El modelo especialista en código de pesos abiertos más avanzado del mundo, rivalizando con GPT-4o en ingeniería de software.
Technical Specifications
- Provider
- Alibaba
- Category
- open-source
- Release Date
- 2024-11
- Batch API Discount
- 50% off async batch
- Consumer Subscription
- Free / Self-Hosted
- Reasoning Effort Control
- Fixed
- Structured Outputs
- Yes
- Output Modalities
- text
- Official Documentation
- Visit Official Docs ↗
Data Privacy, Licensing & Deployment Governance
Official Provider Release Intelligence, API Quotas & Agentic Specs
- Official API Model ID (SDK String)
- qwen-2-5-coder-32b-instruct
- Supported SDK & API Protocol
- OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI
- Lifecycle & Deprecation Status
- Legacy Stable (Upgrade path available in Alibaba lineup)
- Production Rate Limits (RPM & TPM)
- Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud
- Long-Context Pricing Tier (>128K / >200K)
- Flat rate ($0.2/1M in) across full 128K window
- Prompt Cache Write & TTL Policy
- Cached input at $0.04/1M tokens
- Computer Use & Browser GUI Agent
- 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
- Web Search Grounding & Code Sandbox
- Supported via external Tavily/Exa Search & E2B/Docker Sandbox tools
- Fine-Tuning & Distillation Support
- Full Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory)
- Multimodal Tokenization Billing
- Text BPE (~4 chars/token)
- Weights Precision & Quantization
- BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0)
- Minimum GPU VRAM Requirement
- 20 GB VRAM (4-bit Quantized) · 69 GB VRAM (Native BF16)
- Supported Inference Engines
- vLLM, SGLang, Ollama, llama.cpp, TensorRT-LLM, HuggingFace TGI
- System Card & Safety Framework
- Open-Weights System Card + Customizable Guardrail Layer (Llama Guard / ShieldGemma)
- Enterprise Compliance (SOC2 / HIPAA / ZDR)
- 100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 Control
Qwen 2.5 Coder 32B Cost, Context, Hardware & API Integration
Pay-as-you-go API is cheaper for this volume (saves $3.80/mo vs $20 flat plan).
Break-even point: ~617 requests/day equals $20/month.
Same Monthly Workload Cost Across Popular Reference Models
Live Prompt Paste Tokenizer & Cost Counter
Paste real system instructions, JSON schemas, or code to measure BPE token counts across tokenizers.
Hybrid Prompt Routing Cascade Simulator
Route routine queries to a fast lightweight model ($0.15/1M) and escalate only complex reasoning turns to Qwen 2.5 Coder 32B:
Benchmark Scores & 6-Axis Capability Radar
- SWE-bench Verified
- 48.6%
- GPQA Diamond
- 48.2%
- MMLU-Pro
- 68.9%
- HumanEval
- 92.7%
- Humanity's Last Exam
- 6.8%
- Terminal-Bench
- 32.4%
- SciCode
- 31.8%
- LiveCodeBench
- 53.2%
- AIME
- 55.4%
- Long-Context Reasoning
- 65.4%
- Chatbot Arena Elo
- 1268pts
Strengths
- Rendimiento de vanguardia en más de 90 lenguajes de programación
- Funciona fluidamente en una sola GPU de 24GB o 32GB con cuantización
- Capacidad superior para refactorización de repositorios completos
- Costo de inferencia en la nube sumamente asequible ($0.20/$0.40)
Limitations & Trade-offs
- Enfocado estrictamente en código y lógica; menos adaptado a prosa creativa
- Generación limitada a 8K tokens por turno
Editorial Assessment
El estándar absoluto para herramientas de desarrollo autoalojadas.
Best for: Autocompletado en IDE local, revisión automatizada de PR y agentes de desarrollo
Compare Qwen 2.5 Coder 32B
Frequently Asked Questions about Qwen 2.5 Coder 32B
How much does the Qwen 2.5 Coder 32B API cost per 1M tokens?+
Qwen 2.5 Coder 32B by Alibaba is priced at $0.2 per 1M input tokens and $0.6 per 1M output tokens. With prompt caching enabled, cached input tokens cost $0.04 per 1M tokens, and asynchronous Batch API requests receive a 50% discount.
