Aya Vision 8B vs Gemini 4 Argon
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (4)
Compare Aya Vision 8B by Cohere against Gemini 4 Argon by Google across real-world coding, reasoning, token economics, and latency.
Cambia y Compara Cualquier Modelo
Select any AI models from our verified benchmark database to generate live side-by-side matrices.
Live comparison: no in-depth editorial review has been published for this pair yet.
Aya Vision 8B
Modelo Multilingüe GlobalAya 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
$0.10 / 1M
$0.25 / 1M
16K tokens
22%
Gemini 4 Argon
IA Multimodal NativaGemini 4 Argon de Google es un modelo de IA diseñado para comprensión multimodal nativa de texto e imagen y análisis visual de documentos, con ventana de contexto de 1M, velocidad de 115 tokens/s, índice de inteligencia de 97/100 y tarifa d
$2.00 / 1M
$10.00 / 1M
1M tokens
81.9%
Diferencias Clave de un Vistazo
- Aya Vision 8B is 28.9x cheaper for API usage (input + output tokens combined).
- Gemini 4 Argon has a larger context window (1M vs 16K tokens).
- Gemini 4 Argon is faster at 115 tok/s vs 110 tok/s.
- Gemini 4 Argon leads on SWE-bench coding (81.9% vs 22.0%).
| Característica | Aya Vision 8B | Gemini 4 Argon |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 38 | 97 |
Provider | Cohere | |
Input Price Cost per million input tokens | $0.10 / 1M | $2.00 / 1M |
Output Price Cost per million output tokens | $0.25 / 1M | $10.00 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $0.07 / 1M | $1.47 / 1M |
Context Window Maximum input + output tokens | 16K tokens~24 A4 pages of text | 1M tokens~1,500 A4 pages of text |
Max Output Tokens Per single request | 4K | 1000K |
Throughput Speed Tokens generated per second | 110 tok/s | 115 tok/s |
SWE-bench Verified Real-world software engineering | 22% | 81.9% |
GPQA Diamond Graduate-level reasoning | 41% | 81.5% |
Cached Input Price Prompt caching discount per 1M tokens | $0.03 / 1M | $0.10 / 1M |
¿Quién gana en cada área?
At-a-glance decision frameworkPuntuaciones de Benchmarks Verificadas
Official evaluation metrics verified by independent third-party research labs.
Industry benchmark evaluating real-world GitHub issue resolution and multi-file debugging.
Challenging questions created by domain experts to test complex PhD-level reasoning.
Hardened reasoning and academic knowledge benchmark with reduced lucky-guess probability.
Crowdsourced human preference evaluation based on blind, head-to-head model battles.
Extremely difficult, closed-ended questions spanning the frontier of human expert knowledge.
Autonomous multi-step tasks executed inside a real command-line terminal environment.
Research-grade coding problems drawn from real scientific and numerical workloads.
Contamination-free competitive programming problems collected continuously over time.
American Invitational Mathematics Examination — multi-step Olympiad-level reasoning.
Accuracy when reasoning over very large inputs that fill the model context window.
Tokens emitted per second during active generation streaming.
Latencia y Tiempo de Respuesta
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
Simulador Interactivo de Costos de Tokens
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
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
Gemini 4 Argon · Strengths & Key Advantages
- Ventana de contexto de 1M con hasta 1M tokens de salida máxima (SWE-bench Verified 81.9% · GPQA Diamond 81.5%)
- Rendimiento ágil de 115 tokens/segundo con latencia inicial (TTFT) de solo 850 ms
- Economía de API competitiva ($2/$10 por 1M de tokens) con soporte para caché de prompts y salidas JSON estructuradas
Considerations & Trade-offs
- Modelo propietario en la nube; no permite descargar los pesos para ejecución local sin conexión
- En volúmenes masivos de tokens, se recomienda activar el caché de prompts y Batch API para optimizar costos
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | Aya Vision 8B | Gemini 4 Argon |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.06 | $2.45 |
Output Tokens / Task Tokens generated per task | 18K | 75K |
Reasoning Tokens / Task Thinking tokens burned per task | 0K | 36K |
Especificaciones Técnicas
Architecture, release timeline, capabilities, and modalities.
