Head-to-Head Model Comparison

Qwen3 Coder Plus vs Devstral Medium

Benchmarks, API Token Pricing, Context Window & Speed Comparison

由 GetInfoUs 研究团队审核最后审核日期:October 2026编辑政策
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AI CompareAI BenchmarkToken PricingModel CostModel SpecsSWE-bench CodingModel VersusWhich AI ModelLLM Speed & LatencyReasoning ModelsExtended ThinkingPrompt Caching ROI
Qwen3 Coder Plus vs Devstral Medium: Benchmarks, Pricing & Speed Comparison

Qwen3 Coder Plus by Alibaba and Devstral Medium by Mistral AI represent two of the frontier AI models analyzed in our comprehensive 2026 AI benchmark and LLM comparison. In this head-to-head evaluation, we examine API token pricing, context window specifications, inference speed (tokens per second), and empirical reasoning performance. From a pure economic perspective, both models offer identical input token rates. On output generation, Devstral Medium is more economical per million generated tokens. In data-heavy architectures requiring extensive repository or document analysis, Qwen3 Coder Plus provides an expanded memory horizon with 1,049K tokens. In latency-sensitive production environments, Qwen3 Coder Plus leads in tokens-per-second throughput, making it ideal for real-time conversational agents and high-concurrency workflows. Below is the complete empirical head-to-head breakdown across cost, speed, context, and capability matrices.

模型直接对比 (VS)

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Popular Matchups:
Alibaba

Qwen3 Coder Plus

深度推理模型

Alibaba 推出的 Qwen3 Coder Plus 人工智能模型,具备 1.0M 上下文窗口,输入价格为 $0.8/百万 Token,输出价格为 $3.2/百万 Token,专为高质量生产环境、推理与自动化工作流打造。

Intelligence Index85 / 100
Input Token:

$0.80 / 1M

Output Token:

$3.20 / 1M

Context Window:

1.05M tokens

SWE-bench Verified:

54%

Mistral AI

Devstral Medium

深度推理模型

Mistral AI 推出的 Devstral Medium 人工智能模型,具备 128K 上下文窗口,输入价格为 $0.8/百万 Token,输出价格为 $2.4/百万 Token,专为高质量生产环境、推理与自动化工作流打造。

Intelligence Index52 / 100
Input Token:

$0.80 / 1M

Output Token:

$2.40 / 1M

Context Window:

128K tokens

SWE-bench Verified:

51.5%

核心差异一览

  • Devstral Medium is 1.1x cheaper for API usage (input + output tokens combined).
  • Qwen3 Coder Plus has a larger context window (1M vs 128K tokens).
  • Qwen3 Coder Plus is faster at 80 tok/s vs 75 tok/s.
  • Qwen3 Coder Plus leads on SWE-bench coding (54.0% vs 51.5%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureQwen3 Coder PlusDevstral Medium
Intelligence Index
Composite reasoning & knowledge score (0-100)
8552
Provider
AlibabaMistral AI
Input Price
Cost per million input tokens
$0.80 / 1M$0.80 / 1M
Output Price
Cost per million output tokens
$3.20 / 1M$2.40 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$0.54 / 1M$0.54 / 1M
Context Window
Maximum input + output tokens
1.05M tokens~1,573 A4 pages of text128K tokens~192 A4 pages of text
Max Output Tokens
Per single request
16K33K
Throughput Speed
Tokens generated per second
80 tok/s75 tok/s
SWE-bench Verified
Real-world software engineering
54%51.5%
GPQA Diamond
Graduate-level reasoning
66.5%62%
Cached Input Price
Prompt caching discount per 1M tokens
$0.08 / 1M$0.20 / 1M

各项指标谁更胜一筹?

At-a-glance decision framework
Coding
Qwen3 Coder Plus
+2.5% SWE-bench lead
Cost
Devstral Medium
1.1x cheaper monthly runtime
Speed
Qwen3 Coder Plus
+7% faster generation
Context
Qwen3 Coder Plus
1.05M tokens window

权威基准测试得分对比

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

Qwen3 Coder PlusDevstral Medium
SWE-bench Verified (Autonomous Coding)

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

54%vs51.5%
GPQA Diamond (Doctorate-Level Science & Math)

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

66.5%vs62%
MMLU-Pro (Multi-task Language Understanding)

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

81%vs80.5%
LMSYS Chatbot Arena Elo

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

1340ptsvs1330pts
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.

71%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.

80 tok/s vs75 tok/s

延迟与响应速度

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 Plus0.51s
Devstral Medium0.50s
Est. End-to-End Response (500 tokens)TTFT + generation time
Qwen3 Coder Plus6.76s
Devstral Medium7.17s

实时 Token 成本模拟器

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)
Qwen3 Coder Plus Monthly API Bill
$4.20 / month
$0.8/1M in · $3.2/1M out
Devstral Medium Monthly API Bill
$3.66 / month
$0.8/1M in · $2.4/1M out
Devstral Medium saves approximately $0.54 / month (13%) under this workload.1.1x Savings

Qwen3 Coder Plus · Strengths & Key Advantages

  • 由 Alibaba 研发的高精度 Hosted Enterprise Code-Specialized Transformer 架构,支持 1.0M 上下文窗口
  • 极具竞争力的 API 定价(输入 $0.8/1M,输出 $3.2/1M),支持高速推理与工具调用
  • 在代码生成、逻辑推理与多语言处理基准测试中表现出色
Considerations & Trade-offs
  • 超长上下文请求需要规划 Token 成本与并发配额
  • 针对特定垂直领域任务建议结合系统提示词与检索增强(RAG)以获得最佳效果

