Head-to-Head Model Comparison

Qwen3-Coder 30B-A3B Instruct vs Devstral Medium

Benchmarks, API Token Pricing, Context Window & Speed Comparison

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

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Qwen3-Coder 30B-A3B InstructProfile

Devstral MediumProfile

Multi-Model Arena Stack:

5-Model Matrix Workbench

Popular Matchups:

Alibaba

Qwen3-Coder 30B-A3B Instruct

Modelo Base de Pesos Abertos

O Qwen3-Coder 30B-A3B Instruct da Alibaba é um modelo de IA projetado para auto-hospedagem em infraestrutura própria, fine-tuning e soberania de dados, oferecendo janela de contexto de 262K, velocidade de 140 tokens/s, índice de inteligênci

Intelligence Index76 / 100

Input Token:

$0.00 / 1M

Output Token:

$0.00 / 1M

Context Window:

262.1K tokens

SWE-bench Verified:

N/A

Mistral AI

Devstral Medium

IA Agêntica e Uso de Ferramentas

O Devstral Medium da Mistral AI é um modelo de IA projetado para fluxos de trabalho agênticos autônomos, chamada de ferramentas e automação, oferecendo janela de contexto de 128K, velocidade de 75 tokens/s, índice de inteligência de 52/100

Intelligence Index52 / 100

Input Token:

$0.80 / 1M

Output Token:

$2.40 / 1M

Context Window:

128K tokens

SWE-bench Verified:

51.5%

Principais Diferenças em Resumo

Qwen3-Coder 30B-A3B Instruct is 1.0x cheaper for API usage (input + output tokens combined).
Qwen3-Coder 30B-A3B Instruct has a larger context window (262K vs 128K tokens).
Qwen3-Coder 30B-A3B Instruct is faster at 140 tok/s vs 75 tok/s.

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

Feature	Qwen3-Coder 30B-A3B Instruct	Devstral Medium
Intelligence Index Composite reasoning & knowledge score (0-100)	76	52
Provider	Alibaba	Mistral AI
Input Price Cost per million input tokens	$0.00 / 1M	$0.80 / 1M
Output Price Cost per million output tokens	$0.00 / 1M	$2.40 / 1M
Blended Price Weighted 7:2:1 cache:input:output per 1M	$0.00 / 1M	$0.54 / 1M
Context Window Maximum input + output tokens	262.1K tokens~393 A4 pages of text	128K tokens~192 A4 pages of text
Max Output Tokens Per single request	8K	33K
Throughput Speed Tokens generated per second	140 tok/s	75 tok/s
SWE-bench Verified Real-world software engineering	N/A	51.5%
GPQA Diamond Graduate-level reasoning	N/A	62%
Cached Input Price Prompt caching discount per 1M tokens	$0.00 / 1M	$0.20 / 1M

Quem vence em cada categoria?

At-a-glance decision framework

Coding

Evaluations ongoing

Cost

Qwen3-Coder 30B-A3B Instruct

1.0x cheaper monthly runtime

Speed

Qwen3-Coder 30B-A3B Instruct

+87% faster generation

Context

Qwen3-Coder 30B-A3B Instruct

262.1K tokens window

Pontuações de Benchmarks Verificadas

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

Qwen3-Coder 30B-A3B InstructDevstral Medium

SWE-bench Verified (Autonomous Coding)

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

N/Avs51.5%

GPQA Diamond (Doctorate-Level Science & Math)

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

N/Avs62%

MMLU-Pro (Multi-task Language Understanding)

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

74%vs80.5%

LMSYS Chatbot Arena Elo

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

1285ptsvs1330pts

Terminal-Bench (Agentic Coding & Terminal Use)

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

N/Avs45%

LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

63%vsN/A

AIME (Advanced Math Competition)

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

N/Avs72%

Long-Context Reasoning

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

N/Avs78%

Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

140 tok/s vs75 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

Qwen3-Coder 30B-A3B Instruct0.28s

Devstral Medium0.50s

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

Qwen3-Coder 30B-A3B Instruct3.85s

Devstral Medium7.17s

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)

Qwen3-Coder 30B-A3B Instruct Monthly API Bill

$0.00 / month

$0/1M in · $0/1M out

Devstral Medium Monthly API Bill

$3.66 / month

$0.8/1M in · $2.4/1M out

Qwen3-Coder 30B-A3B Instruct saves approximately $3.66 / month (100%) under this workload.1.0x Savings

Qwen3-Coder 30B-A3B Instruct · Strengths & Key Advantages

Janela de contexto de 262K com limite máximo de saída de 8K tokens (MMLU-Pro 74% · Arena Elo 1285)
Taxa de transferência rápida de 140 tokens/segundo com latência inicial (TTFT) de 280 ms
Pesos abertos (30B total (3B MoE)) 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

Devstral Medium · Strengths & Key Advantages

Janela de contexto de 128K com limite máximo de saída de 33K tokens (SWE-bench Verified 51.5% · GPQA Diamond 62%)
Taxa de transferência rápida de 75 tokens/segundo com latência inicial (TTFT) de 500 ms
Economia de API competitiva ($0.8/$2.4 por 1M de tokens) com suporte a cache de prompts e saídas JSON estruturadas

Considerations & Trade-offs

Modelo proprietário em nuvem; não permite download dos pesos para execução local offline
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	Qwen3-Coder 30B-A3B Instruct	Devstral Medium
Cost per Task Estimated USD to finish one task	$0.00	$0.55
Output Tokens / Task Tokens generated per task	15K	38K
Reasoning Tokens / Task Thinking tokens burned per task	0K	18K

Especificações Técnicas

Architecture, release timeline, capabilities, and modalities.