| Característica | Aya Vision 8B | Gemini 4 Argon |
|---|---|---|
| Official API Model ID (SDK) | aya-vision-8b | models/gemini-4-argon |
| API Protocol | OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI | Google Gemini API (generateContent) + OpenAI-Compatible SDK |
| Release Date | 2025-03 | 2026-09 |
| Knowledge Cutoff | January 2025 | June 2026 |
| Architecture | Multilingual Vision-Language Transformer | Pathways Multimodal Sparse Mixture-of-Experts |
| Parameters | 8B | Confidential |
| Enterprise Rate Limits (RPM / TPM) | Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud | 10,000 – 30,000 RPM (Tier 5 Enterprise) · 4,000,000 – 10,000,000 TPM |
| Long-Context Tier (>128K/200K) | Flat rate ($0.1/1M in) across full 16K window | Standard rate up to 200K tokens; 2x input/output tier above 200K tokens |
| Prompt Cache Policy & TTL | Cached input at $0.03/1M tokens | Implicit + Explicit Context Caching at $0.1/1M with configurable TTL |
| Computer Use / GUI Agent | API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop) | Supported (Screen coordinate grounding, browser & desktop GUI action loops) |
| MCP & Parallel Tool Calling | Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema | Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema |
| Web Search Grounding & Sandbox | Supported via external Tavily/Exa Search & E2B/Docker Sandbox tools | Built-in Google Search Grounding + Managed Python Code Execution Sandbox |
| Official Fine-Tuning Support | Full Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory) | Vertex AI Supervised Adapter Tuning & Context Distillation |
| Multimodal Token Billing | Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) | Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) · Audio (~25–32 tokens/sec) · Video (~258–300 tokens/sec) |
| Quantization & Min GPU VRAM | BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 5 GB VRAM (4-bit Quantized) · 17 GB VRAM (Native BF16) | Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API) |
| Safety & Frontier Classification | Open-Weights System Card + Customizable Guardrail Layer (Llama Guard / ShieldGemma) | Google DeepMind Frontier Safety Framework Verified |
| Enterprise Compliance (ZDR/HIPAA/SOC2) | 100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 Control | SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier |
| Input Modalities | text, vision | text, vision, audio, video |
| Output Modalities | text | text |
Aya Vision 8B vs Gemini 4 Argon: Respuestas Rápidas (FAQ)
Which is more intelligent, Aya Vision 8B or Gemini 4 Argon?
Gemini 4 Argon is more intelligent. It scores 97 compared with 38 on the composite Intelligence Index.
Which model is faster?
Gemini 4 Argon is faster, generating 115 tokens per second compared with 110 tokens per second.
Which model is cheaper to run?
Aya Vision 8B is cheaper at $0.07 per 1M tokens blended, compared with $1.47 (7:2:1 cache:input:output ratio).
Which model has lower latency?
Aya Vision 8B has lower latency, with a time to first token of 0.35s compared with 0.85s.
Which model has a larger context window?
Gemini 4 Argon has a larger context window, supporting 1M tokens compared with 16K tokens.
Veredicto
Choose Aya Vision 8B for ideal para traducción multilingüe, comprensión intercultural y flujos de trabajo globales, sistemas rag empresariales y automatización mediante api., or choose Gemini 4 Argon for ideal para comprensión multimodal nativa de texto e imagen y análisis visual de documentos, sistemas rag empresariales y automatización mediante api..
Preguntas frecuentes
Which is cheaper: Aya Vision 8B or Gemini 4 Argon?+
Aya Vision 8B costs $0.1/1M input and $0.25/1M output tokens, while Gemini 4 Argon costs $2/1M input and $10/1M output tokens.
Which model has a larger context window: Aya Vision 8B or Gemini 4 Argon?+
Aya Vision 8B supports 16K tokens whereas Gemini 4 Argon supports 1M tokens.
Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.
Related reading
- Aion-3.0 vs. Aion-Mini: Comparativa de Benchmarks, Precios API y Velocidad (2026)Comparar
- Aion-3.0 vs. Gemini 3.6 Flash: Comparativa de Benchmarks, Precios API y Velocidad (2026)Comparar
- Aion-Mini vs. Laguna XS 2.1: Comparativa de Benchmarks, Precios API y Velocidad (2026)Comparar
- Aya Expanse 32B vs. Llama 3.2 90B Vision: Comparativa de Benchmarks, Precios API y Velocidad (2026)Comparar
- Aya Expanse 8B vs. Command R+: Comparativa de Benchmarks, Precios API y Velocidad (2026)Comparar
- Aya Expanse 8B vs. Qwen 2.5 7B Instruct: Comparativa de Benchmarks, Precios API y Velocidad (2026)Comparar
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: Cohere & Google Official Documentation