Head-to-Head Model Comparison

Mixtral 8x7B vs Llama 3 (8B)

Benchmarks, API Token Pricing, Context Window & Speed Comparison

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

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Mixtral 8x7BProfile

Llama 3 (8B)Profile

Multi-Model Arena Stack:

5-Model Matrix Workbench

Popular Matchups:

Mistral AI

Mixtral 8x7B

Modelo Base de Pesos Abertos

O Mixtral 8x7B da Mistral AI é um modelo de IA projetado para auto-hospedagem em infraestrutura própria, fine-tuning e soberania de dados, oferecendo janela de contexto de 33K, velocidade de 130 tokens/s, índice de inteligência de 37/100 e

Intelligence Index37 / 100

Input Token:

$0.20 / 1M

Output Token:

$0.20 / 1M

Context Window:

32.8K tokens

SWE-bench Verified:

N/A

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%

Principais Diferenças em Resumo

Llama 3 (8B) is 3.0x cheaper for API usage (input + output tokens combined).
Mixtral 8x7B has a larger context window (33K vs 8K tokens).
Llama 3 (8B) is faster at 210 tok/s vs 130 tok/s.

Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →

Feature	Mixtral 8x7B	Llama 3 (8B)
Intelligence Index Composite reasoning & knowledge score (0-100)	37	34
Provider	Mistral AI	Meta
Input Price Cost per million input tokens	$0.20 / 1M	$0.05 / 1M
Output Price Cost per million output tokens	$0.20 / 1M	$0.10 / 1M
Blended Price Weighted 7:2:1 cache:input:output per 1M	$0.10 / 1M	$0.03 / 1M
Context Window Maximum input + output tokens	32.8K tokens~49 A4 pages of text	8.2K tokens~12 A4 pages of text
Max Output Tokens Per single request	4K	4K
Throughput Speed Tokens generated per second	130 tok/s	210 tok/s
SWE-bench Verified Real-world software engineering	N/A	12%
GPQA Diamond Graduate-level reasoning	38%	34.2%
Cached Input Price Prompt caching discount per 1M tokens	$0.05 / 1M	$0.01 / 1M

Quem vence em cada categoria?

At-a-glance decision framework

Coding

Evaluations ongoing

Cost

Llama 3 (8B)

3.0x cheaper monthly runtime

Speed

Llama 3 (8B)

+62% faster generation

Context

Mixtral 8x7B

32.8K tokens window

Pontuações de Benchmarks Verificadas

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

Mixtral 8x7BLlama 3 (8B)

SWE-bench Verified (Autonomous Coding)

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

N/Avs12%

GPQA Diamond (Doctorate-Level Science & Math)

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

38%vs34.2%

MMLU-Pro (Multi-task Language Understanding)

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

66.5%vs62.5%

LMSYS Chatbot Arena Elo

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

1195ptsvs1150pts

Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

130 tok/s vs210 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

Mixtral 8x7B0.38s

Llama 3 (8B)0.22s

Est. End-to-End Response (500 tokens)TTFT + generation time

Mixtral 8x7B4.23s

Llama 3 (8B)2.60s

Simulador Interativo de Custo de Tokens

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

Daily Input Tokens100K / day

10K500K1M

Daily Output Tokens30K / day

5K150K300K

Prompt Cache Hit Ratio50% cached

0% (Cold)50%90% (Warm)

Mixtral 8x7B Monthly API Bill

$0.56 / month

$0.2/1M in · $0.2/1M out

Llama 3 (8B) Monthly API Bill

$0.18 / month

$0.05/1M in · $0.1/1M out

Llama 3 (8B) saves approximately $0.37 / month (67%) under this workload.3.0x Savings

Mixtral 8x7B · Strengths & Key Advantages

Janela de contexto de 33K com limite máximo de saída de 4K tokens (GPQA Diamond 38% · MMLU-Pro 66.5%)
Taxa de transferência rápida de 130 tokens/segundo com latência inicial (TTFT) de 380 ms
Pesos abertos (46.7B (12.9B )) 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 (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

Token Use & Task Economics

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

Metric	Mixtral 8x7B	Llama 3 (8B)
Cost per Task Estimated USD to finish one task	$0.20	$0.20
Output Tokens / Task Tokens generated per task	24K	24K
Reasoning Tokens / Task Thinking tokens burned per task	0K	0K

Especificações Técnicas

Architecture, release timeline, capabilities, and modalities.

