oferece uma janela de contexto de 8.2K tokens a $0.05/$0.10 por milhão de tokens, enquanto o Llama 3 (70B) oferece 8.2K tokens de contexto a $0.35/$0.80 por milhão de tokens. Veja abaixo a comparação completa de benchmarks, latência e custos.

Comparação Direta (VS)

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Meta

Llama 3 (8B)

Inferência Ultrarrápida

O Llama 3 (8B) da Meta é um modelo de IA projetado para respostas em tempo real com latência ultrabaixa e roteamento de alto volume, oferecendo janela de contexto de 8K, velocidade de 210 tokens/s, índice de inteligência de 34/100 e tarifa

Intelligence Index34 / 100
Input Token:

$0.05 / 1M

Output Token:

$0.10 / 1M

Context Window:

8.2K tokens

SWE-bench Verified:

12%

Meta

Llama 3 (70B)

Modelo Base de Pesos Abertos

O Llama 3 (70B) da Meta é um modelo de IA projetado para auto-hospedagem em infraestrutura própria, fine-tuning e soberania de dados, oferecendo janela de contexto de 8K, velocidade de 110 tokens/s, índice de inteligência de 42/100 e tarifa

Intelligence Index42 / 100
Input Token:

$0.35 / 1M

Output Token:

$0.80 / 1M

Context Window:

8.2K tokens

SWE-bench Verified:

24%

Principais Diferenças em Resumo

  • Llama 3 (8B) is 7.5x cheaper for API usage (input + output tokens combined).
  • Llama 3 (8B) is faster at 210 tok/s vs 110 tok/s.
  • Llama 3 (70B) leads on SWE-bench coding (24.0% vs 12.0%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureLlama 3 (8B)Llama 3 (70B)
Intelligence Index
Composite reasoning & knowledge score (0-100)
3442
Provider
MetaMeta
Input Price
Cost per million input tokens
$0.05 / 1M$0.35 / 1M
Output Price
Cost per million output tokens
$0.10 / 1M$0.80 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$0.03 / 1M$0.21 / 1M
Context Window
Maximum input + output tokens
8.2K tokens~12 A4 pages of text8.2K tokens~12 A4 pages of text
Max Output Tokens
Per single request
4K4K
Throughput Speed
Tokens generated per second
210 tok/s110 tok/s
SWE-bench Verified
Real-world software engineering
12%24%
GPQA Diamond
Graduate-level reasoning
34.2%46%
Cached Input Price
Prompt caching discount per 1M tokens
$0.01 / 1M$0.09 / 1M

Quem vence em cada categoria?

At-a-glance decision framework
Coding
Llama 3 (70B)
+12.0% SWE-bench lead
Cost
Llama 3 (8B)
7.5x cheaper monthly runtime
Speed
Llama 3 (8B)
+91% faster generation
Context
Tied
8.2K tokens window

Pontuações de Benchmarks Verificadas

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

Llama 3 (8B)Llama 3 (70B)
SWE-bench Verified (Autonomous Coding)

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

12%vs24%
GPQA Diamond (Doctorate-Level Science & Math)

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

34.2%vs46%
MMLU-Pro (Multi-task Language Understanding)

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

62.5%vs72%
LMSYS Chatbot Arena Elo

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

1150ptsvs1245pts
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

210 tok/s vs110 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
Llama 3 (8B)0.22s
Llama 3 (70B)0.42s
Est. End-to-End Response (500 tokens)TTFT + generation time
Llama 3 (8B)2.60s
Llama 3 (70B)4.97s

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)
Llama 3 (8B) Monthly API Bill
$0.18 / month
$0.05/1M in · $0.1/1M out
Llama 3 (70B) Monthly API Bill
$1.38 / month
$0.35/1M in · $0.8/1M out
Llama 3 (8B) saves approximately $1.19 / month (87%) under this workload.7.5x Savings

Llama 3 (8B) · Strengths & Key Advantages

  • Janela de contexto de 8K com limite máximo de saída de 4K tokens (SWE-bench Verified 12% · GPQA Diamond 34.2%)
  • Taxa de transferência rápida de 210 tokens/segundo com latência inicial (TTFT) de 220 ms
  • Pesos abertos (8B) para auto-hospedagem local ou em nuvem privada via vLLM, SGLang ou Ollama
Considerations & Trade-offs
  • Requer servidores GPU com memória VRAM adequada para execução local em precisão total
  • Em derivações científicas extremas, modelos pesados dedicados exclusivamente ao raciocínio oferecem maior profundidade