Feature	Qwen3-Coder 30B-A3B Instruct	Devstral Medium
Official API Model ID (SDK)	qwen3-coder-30b-a3b-instruct	devstral-medium-latest
API Protocol	OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI	Mistral AI REST API (OpenAI-Compatible)
Release Date	2025-04	2025-07
Knowledge Cutoff	March 2025	May 2025
Architecture	Compact Sparse Mixture-of-Experts Transformer	High-Capacity Agentic Code Transformer
Parameters	30B total (3B active MoE)	Confidential (~70B)
Enterprise Rate Limits (RPM / TPM)	Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud	5,000 – 15,000 RPM (Production Tier) · 800,000 – 2,000,000 TPM
Long-Context Tier (>128K/200K)	Free across full context window (only KV-cache VRAM scales)	Flat rate ($0.8/1M in) across full 128K window
Prompt Cache Policy & TTL	Automatic prefix KV-caching in vLLM / SGLang (0 cost)	Cached input at $0.2/1M 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)	API Prompt Engineering & RAG Distillation
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) · 19 GB VRAM (4-bit Quantized) · 65 GB VRAM (Native BF16)	Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API)
Safety & Frontier Classification	Open-Weights System Card + Customizable Guardrail Layer (Llama Guard / ShieldGemma)	Mistral AI Production Safety & Alignment Verified
Enterprise Compliance (ZDR/HIPAA/SOC2)	100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 Control	SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier
Input Modalities	text	text
Output Modalities	text	text

Qwen3-Coder 30B-A3B Instruct vs Devstral Medium: Respostas Rápidas (FAQ)

Which is more intelligent, Qwen3-Coder 30B-A3B Instruct or Devstral Medium?

Qwen3-Coder 30B-A3B Instruct is more intelligent. It scores 76 compared with 52 on the composite Intelligence Index.

Which model is faster?

Qwen3-Coder 30B-A3B Instruct is faster, generating 140 tokens per second compared with 75 tokens per second.

Which model is cheaper to run?

Qwen3-Coder 30B-A3B Instruct is cheaper at $0.00 per 1M tokens blended, compared with $0.54 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Qwen3-Coder 30B-A3B Instruct has lower latency, with a time to first token of 0.28s compared with 0.50s.

Which model has a larger context window?

Qwen3-Coder 30B-A3B Instruct has a larger context window, supporting 262.1K tokens compared with 128K tokens.

Veredito

Tanto Qwen3-Coder 30B-A3B Instruct (Indicado para auto-hospedagem em infraestrutura própria, fine-tuning e soberania de dados, arquiteturas RAG corporativas e integração escalável via API.) quanto Devstral Medium (Indicado para fluxos de trabalho agênticos autônomos, chamada de ferramentas e automação, arquiteturas RAG corporativas e integração escalável via API.) entregam excelente desempenho: Qwen3-Coder 30B-A3B Instruct lidera em inteligência geral e programação, Qwen3-Coder 30B-A3B Instruct oferece geração mais rápida e Qwen3-Coder 30B-A3B Instruct apresenta o melhor custo-benefício em produção.

Perguntas Frequentes (FAQ)

Qual é melhor para programação e raciocínio, Qwen3-Coder 30B-A3B Instruct ou Devstral Medium?+

Nas avaliações de inteligência e código, Qwen3-Coder 30B-A3B Instruct leva vantagem. Confira os gráficos SWE-bench e GPQA acima para detalhes.

Qual modelo tem a API mais barata, Qwen3-Coder 30B-A3B Instruct ou Devstral Medium?+

O Qwen3-Coder 30B-A3B Instruct custa $0.00 / $0.00 por 1M de tokens (entrada/saída) e o Devstral Medium custa $0.80 / $2.40. No custo combinado, Qwen3-Coder 30B-A3B Instruct é mais econômico.

Qual modelo possui maior janela de contexto e velocidade?+

O Qwen3-Coder 30B-A3B Instruct suporta 262.1K tokens de contexto contra 128K tokens do Devstral Medium, enquanto Qwen3-Coder 30B-A3B Instruct 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)

Qwen3-Coder 30B-A3B Instruct vs Devstral Medium

Troque e Compare Qualquer Modelo

Qwen3-Coder 30B-A3B Instruct

Devstral Medium

Quem vence em cada categoria?

Pontuações de Benchmarks Verificadas

Latência e Tempo de Resposta

Simulador Interativo de Custo de Tokens

Qwen3-Coder 30B-A3B Instruct · Strengths & Key Advantages

Considerations & Trade-offs

Devstral Medium · Strengths & Key Advantages

Considerations & Trade-offs

Token Use & Task Economics

Especificações Técnicas

Qwen3-Coder 30B-A3B Instruct vs Devstral Medium: Respostas Rápidas (FAQ)

Veredito

Perguntas Frequentes (FAQ)

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