GetInfoUs
Head-to-Head Model Comparison

Aya Vision 8B vs Command R7B Arabic

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Revisado por el equipo de investigación de GetInfoUsÚltima revisión: October 2026Política editorial
Compartir
Related topics (12)
AI CompareAI BenchmarkToken PricingModel CostModel SpecsSWE-bench CodingModel VersusWhich AI ModelLLM Speed & LatencyReasoning ModelsExtended ThinkingPrompt Caching ROI
Aya Vision 8B vs Command R7B Arabic: Benchmarks, Pricing & Speed Comparison

Aya Vision 8B de Cohere y Command R7B Arabic de Cohere compiten directamente en el ecosistema actual de IA. Aya Vision 8B ofrece una ventana de contexto de 16K tokens a $0.10/$0.25 por millón de tokens (entrada/salida), mientras que Command R7B Arabic ofrece 128K tokens de contexto a $0.07/$0.20 por millón de tokens. Analizamos sus benchmarks, latencia y costos reales.

Comparación Directa (VS)

Cambia y Compara Cualquier Modelo

Select any AI models from our verified benchmark database to generate live side-by-side matrices.

Profile
Profile
Multi-Model Arena Stack:
5-Model Matrix Workbench
Popular Matchups:
Cohere

Aya Vision 8B

Modelo Multilingüe Global

Aya Vision 8B de Cohere es un modelo de IA diseñado para traducción multilingüe, comprensión intercultural y flujos de trabajo globales, con ventana de contexto de 16K, velocidad de 110 tokens/s, índice de inteligencia de 38/100 y tarifa de

Intelligence Index38 / 100
Input Token:

$0.10 / 1M

Output Token:

$0.25 / 1M

Context Window:

16K tokens

SWE-bench Verified:

22%

Cohere

Command R7B Arabic

Modelo Base de Pesos Abiertos

Command R7B Arabic de Cohere es un modelo de IA diseñado para autoalojamiento en servidores propios, ajuste fino (fine-tuning) y soberanía de datos, con ventana de contexto de 128K, velocidad de 135 tokens/s, índice de inteligencia de 39/10

Intelligence Index39 / 100
Input Token:

$0.07 / 1M

Output Token:

$0.20 / 1M

Context Window:

128K tokens

SWE-bench Verified:

26%

Diferencias Clave de un Vistazo

  • Command R7B Arabic is 1.3x cheaper for API usage (input + output tokens combined).
  • Command R7B Arabic has a larger context window (128K vs 16K tokens).
  • Command R7B Arabic is faster at 135 tok/s vs 110 tok/s.
  • Command R7B Arabic leads on SWE-bench coding (26.0% vs 22.0%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
CaracterísticaAya Vision 8BCommand R7B Arabic
Intelligence Index
Composite reasoning & knowledge score (0-100)
3839
Provider
CohereCohere
Input Price
Cost per million input tokens
$0.10 / 1M$0.07 / 1M
Output Price
Cost per million output tokens
$0.25 / 1M$0.20 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$0.07 / 1M$0.05 / 1M
Context Window
Maximum input + output tokens
16K tokens~24 A4 pages of text128K tokens~192 A4 pages of text
Max Output Tokens
Per single request
4K4K
Throughput Speed
Tokens generated per second
110 tok/s135 tok/s
SWE-bench Verified
Real-world software engineering
22%26%
GPQA Diamond
Graduate-level reasoning
41%43%
Cached Input Price
Prompt caching discount per 1M tokens
$0.03 / 1M$0.02 / 1M

¿Quién gana en cada área?

At-a-glance decision framework
Código
Command R7B Arabic
+4.0% SWE-bench lead
Costo
Command R7B Arabic
1.3x cheaper monthly runtime
Velocidad
Command R7B Arabic
+23% faster generation
Contexto
Command R7B Arabic
128K tokens window

Puntuaciones de Benchmarks Verificadas

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

Aya Vision 8BCommand R7B Arabic
SWE-bench Verified (Autonomous Coding)

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

22%vs26%
GPQA Diamond (Doctorate-Level Science & Math)

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

41%vs43%
MMLU-Pro (Multi-task Language Understanding)

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

64%vs67%
LMSYS Chatbot Arena Elo

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

1220ptsvs1225pts
Long-Context Reasoning

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

N/Avs70%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

110 tok/s vs135 tok/s

Latencia y Tiempo de Respuesta

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
Aya Vision 8B0.35s
Command R7B Arabic0.31s
Est. End-to-End Response (500 tokens)TTFT + generation time
Aya Vision 8B4.90s
Command R7B Arabic4.01s

Simulador Interactivo de Costos de Tokens

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)
Aya Vision 8B Monthly API Bill
$0.42 / month
$0.1/1M in · $0.25/1M out
Command R7B Arabic Monthly API Bill
$0.32 / month
$0.07/1M in · $0.2/1M out
Command R7B Arabic saves approximately $0.10 / month (25%) under this workload.1.3x Savings

Aya Vision 8B · Strengths & Key Advantages

  • Ventana de contexto de 16K con hasta 4K tokens de salida máxima (SWE-bench Verified 22% · GPQA Diamond 41%)
  • Rendimiento ágil de 110 tokens/segundo con latencia inicial (TTFT) de solo 350 ms
  • Pesos abiertos (8B) listos para autoalojamiento local o en nube privada mediante vLLM y Ollama
Considerations & Trade-offs
  • Requiere infraestructura GPU dedicada con suficiente memoria VRAM para inferencia local sin cuantización
  • En demostraciones científicas extremas, los modelos de razonamiento pesado de gama alta ofrecen mayor profundidad