Devstral Medium · Strengths & Key Advantages

  • 由 Mistral AI 研发的高精度 High-Capacity Agentic Code Transformer 架构,支持 128K 上下文窗口
  • 极具竞争力的 API 定价(输入 $0.8/1M,输出 $2.4/1M),支持高速推理与工具调用
  • 在代码生成、逻辑推理与多语言处理基准测试中表现出色
Considerations & Trade-offs
  • 超长上下文请求需要规划 Token 成本与并发配额
  • 针对特定垂直领域任务建议结合系统提示词与检索增强(RAG)以获得最佳效果

Token Use & Task Economics

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

MetricQwen3 Coder PlusDevstral Medium
Cost per Task
Estimated USD to finish one task
$0.22$0.55
Output Tokens / Task
Tokens generated per task
22K38K
Reasoning Tokens / Task
Thinking tokens burned per task
7K18K

技术规格参数

Architecture, release timeline, capabilities, and modalities.

FeatureQwen3 Coder PlusDevstral Medium
Official API Model ID (SDK)qwen3-coder-plus-instructdevstral-medium-latest
API ProtocolAlibaba REST API (OpenAI-Compatible)Mistral AI REST API (OpenAI-Compatible)
Release Date2025-072025-07
Knowledge CutoffMay 2025May 2025
ArchitectureHosted Enterprise Code-Specialized TransformerHigh-Capacity Agentic Code Transformer
ParametersConfidentialConfidential (~70B)
Enterprise Rate Limits (RPM / TPM)5,000 – 15,000 RPM (Production Tier) · 4,000,000 – 10,000,000 TPM5,000 – 15,000 RPM (Production Tier) · 800,000 – 2,000,000 TPM
Long-Context Tier (>128K/200K)Flat rate ($0.8/1M in) across full 1049K windowFlat rate ($0.8/1M in) across full 128K window
Prompt Cache Policy & TTLCached input at $0.08/1M tokensCached input at $0.2/1M 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 SupportAPI Prompt Engineering & RAG DistillationAPI Prompt Engineering & RAG Distillation
Multimodal Token BillingText BPE (~4 chars/token)Text BPE (~4 chars/token)
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 ClassificationAlibaba Production Safety & Alignment VerifiedMistral AI Production Safety & Alignment Verified
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 Modalitiestexttext
Output Modalitiestexttext

Qwen3 Coder Plus vs Devstral Medium: 常见问题解答 (FAQ)

Which is more intelligent, Qwen3 Coder Plus or Devstral Medium?

Qwen3 Coder Plus is more intelligent. It scores 85 compared with 52 on the composite Intelligence Index.

Which model is faster?

Qwen3 Coder Plus is faster, generating 80 tokens per second compared with 75 tokens per second.

Which model has lower latency?

Devstral Medium has lower latency, with a time to first token of 0.50s compared with 0.51s.

Which model has a larger context window?

Qwen3 Coder Plus has a larger context window, supporting 1.05M tokens compared with 128K tokens.

综合结论

Verdict & Model Selection Recommendation: Choose Qwen3 Coder Plus if your priority is Autonomous coding agents, full-repository refactoring, and complex bug remediation. Its performance in demanding tasks justifies its operational token cost. Choose Devstral Medium if your workflow prioritizes Autonomous bug-fixing bots, CI/CD pipeline automation, and enterprise repository refactoring. For large-scale batch processing or customer-facing conversational interfaces, its balance of speed and economics delivers superior ROI.

常见问题 (FAQ)

How does Qwen3 Coder Plus compare to Devstral Medium in API token pricing and cost per token?+

Qwen3 Coder Plus costs $0.80 per 1M input tokens and $3.20 per 1M output tokens, whereas Devstral Medium costs $0.80 input and $2.40 output. Overall, Devstral Medium is the more cost-effective model for high-volume API pipelines. Both models support prompt caching discounts of up to 90% for repeated prompt prefixes.

Which model has a larger context window: Qwen3 Coder Plus or Devstral Medium?+

Qwen3 Coder Plus supports a context window of 1,049K tokens (~786k words), while Devstral Medium supports 128K tokens (~96k words). Therefore, Qwen3 Coder Plus can process more textual data and document context in a single prompt.

Which AI model is better for software engineering and coding: Qwen3 Coder Plus or Devstral Medium?+

Qwen3 Coder Plus scores 54% on SWE-bench Verified while Devstral Medium scores 51.5%. For autonomous software engineering and multi-file debugging, Qwen3 Coder Plus holds the verified benchmark lead.

What is the difference in reasoning capability and extended thinking between Qwen3 Coder Plus and Devstral Medium?+

Qwen3 Coder Plus features native chain-of-thought extended thinking mode with configurable reasoning effort. In contrast, Devstral Medium provides chain-of-thought reasoning depth for complex math and science.

How does inference speed (tokens per second) compare between Qwen3 Coder Plus and Devstral Medium?+

Qwen3 Coder Plus generates approximately 80 tokens per second, while Devstral Medium delivers 75 tokens per second. In latency-sensitive production environments, Qwen3 Coder Plus provides faster time-to-first-token (TTFT) and higher streaming response velocity.

Can you implement a tiered LLM routing setup combining Qwen3 Coder Plus and Devstral Medium to optimize costs?+

Yes! High-efficiency architectures route high-frequency routine classification and conversational tasks to Devstral Medium to save operational costs, and dynamically escalate complex architectural queries or reasoning tasks to Qwen3 Coder Plus. This tiered routing pattern cuts overall API bills by up to 70%.

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.

数据来源: GetInfoUs Independent AI Benchmarks & Official API Specs