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Aya Vision 32B vs DeepSeek-V3-0324

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Revisado por el equipo de investigación de GetInfoUsÚltima revisión: October 2026Política editorial
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AI CompareAI BenchmarkToken PricingModel CostModel SpecsSWE-bench CodingModel VersusWhich AI ModelLLM Speed & LatencyReasoning ModelsExtended ThinkingPrompt Caching ROI
Aya Vision 32B vs DeepSeek-V3-0324: Benchmarks, Pricing & Speed Comparison

Aya Vision 32B de Cohere y DeepSeek-V3-0324 de DeepSeek compiten directamente en el ecosistema actual de IA. Aya Vision 32B ofrece una ventana de contexto de 16K tokens a $0.35/$0.80 por millón de tokens (entrada/salida), mientras que DeepSeek-V3-0324 ofrece 128K tokens de contexto a $0.27/$1.10 por millón de tokens. Analizamos sus benchmarks, latencia y costos reales.

Comparación Directa (VS)

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Cohere

Aya Vision 32B

Modelo Multilingüe Global

Aya Vision 32B 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 75 tokens/s, índice de inteligencia de 45/100 y tarifa de

Intelligence Index45 / 100
Input Token:

$0.35 / 1M

Output Token:

$0.80 / 1M

Context Window:

16K tokens

SWE-bench Verified:

32%

DeepSeek

DeepSeek-V3-0324

Modelo Base de Pesos Abiertos

DeepSeek-V3-0324 de DeepSeek 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 65 tokens/s, índice de inteligencia de 48/100

Intelligence Index48 / 100
Input Token:

$0.27 / 1M

Output Token:

$1.10 / 1M

Context Window:

128K tokens

SWE-bench Verified:

52.4%

Diferencias Clave de un Vistazo

  • Aya Vision 32B is 1.1x cheaper for API usage (input + output tokens combined).
  • DeepSeek-V3-0324 has a larger context window (128K vs 16K tokens).
  • Aya Vision 32B is faster at 75 tok/s vs 65 tok/s.
  • DeepSeek-V3-0324 leads on SWE-bench coding (52.4% vs 32.0%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
CaracterísticaAya Vision 32BDeepSeek-V3-0324
Intelligence Index
Composite reasoning & knowledge score (0-100)
4548
Provider
CohereDeepSeek
Input Price
Cost per million input tokens
$0.35 / 1M$0.27 / 1M
Output Price
Cost per million output tokens
$0.80 / 1M$1.10 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$0.21 / 1M$0.21 / 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
4K8K
Throughput Speed
Tokens generated per second
75 tok/s65 tok/s
SWE-bench Verified
Real-world software engineering
32%52.4%
GPQA Diamond
Graduate-level reasoning
51.5%63.5%
Cached Input Price
Prompt caching discount per 1M tokens
$0.08 / 1M$0.07 / 1M

¿Quién gana en cada área?

At-a-glance decision framework
Código
DeepSeek-V3-0324
+20.4% SWE-bench lead
Costo
Aya Vision 32B
1.1x cheaper monthly runtime
Velocidad
Aya Vision 32B
+15% faster generation
Contexto
DeepSeek-V3-0324
128K tokens window

Puntuaciones de Benchmarks Verificadas

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

Aya Vision 32BDeepSeek-V3-0324
SWE-bench Verified (Autonomous Coding)

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

32%vs52.4%
GPQA Diamond (Doctorate-Level Science & Math)

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

51.5%vs63.5%
MMLU-Pro (Multi-task Language Understanding)

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

74%vs78.4%
LMSYS Chatbot Arena Elo

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

1280ptsvs1320pts
Humanity's Last Exam (Frontier Expert Knowledge)

Extremely difficult, closed-ended questions spanning the frontier of human expert knowledge.

N/Avs10.2%
Terminal-Bench (Agentic Coding & Terminal Use)

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

N/Avs34.8%
SciCode (Scientific Computing)

Research-grade coding problems drawn from real scientific and numerical workloads.

