Aya Vision 32B vs DeepSeek-V3-0324
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (12)
Aya Vision 32B da Cohere e DeepSeek-V3-0324 da DeepSeek são dois modelos de IA de destaque. O Aya Vision 32B oferece uma janela de contexto de 16K tokens a $0.35/$0.80 por milhão de tokens, enquanto o DeepSeek-V3-0324 oferece 128K tokens de contexto a $0.27/$1.10 por milhão de tokens. Veja abaixo a comparação completa de benchmarks, latência e custos.
Troque e Compare Qualquer Modelo
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Aya Vision 32B
Modelo Multilíngue GlobalO Aya Vision 32B da Cohere é um modelo de IA projetado para tradução multilíngue precisa, análise transcultural e fluxos globais, oferecendo janela de contexto de 16K, velocidade de 75 tokens/s, índice de inteligência de 45/100 e tarifa de
$0.35 / 1M
$0.80 / 1M
16K tokens
32%
DeepSeek-V3-0324
Modelo Base de Pesos AbertosO DeepSeek-V3-0324 da DeepSeek é um modelo de IA projetado para auto-hospedagem em infraestrutura própria, fine-tuning e soberania de dados, oferecendo janela de contexto de 128K, velocidade de 65 tokens/s, índice de inteligência de 48/100
$0.27 / 1M
$1.10 / 1M
128K tokens
52.4%
Principais Diferenças em Resumo
- 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%).
| Feature | Aya Vision 32B | DeepSeek-V3-0324 |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 45 | 48 |
Provider | Cohere | DeepSeek |
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 text | 128K tokens~192 A4 pages of text |
Max Output Tokens Per single request | 4K | 8K |
Throughput Speed Tokens generated per second | 75 tok/s | 65 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 |
Quem vence em cada categoria?
At-a-glance decision frameworkPontuações 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.
Latência e Tempo de Resposta
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
Simulador Interativo de Custo de Tokens
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
Aya Vision 32B · Strengths & Key Advantages
- Janela de contexto de 16K com limite máximo de saída de 4K tokens (SWE-bench Verified 32% · GPQA Diamond 51.5%)
- Taxa de transferência rápida de 75 tokens/segundo com latência inicial (TTFT) de 480 ms
- Pesos abertos (32B) para auto-hospedagem local ou em nuvem privada via vLLM, SGLang ou Ollama
Considerations & Trade-offs
- Requer servidores GPU com memória VRAM adequada para execução local em precisão total
- Em derivações científicas extremas, modelos pesados dedicados exclusivamente ao raciocínio oferecem maior profundidade
DeepSeek-V3-0324 · Strengths & Key Advantages
- Janela de contexto de 128K com limite máximo de saída de 8K tokens (SWE-bench Verified 52.4% · GPQA Diamond 63.5%)
- Taxa de transferência rápida de 65 tokens/segundo com latência inicial (TTFT) de 650 ms
- Pesos abertos (671B (37B MoE)) para auto-hospedagem local ou em nuvem privada via vLLM, SGLang ou Ollama
Considerations & Trade-offs
- Requer servidores GPU com memória VRAM adequada para execução local em precisão total
- Em derivações científicas extremas, modelos pesados dedicados exclusivamente ao raciocínio oferecem maior profundidade
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | Aya Vision 32B | DeepSeek-V3-0324 |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.22 | $0.18 |
Output Tokens / Task Tokens generated per task | 25K | 45K |
Reasoning Tokens / Task Thinking tokens burned per task | 0K | 0K |
Especificações Técnicas
Architecture, release timeline, capabilities, and modalities.
| Feature | Aya Vision 32B | DeepSeek-V3-0324 |
|---|---|---|
| Official API Model ID (SDK) | aya-vision-32b | deepseek-chat |
| API Protocol | OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI | OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI |
| Release Date | 2025-03 | 2025-03 |
| Knowledge Cutoff | January 2025 | January 2025 |
| Architecture | High-Capacity Multilingual VLM | 671B Mixture-of-Experts (37B active) |
| Parameters | 32B | 671B (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 Cloud | Unlimited (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 window | Flat rate ($0.27/1M in) across full 128K window |
| Prompt Cache Policy & TTL | Cached input at $0.08/1M tokens | Automatic prefix caching at $0.07/1M (no extra cache-write fee) |
| Computer Use / GUI Agent | API / 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 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 | Supported via external Tavily/Exa Search & E2B/Docker Sandbox tools |
| Official Fine-Tuning Support | Full 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 Billing | Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) | Text BPE (~4 chars/token) |
| Quantization & Min GPU VRAM | BF16 / 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 Classification | Open-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 Control | 100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 Control |
| Input Modalities | text, vision | text |
| Output Modalities | text | text |
Aya Vision 32B vs DeepSeek-V3-0324: Respostas 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.
Veredito
Tanto Aya Vision 32B (Indicado para tradução multilíngue precisa, análise transcultural e fluxos globais, arquiteturas RAG corporativas e integração escalável via API.) quanto DeepSeek-V3-0324 (Indicado para auto-hospedagem em infraestrutura própria, fine-tuning e soberania de dados, arquiteturas RAG corporativas e integração escalável via API.) entregam excelente desempenho: DeepSeek-V3-0324 lidera em inteligência geral e programação, Aya Vision 32B oferece geração mais rápida e Aya Vision 32B apresenta o melhor custo-benefício em produção.
Perguntas Frequentes (FAQ)
Qual é melhor para programação e raciocínio, Aya Vision 32B ou DeepSeek-V3-0324?+
Nas avaliações de inteligência e código, DeepSeek-V3-0324 leva vantagem. Confira os gráficos SWE-bench e GPQA acima para detalhes.
Qual modelo tem a API mais barata, Aya Vision 32B ou DeepSeek-V3-0324?+
O Aya Vision 32B custa $0.35 / $0.80 por 1M de tokens (entrada/saída) e o DeepSeek-V3-0324 custa $0.27 / $1.10. No custo combinado, Aya Vision 32B é mais econômico.
Qual modelo possui maior janela de contexto e velocidade?+
O Aya Vision 32B suporta 16K tokens de contexto contra 128K tokens do DeepSeek-V3-0324, enquanto Aya Vision 32B entrega maior velocidade de geração.
Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.
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Benchmark scores, token prices, and rate limits evolve rapidly as AI labs release model updates. Always verify current specifications and pricing on the official provider documentation.
Fontes oficiais: Documentação oficial de API da Cohere e DeepSeek e benchmarks independentes (2026).