Command R7B Arabic · Strengths & Key Advantages

  • Ventana de contexto de 128K con hasta 4K tokens de salida máxima (SWE-bench Verified 26% · GPQA Diamond 43%)
  • Rendimiento ágil de 135 tokens/segundo con latencia inicial (TTFT) de solo 310 ms
  • Pesos abiertos (7B) listos para autoalojamiento local o en nube privada mediante vLLM y Ollama
Considerations & Trade-offs
  • Requiere infraestructura GPU dedicada con suficiente memoria VRAM para inferencia local sin cuantización
  • En demostraciones científicas extremas, los modelos de razonamiento pesado de gama alta ofrecen mayor profundidad

Token Use & Task Economics

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

MetricAya Vision 8BCommand R7B Arabic
Cost per Task
Estimated USD to finish one task
$0.06$0.05
Output Tokens / Task
Tokens generated per task
18K20K
Reasoning Tokens / Task
Thinking tokens burned per task
0K0K

Especificaciones Técnicas

Architecture, release timeline, capabilities, and modalities.

CaracterísticaAya Vision 8BCommand R7B Arabic
Official API Model ID (SDK)aya-vision-8bcommand-r7b-arabic
API ProtocolOpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGIOpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI
Release Date2025-032025-02
Knowledge CutoffJanuary 2025December 2024
ArchitectureMultilingual Vision-Language TransformerArabic-Specialized RAG Transformer
Parameters8B7B
Enterprise Rate Limits (RPM / TPM)Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed CloudUnlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud
Long-Context Tier (>128K/200K)Flat rate ($0.1/1M in) across full 16K windowFlat rate ($0.07/1M in) across full 128K window
Prompt Cache Policy & TTLCached input at $0.03/1M tokensCached input at $0.02/1M 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 SupportFull 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 BillingText BPE (~4 chars/token) · Vision (~258–765 tokens per image tile)Text BPE (~4 chars/token)
Quantization & Min GPU VRAMBF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 5 GB VRAM (4-bit Quantized) · 17 GB VRAM (Native BF16)BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 4 GB VRAM (4-bit Quantized) · 15 GB VRAM (Native BF16)
Safety & Frontier ClassificationOpen-Weights System Card + Customizable Guardrail Layer (Llama Guard / ShieldGemma)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 Control100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 Control
Input Modalitiestext, visiontext
Output Modalitiestexttext

Aya Vision 8B vs Command R7B Arabic: Respuestas Rápidas (FAQ)

Which is more intelligent, Aya Vision 8B or Command R7B Arabic?

Command R7B Arabic is more intelligent. It scores 39 compared with 38 on the composite Intelligence Index.

Which model is faster?

Command R7B Arabic is faster, generating 135 tokens per second compared with 110 tokens per second.

Which model is cheaper to run?

Command R7B Arabic is cheaper at $0.05 per 1M tokens blended, compared with $0.07 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Command R7B Arabic has lower latency, with a time to first token of 0.31s compared with 0.35s.

Which model has a larger context window?

Command R7B Arabic has a larger context window, supporting 128K tokens compared with 16K tokens.

Veredicto

Tanto Aya Vision 8B (Ideal para traducción multilingüe, comprensión intercultural y flujos de trabajo globales, sistemas RAG empresariales y automatización mediante API.) como Command R7B Arabic (Ideal para autoalojamiento en servidores propios, ajuste fino (fine-tuning) y soberanía de datos, sistemas RAG empresariales y automatización mediante API.) destacan en producción: Command R7B Arabic lidera en inteligencia general y programación, Command R7B Arabic ofrece mayor velocidad de generación de tokens y Command R7B Arabic resulta más rentable para cargas de trabajo API de alto volumen.

Preguntas frecuentes

¿Cuál es mejor para programación y razonamiento, Aya Vision 8B o Command R7B Arabic?+

En las pruebas de inteligencia compuesta y resolución de código, Command R7B Arabic obtiene la ventaja. Puedes revisar la tabla SWE-bench y GPQA arriba para comparar cada métrica.

¿Cuánto cuesta la API de Aya Vision 8B frente a Command R7B Arabic?+

Aya Vision 8B cuesta $0.10 / $0.25 por millón de tokens de entrada/salida, mientras que Command R7B Arabic cuesta $0.07 / $0.20. En costo combinado, Command R7B Arabic es la opción más económica.

¿Qué modelo tiene mayor ventana de contexto y menor latencia?+

Aya Vision 8B cuenta con 16K tokens de contexto frente a 128K tokens de Command R7B Arabic. En velocidad de inferencia, Command R7B Arabic ofrece un rendimiento superior.

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 & PricingContext WindowAI BenchmarksReasoning ModelsTool CallingModel Context Protocol (MCP)

Related reading

Las puntuaciones de benchmarks, precios por token y límites de tasa evolucionan rápidamente. Verifique siempre las especificaciones actuales en la documentación oficial del proveedor.

Fuentes: Documentación oficial de API de Cohere y Cohere, tarjetas de sistema y benchmarks independientes (2026).