N/Avs32.1%
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

N/Avs54.8%
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/Avs71.5%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

75 tok/s vs65 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 32B0.48s
DeepSeek-V3-03240.65s
Est. End-to-End Response (500 tokens)TTFT + generation time
Aya Vision 32B7.15s
DeepSeek-V3-03248.34s

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 32B Monthly API Bill
$1.36 / month
$0.35/1M in · $0.8/1M out
DeepSeek-V3-0324 Monthly API Bill
$1.50 / month
$0.27/1M in · $1.1/1M out
Aya Vision 32B saves approximately $0.14 / month (9%) under this workload.1.1x Savings

Aya Vision 32B · Strengths & Key Advantages

  • Ventana de contexto de 16K con hasta 4K tokens de salida máxima (SWE-bench Verified 32% · GPQA Diamond 51.5%)
  • Rendimiento ágil de 75 tokens/segundo con latencia inicial (TTFT) de solo 480 ms
  • Pesos abiertos (32B) 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

DeepSeek-V3-0324 · Strengths & Key Advantages

  • Ventana de contexto de 128K con hasta 8K tokens de salida máxima (SWE-bench Verified 52.4% · GPQA Diamond 63.5%)
  • Rendimiento ágil de 65 tokens/segundo con latencia inicial (TTFT) de solo 650 ms
  • Pesos abiertos (671B (37B MoE)) 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 32BDeepSeek-V3-0324
Cost per Task
Estimated USD to finish one task
$0.22$0.18
Output Tokens / Task
Tokens generated per task
25K45K
Reasoning Tokens / Task
Thinking tokens burned per task
0K0K

Especificaciones Técnicas

Architecture, release timeline, capabilities, and modalities.

CaracterísticaAya Vision 32BDeepSeek-V3-0324
Official API Model ID (SDK)aya-vision-32bdeepseek-chat
API ProtocolOpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGIOpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI
Release Date2025-032025-03
Knowledge CutoffJanuary 2025January 2025
ArchitectureHigh-Capacity Multilingual VLM671B Mixture-of-Experts (37B active)
Parameters32B671B (37B active MoE)
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 ($0.35/1M in) across full 16K windowFlat rate ($0.27/1M in) across full 128K window
Prompt Cache Policy & TTLCached input at $0.08/1M tokensAutomatic prefix caching at $0.07/1M (no extra cache-write fee)
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) · 20 GB VRAM (4-bit Quantized) · 69 GB VRAM (Native BF16)BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 416 GB VRAM (4-bit Quantized) · 1443 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 32B vs DeepSeek-V3-0324: Respuestas Rápidas (FAQ)

Which is more intelligent, Aya Vision 32B or DeepSeek-V3-0324?

DeepSeek-V3-0324 is more intelligent. It scores 48 compared with 45 on the composite Intelligence Index.

Which model is faster?

Aya Vision 32B is faster, generating 75 tokens per second compared with 65 tokens per second.

Which model has lower latency?

Aya Vision 32B has lower latency, with a time to first token of 0.48s compared with 0.65s.

Which model has a larger context window?

DeepSeek-V3-0324 has a larger context window, supporting 128K tokens compared with 16K tokens.

Veredicto

Tanto Aya Vision 32B (Ideal para traducción multilingüe, comprensión intercultural y flujos de trabajo globales, sistemas RAG empresariales y automatización mediante API.) como DeepSeek-V3-0324 (Ideal para autoalojamiento en servidores propios, ajuste fino (fine-tuning) y soberanía de datos, sistemas RAG empresariales y automatización mediante API.) destacan en producción: DeepSeek-V3-0324 lidera en inteligencia general y programación, Aya Vision 32B ofrece mayor velocidad de generación de tokens y Aya Vision 32B resulta más rentable para cargas de trabajo API de alto volumen.

Preguntas frecuentes

¿Cuál es mejor para programación y razonamiento, Aya Vision 32B o DeepSeek-V3-0324?+

En las pruebas de inteligencia compuesta y resolución de código, DeepSeek-V3-0324 obtiene la ventaja. Puedes revisar la tabla SWE-bench y GPQA arriba para comparar cada métrica.

¿Cuánto cuesta la API de Aya Vision 32B frente a DeepSeek-V3-0324?+

Aya Vision 32B cuesta $0.35 / $0.80 por millón de tokens de entrada/salida, mientras que DeepSeek-V3-0324 cuesta $0.27 / $1.10. En costo combinado, Aya Vision 32B es la opción más económica.

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

Aya Vision 32B cuenta con 16K tokens de contexto frente a 128K tokens de DeepSeek-V3-0324. En velocidad de inferencia, Aya Vision 32B 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 DeepSeek, tarjetas de sistema y benchmarks independientes (2026).