Should I use a $20/month subscription or the Qwen 2.5 Coder 32B pay-as-you-go API?+
A flat $20/month consumer subscription is predictable for daily interactive chat and manual coding. However, if you are building software, running automated workflows, or sending low-to-moderate volume with prompt caching enabled, the pay-as-you-go API is typically far more cost-effective and offers higher rate limits without manual UI caps.
How many words and pages fit in Qwen 2.5 Coder 32B's context window?+
Qwen 2.5 Coder 32B features a 128K tokens context window, which equals approximately 96,000 English words or ~256 standard single-spaced pages in a single prompt. Its maximum output generation per turn is 8,192 tokens.
Can I run Qwen 2.5 Coder 32B locally on my own GPU (Open Weights)?+
Yes, Qwen 2.5 Coder 32B (32B) releases open weights that can be self-hosted locally or on private cloud GPUs using vLLM, Ollama, SGLang, or llama.cpp.
Does Alibaba train on data sent to the Qwen 2.5 Coder 32B API, and is commercial use allowed?+
100% Isolated when self-hosted on private GPUs or VPC. License tier: Permissive Open-Weights (Apache 2.0 / MIT Commercial). Full commercial ownership of generated outputs. Supported deployment channels include: Self-Hosted GPU (vLLM / Ollama), Private VPC, or Managed Serverless API.
How does Qwen 2.5 Coder 32B perform on coding and reasoning benchmarks?+
Qwen 2.5 Coder 32B achieves a composite Intelligence Index of 43/100, scoring 48.6% on SWE-bench Verified, 48.2% on GPQA Diamond, 68.9% on MMLU-Pro, and 1268 pts on Chatbot Arena Elo.
What is Qwen 2.5 Coder 32B best used for?+
Qwen 2.5 Coder 32B is best suited for: Autocompletado en IDE local, revisión automatizada de PR y agentes de desarrollo. Assessment: El estándar absoluto para herramientas de desarrollo autoalojadas.
Alibaba Family Lineage, Routing Tiers & Upgrade Path
Step down to a lighter sibling for high-volume routing or step up to Alibaba's flagship reasoning tier:
Qwen3.8 Max Preview
Qwen3.7 Plus
Qwen3.7 Max
Qwen3.6 Max Preview
Qwen3.6 Plus
Qwen3.6 Flash
AI Glossary & Architecture Concepts
View full glossary →Key machine learning concepts and benchmarks relevant to Qwen 2.5 Coder 32B:
La unidad básica de texto que procesa un modelo de lenguaje, que normalmente equivale a 3 o 4 caracteres o aproximadamente 0,75 palabras. Por ejemplo, una frase típica se divide en varios tokens.
Un conjunto estandarizado de pruebas para evaluar y comparar objetivamente las capacidades de distintos modelos de IA en tareas como programación (SWE-bench) o matemáticas avanzadas (AIME).
La cantidad máxima de tokens que un modelo puede considerar a la vez, incluyendo tanto la entrada que lee como la salida que genera. Una ventana de 1.000.000 de tokens puede procesar unas 750.000 palabras en una sola petición.
La capacidad de un modelo de detectar la necesidad de una función externa y emitir argumentos JSON estructurados para ejecutar API, búsquedas web o consultas a bases de datos.
Un protocolo abierto desarrollado por Anthropic que permite a los agentes de IA conectarse de forma estandarizada a sistemas de archivos locales, entornos de desarrollo y servicios externos.
Una optimización donde los proveedores almacenan estados de atención previos para prefijos de prompts frecuentes, reduciendo el coste de entrada hasta en un 90% y acelerando la respuesta.
Las puntuaciones de benchmarks, precios por token y límites de tasa evolucionan rápidamente. Verifique siempre las especificaciones actuales en la documentación oficial del proveedor.