Head-to-Head Model Comparison

Gemma 4 31B vs Mistral Small 4

Benchmarks, API Token Pricing, Context Window & Speed Comparison

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

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Gemma 4 31BProfile

Mistral Small 4Profile

Multi-Model Arena Stack:

5-Model Matrix Workbench

Popular Matchups:

Google

Gemma 4 31B

Raciocínio de Pesos Abertos

O Gemma 4 31B da Google é um modelo de IA projetado para raciocínio em cadeia de pensamento com pesos abertos e alta eficiência, oferecendo janela de contexto de 262K, velocidade de 80 tokens/s, índice de inteligência de 81/100 e tarifa de

Intelligence Index81 / 100

Input Token:

$0.00 / 1M

Output Token:

$0.00 / 1M

Context Window:

262.1K tokens

SWE-bench Verified:

68.5%

Mistral AI

Mistral Small 4

Inferência Ultrarrápida

O Mistral Small 4 da Mistral AI é um modelo de IA projetado para respostas em tempo real com latência ultrabaixa e roteamento de alto volume, oferecendo janela de contexto de 256K, velocidade de 120 tokens/s, índice de inteligência de 48/10

Intelligence Index48 / 100

Input Token:

$0.10 / 1M

Output Token:

$0.30 / 1M

Context Window:

256K tokens

SWE-bench Verified:

44.5%

Principais Diferenças em Resumo

Gemma 4 31B is 1.0x cheaper for API usage (input + output tokens combined).
Gemma 4 31B has a larger context window (262K vs 256K tokens).
Mistral Small 4 is faster at 120 tok/s vs 80 tok/s.
Gemma 4 31B leads on SWE-bench coding (68.5% vs 44.5%).

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

Feature	Gemma 4 31B	Mistral Small 4
Intelligence Index Composite reasoning & knowledge score (0-100)	81	48
Provider	Google	Mistral AI
Input Price Cost per million input tokens	$0.00 / 1M	$0.10 / 1M
Output Price Cost per million output tokens	$0.00 / 1M	$0.30 / 1M
Blended Price Weighted 7:2:1 cache:input:output per 1M	$0.00 / 1M	$0.07 / 1M
Context Window Maximum input + output tokens	262.1K tokens~393 A4 pages of text	256K tokens~384 A4 pages of text
Max Output Tokens Per single request	33K	16K
Throughput Speed Tokens generated per second	80 tok/s	120 tok/s
SWE-bench Verified Real-world software engineering	68.5%	44.5%
GPQA Diamond Graduate-level reasoning	77%	56%
Cached Input Price Prompt caching discount per 1M tokens	$0.00 / 1M	$0.03 / 1M

Quem vence em cada categoria?

At-a-glance decision framework

Coding

Gemma 4 31B

+24.0% SWE-bench lead

Cost

Gemma 4 31B

1.0x cheaper monthly runtime

Speed

Mistral Small 4

+50% faster generation

Context

Gemma 4 31B

262.1K tokens window

Pontuações de Benchmarks Verificadas

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

Gemma 4 31BMistral Small 4

SWE-bench Verified (Autonomous Coding)

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

68.5%vs44.5%

GPQA Diamond (Doctorate-Level Science & Math)

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

77%vs56%

MMLU-Pro (Multi-task Language Understanding)

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

84.8%vs78%

LMSYS Chatbot Arena Elo

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

1410ptsvs1315pts

Terminal-Bench (Agentic Coding & Terminal Use)

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

N/Avs38%

AIME (Advanced Math Competition)

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

86%vs66%

Long-Context Reasoning

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

N/Avs80%

Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

80 tok/s vs120 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

Gemma 4 31B0.48s

Mistral Small 40.34s

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

Gemma 4 31B6.73s

Mistral Small 44.51s

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)

Gemma 4 31B Monthly API Bill

$0.00 / month

$0/1M in · $0/1M out

Mistral Small 4 Monthly API Bill

$0.47 / month

$0.1/1M in · $0.3/1M out

Gemma 4 31B saves approximately $0.47 / month (100%) under this workload.1.0x Savings

Gemma 4 31B · Strengths & Key Advantages

Janela de contexto de 262K com limite máximo de saída de 33K tokens (SWE-bench Verified 68.5% · GPQA Diamond 77%)
Taxa de transferência rápida de 80 tokens/segundo com latência inicial (TTFT) de 480 ms
Pesos abertos (31B) 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

Mistral Small 4 · Strengths & Key Advantages

Janela de contexto de 256K com limite máximo de saída de 16K tokens (SWE-bench Verified 44.5% · GPQA Diamond 56%)
Taxa de transferência rápida de 120 tokens/segundo com latência inicial (TTFT) de 340 ms
Pesos abertos (24B) 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	Gemma 4 31B	Mistral Small 4
Cost per Task Estimated USD to finish one task	$0.00	$0.12
Output Tokens / Task Tokens generated per task	12K	28K
Reasoning Tokens / Task Thinking tokens burned per task	6K	12K

Especificações Técnicas

Architecture, release timeline, capabilities, and modalities.