Feature	Mixtral 8x7B	Llama 3 (8B)
Official API Model ID (SDK)	mixtral-8x7b-latest	meta-llama/Llama-3-(8B)
API Protocol	OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI	OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI
Release Date	2023-12	2024-04
Knowledge Cutoff	Late 2023	March 2024
Architecture	Sparse Mixture of Experts (MoE, 2 active of 8)	Dense GQA Transformer with 128K Tokenizer
Parameters	46.7B (12.9B active)	8B
Enterprise Rate Limits (RPM / TPM)	Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud	Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud
Long-Context Tier (>128K/200K)	Flat rate ($0.2/1M in) across full 33K window	Flat rate ($0.05/1M in) across full 8K window
Prompt Cache Policy & TTL	Cached input at $0.05/1M tokens	Cached input at $0.0125/1M tokens
Computer Use / GUI Agent	API / 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 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	Supported via external Tavily/Exa Search & E2B/Docker Sandbox tools	Supported via external Tavily/Exa Search & E2B/Docker Sandbox tools
Official Fine-Tuning Support	Full 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 Billing	Text BPE (~4 chars/token)	Text BPE (~4 chars/token)
Quantization & Min GPU VRAM	BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 29 GB VRAM (4-bit Quantized) · 100 GB VRAM (Native BF16)	BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 5 GB VRAM (4-bit Quantized) · 17 GB VRAM (Native BF16)
Safety & Frontier Classification	Open-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 Control	100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 Control
Input Modalities	text	text
Output Modalities	text	text

Mixtral 8x7B vs Llama 3 (8B): Respostas Rápidas (FAQ)

Which is more intelligent, Mixtral 8x7B or Llama 3 (8B)?

Mixtral 8x7B is more intelligent. It scores 37 compared with 34 on the composite Intelligence Index.

Which model is faster?

Llama 3 (8B) is faster, generating 210 tokens per second compared with 130 tokens per second.

Which model is cheaper to run?

Llama 3 (8B) is cheaper at $0.03 per 1M tokens blended, compared with $0.10 (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 0.38s.

Which model has a larger context window?

Mixtral 8x7B has a larger context window, supporting 32.8K tokens compared with 8.2K tokens.

Veredito

Tanto Mixtral 8x7B (Indicado para auto-hospedagem em infraestrutura própria, fine-tuning e soberania de dados, arquiteturas RAG corporativas e integração escalável via API.) quanto 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.) entregam excelente desempenho: Mixtral 8x7B 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, Mixtral 8x7B ou Llama 3 (8B)?+

Nas avaliações de inteligência e código, Mixtral 8x7B leva vantagem. Confira os gráficos SWE-bench e GPQA acima para detalhes.

Qual modelo tem a API mais barata, Mixtral 8x7B ou Llama 3 (8B)?+

O Mixtral 8x7B custa $0.20 / $0.20 por 1M de tokens (entrada/saída) e o Llama 3 (8B) custa $0.05 / $0.10. No custo combinado, Llama 3 (8B) é mais econômico.

Qual modelo possui maior janela de contexto e velocidade?+

O Mixtral 8x7B suporta 32.8K tokens de contexto contra 8.2K tokens do Llama 3 (8B), 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.

Tokens & Pricing Context Window AI Benchmarks Reasoning Models Tool Calling Model Context Protocol (MCP)

Mixtral 8x7B vs Llama 3 (8B)

Troque e Compare Qualquer Modelo

Mixtral 8x7B

Llama 3 (8B)

Quem vence em cada categoria?

Pontuações de Benchmarks Verificadas

Latência e Tempo de Resposta

Simulador Interativo de Custo de Tokens

Mixtral 8x7B · Strengths & Key Advantages

Considerations & Trade-offs

Llama 3 (8B) · Strengths & Key Advantages

Considerations & Trade-offs

Token Use & Task Economics

Especificações Técnicas

Mixtral 8x7B vs Llama 3 (8B): Respostas Rápidas (FAQ)

Veredito

Perguntas Frequentes (FAQ)

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