Llama 3 (70B) · Strengths & Key Advantages

  • Janela de contexto de 8K com limite máximo de saída de 4K tokens (SWE-bench Verified 24% · GPQA Diamond 46%)
  • Taxa de transferência rápida de 110 tokens/segundo com latência inicial (TTFT) de 420 ms
  • Pesos abertos (70B) para auto-hospedagem local ou em nuvem privada via vLLM, SGLang ou Ollama
Considerations & Trade-offs
  • Requer servidores GPU com memória VRAM adequada para execução local em precisão total
  • Em derivações científicas extremas, modelos pesados dedicados exclusivamente ao raciocínio oferecem maior profundidade

Token Use & Task Economics

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

MetricLlama 3 (8B)Llama 3 (70B)
Cost per Task
Estimated USD to finish one task
$0.20$0.20
Output Tokens / Task
Tokens generated per task
24K24K
Reasoning Tokens / Task
Thinking tokens burned per task
0K0K

Especificações Técnicas

Architecture, release timeline, capabilities, and modalities.

FeatureLlama 3 (8B)Llama 3 (70B)
Official API Model ID (SDK)meta-llama/Llama-3-(8B)meta-llama/Llama-3-(70B)
API ProtocolOpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGIOpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI
Release Date2024-042024-04
Knowledge CutoffMarch 2024March 2024
ArchitectureDense GQA Transformer with 128K TokenizerGQA High-Capacity Transformer
Parameters8B70B
Enterprise Rate Limits (RPM / TPM)Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed CloudUnlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud
Long-Context Tier (>128K/200K)Flat rate ($0.05/1M in) across full 8K windowFlat rate ($0.35/1M in) across full 8K window
Prompt Cache Policy & TTLCached input at $0.0125/1M tokensCached input at $0.0875/1M tokens
Computer Use / GUI AgentAPI / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop)API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop)
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 & SandboxSupported via external Tavily/Exa Search & E2B/Docker Sandbox toolsSupported via external Tavily/Exa Search & E2B/Docker Sandbox tools
Official Fine-Tuning SupportFull Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory)Full Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory)
Multimodal Token BillingText BPE (~4 chars/token)Text BPE (~4 chars/token)
Quantization & Min GPU VRAMBF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 5 GB VRAM (4-bit Quantized) · 17 GB VRAM (Native BF16)BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 43 GB VRAM (4-bit Quantized) · 151 GB VRAM (Native BF16)
Safety & Frontier ClassificationOpen-Weights System Card + Customizable Guardrail Layer (Llama Guard / ShieldGemma)Open-Weights System Card + Customizable Guardrail Layer (Llama Guard / ShieldGemma)
Enterprise Compliance (ZDR/HIPAA/SOC2)100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 Control100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 Control
Input Modalitiestexttext
Output Modalitiestexttext

Llama 3 (8B) vs Llama 3 (70B): Respostas Rápidas (FAQ)

Which is more intelligent, Llama 3 (8B) or Llama 3 (70B)?

Llama 3 (70B) is more intelligent. It scores 42 compared with 34 on the composite Intelligence Index.

Which model is faster?

Llama 3 (8B) is faster, generating 210 tokens per second compared with 110 tokens per second.

Which model is cheaper to run?

Llama 3 (8B) is cheaper at $0.03 per 1M tokens blended, compared with $0.21 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Llama 3 (8B) has lower latency, with a time to first token of 0.22s compared with 0.42s.

Veredito

Tanto Llama 3 (8B) (Indicado para respostas em tempo real com latência ultrabaixa e roteamento de alto volume, arquiteturas RAG corporativas e integração escalável via API.) quanto Llama 3 (70B) (Indicado para auto-hospedagem em infraestrutura própria, fine-tuning e soberania de dados, arquiteturas RAG corporativas e integração escalável via API.) entregam excelente desempenho: Llama 3 (70B) lidera em inteligência geral e programação, Llama 3 (8B) oferece geração mais rápida e Llama 3 (8B) apresenta o melhor custo-benefício em produção.

Perguntas Frequentes (FAQ)

Qual é melhor para programação e raciocínio, Llama 3 (8B) ou Llama 3 (70B)?+

Nas avaliações de inteligência e código, Llama 3 (70B) leva vantagem. Confira os gráficos SWE-bench e GPQA acima para detalhes.

Qual modelo tem a API mais barata, Llama 3 (8B) ou Llama 3 (70B)?+

O Llama 3 (8B) custa $0.05 / $0.10 por 1M de tokens (entrada/saída) e o Llama 3 (70B) custa $0.35 / $0.80. No custo combinado, Llama 3 (8B) é mais econômico.

Qual modelo possui maior janela de contexto e velocidade?+

O Llama 3 (8B) suporta 8.2K tokens de contexto contra 8.2K tokens do Llama 3 (70B), enquanto Llama 3 (8B) entrega maior velocidade de geração.

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: Documentação oficial de API da Meta e Meta e benchmarks independentes (2026).