Feature	Gemma 4 31B	Mistral Small 4
Official API Model ID (SDK)	models/gemma-4-31b	mistral-small-4-latest
API Protocol	Google Gemini API (generateContent) + OpenAI-Compatible SDK	OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI
Release Date	2026-04	2026-03
Knowledge Cutoff	January 2026	January 2026
Architecture	Dense open reasoning transformer with native thinking	Next-Gen Compact Multimodal Transformer
Parameters	31B	24B
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)	Free across full context window (only KV-cache VRAM scales)	Flat rate ($0.1/1M in) across full 256K window
Prompt Cache Policy & TTL	Automatic prefix KV-caching in vLLM / SGLang (0 cost)	Cached input at $0.03/1M 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	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) · Vision (~258–765 tokens per image tile)	Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile)
Quantization & Min GPU VRAM	BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 19 GB VRAM (4-bit Quantized) · 67 GB VRAM (Native BF16)	BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 15 GB VRAM (4-bit Quantized) · 52 GB VRAM (Native BF16)
Safety & Frontier Classification	Google DeepMind Frontier Safety Framework Verified	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, vision	text, vision
Output Modalities	text	text

Gemma 4 31B vs Mistral Small 4: Respostas Rápidas (FAQ)

Which is more intelligent, Gemma 4 31B or Mistral Small 4?

Gemma 4 31B is more intelligent. It scores 81 compared with 48 on the composite Intelligence Index.

Which model is faster?

Mistral Small 4 is faster, generating 120 tokens per second compared with 80 tokens per second.

Which model is cheaper to run?

Gemma 4 31B is cheaper at $0.00 per 1M tokens blended, compared with $0.07 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Mistral Small 4 has lower latency, with a time to first token of 0.34s compared with 0.48s.

Which model has a larger context window?

Gemma 4 31B has a larger context window, supporting 262.1K tokens compared with 256K tokens.

Veredito

Tanto Gemma 4 31B (Indicado para raciocínio em cadeia de pensamento com pesos abertos e alta eficiência, arquiteturas RAG corporativas e integração escalável via API.) quanto Mistral Small 4 (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: Gemma 4 31B lidera em inteligência geral e programação, Mistral Small 4 oferece geração mais rápida e Gemma 4 31B apresenta o melhor custo-benefício em produção.

Perguntas Frequentes (FAQ)

Qual é melhor para programação e raciocínio, Gemma 4 31B ou Mistral Small 4?+

Nas avaliações de inteligência e código, Gemma 4 31B leva vantagem. Confira os gráficos SWE-bench e GPQA acima para detalhes.

Qual modelo tem a API mais barata, Gemma 4 31B ou Mistral Small 4?+

O Gemma 4 31B custa $0.00 / $0.00 por 1M de tokens (entrada/saída) e o Mistral Small 4 custa $0.10 / $0.30. No custo combinado, Gemma 4 31B é mais econômico.

Qual modelo possui maior janela de contexto e velocidade?+

O Gemma 4 31B suporta 262.1K tokens de contexto contra 256K tokens do Mistral Small 4, enquanto Mistral Small 4 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)

Gemma 4 31B vs Mistral Small 4

Troque e Compare Qualquer Modelo

Gemma 4 31B

Mistral Small 4

Quem vence em cada categoria?

Pontuações de Benchmarks Verificadas

Latência e Tempo de Resposta

Simulador Interativo de Custo de Tokens

Gemma 4 31B · Strengths & Key Advantages

Considerations & Trade-offs

Mistral Small 4 · Strengths & Key Advantages

Considerations & Trade-offs

Token Use & Task Economics

Especificações Técnicas

Gemma 4 31B vs Mistral Small 4: Respostas Rápidas (FAQ)

Veredito

Perguntas Frequentes (FAQ)

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