dedicado 7B Arabic idioma edition optimizado para Middle Eastern empresarial búsqueda, cultural matiz, y soberano Arabic RAG.
Technical Specifications
- Provider
- Cohere
- Category
- open-source
- Release Date
- 2025-02
- 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)
- command-r7b-arabic
- Supported SDK & API Protocol
- OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI
- Lifecycle & Deprecation Status
- Active GA (Guaranteed support through 2027+)
- 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 ($0.07/1M in) across full 128K window
- Prompt Cache Write & TTL Policy
- Cached input at $0.02/1M 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
- 4 GB VRAM (4-bit Quantized) · 15 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
Command R7B Arabic Cost, Context, Hardware & API Integration
Pay-as-you-go API is cheaper for this volume (saves $14.30/mo vs $20 flat plan).
Break-even point: ~1,754 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 Command R7B Arabic:
Benchmark Scores & 6-Axis Capability Radar
- SWE-bench Verified
- 26%
- GPQA Diamond
- 43%
- MMLU-Pro
- 67%
- HumanEval
- 72%
- Long-Context Reasoning
- 70%
- Chatbot Arena Elo
- 1225pts
Strengths
- Unsurpassed Arabic grammar, dialectal comprensión, y cultural contexto
- completo 128K ventana de contexto para largo Arabic legal decrees y government records
- de pesos abiertos enabling soberano en-premise hosting en el GCC region
Limitations & Trade-offs
- Tailored specifically para Arabic; menos competitivo en pure English codificación tareas
- texto-solo sin nativo imagen visión features
Editorial Assessment
el leading de pesos abiertos Arabic RAG specialist tailored para regional empresarial cumplimiento.
Best for: Middle Eastern government digitization, Arabic empresarial búsqueda, y regional cliente soporte
Compare Command R7B Arabic
Frequently Asked Questions about Command R7B Arabic
How much does the Command R7B Arabic API cost per 1M tokens?+
Command R7B Arabic by Cohere is priced at $0.07 per 1M input tokens and $0.2 per 1M output tokens. With prompt caching enabled, cached input tokens cost $0.02 per 1M tokens, and asynchronous Batch API requests receive a 50% discount.
Should I use a $20/month subscription or the Command R7B Arabic 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 Command R7B Arabic's context window?+
Command R7B Arabic 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 4,096 tokens.
Can I run Command R7B Arabic locally on my own GPU (Open Weights)?+
Yes, Command R7B Arabic (7B) releases open weights that can be self-hosted locally or on private cloud GPUs using vLLM, Ollama, SGLang, or llama.cpp.
Does Cohere train on data sent to the Command R7B Arabic API, and is commercial use allowed?+
100% Isolated when self-hosted on private GPUs or VPC. License tier: Open-Weights Research & Commercial License. Full commercial ownership of generated outputs. Supported deployment channels include: Self-Hosted GPU (vLLM / Ollama), Private VPC, or Managed Serverless API.
How does Command R7B Arabic perform on coding and reasoning benchmarks?+
Command R7B Arabic achieves a composite Intelligence Index of 39/100, scoring 26% on SWE-bench Verified, 43% on GPQA Diamond, 67% on MMLU-Pro, and 1225 pts on Chatbot Arena Elo.
What is Command R7B Arabic best used for?+
Command R7B Arabic is best suited for: Middle Eastern government digitization, Arabic empresarial búsqueda, y regional cliente soporte. Assessment: el leading de pesos abiertos Arabic RAG specialist tailored para regional empresarial cumplimiento.
Cohere Family Lineage, Routing Tiers & Upgrade Path
Step down to a lighter sibling for high-volume routing or step up to Cohere's flagship reasoning tier:
North Mini Code
Command A Plus
Command A Reasoning
Command A Translate
Command A Vision
Command A
AI Glossary & Architecture Concepts
View full glossary →Key machine learning concepts and benchmarks relevant to Command R7B Arabic:
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.