Command A vs Aya Vision 32B
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (12)
Command A by Cohere and Aya Vision 32B by Cohere represent two of the frontier AI models analyzed in our comprehensive 2026 AI benchmark and LLM comparison. In this head-to-head evaluation, we examine API token pricing, context window specifications, inference speed (tokens per second), and empirical reasoning performance. From a pure economic perspective, Aya Vision 32B holds a notable pricing advantage for token ingestion. On output generation, Aya Vision 32B is more economical per million generated tokens. In data-heavy architectures requiring extensive repository or document analysis, Command A provides an expanded memory horizon with 256K tokens. In latency-sensitive production environments, Aya Vision 32B leads in tokens-per-second throughput, making it ideal for real-time conversational agents and high-concurrency workflows. Below is the complete empirical head-to-head breakdown across cost, speed, context, and capability matrices.
Changez et Comparez les Modèles
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Command A
Agent d'entreprisecommercial phare agent modèle intégrant 256K contexte, hardened multi-étapes outil exécution, et souverain déploiement support.
$2.50 / 1M
$10.00 / 1M
256K tokens
46%
Aya Vision 32B
VLM multilingueélevé-capacité 32B multilingue modèle de vision offrant profond visuel raisonnement, diagram analyse, et rich document compréhension à travers 23 langues.
$0.35 / 1M
$0.80 / 1M
16K tokens
32%
Différences Clés en un Coup d’Œil
- Aya Vision 32B is 10.2x cheaper for API usage (input + output tokens combined).
- Command A has a larger context window (256K vs 16K tokens).
- Aya Vision 32B is faster at 75 tok/s vs 70 tok/s.
- Command A leads on SWE-bench coding (46.0% vs 32.0%).
| Caractéristique | Command A | Aya Vision 32B |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 51 | 45 |
Provider | Cohere | Cohere |
Input Price Cost per million input tokens | $2.50 / 1M | $0.35 / 1M |
Output Price Cost per million output tokens | $10.00 / 1M | $0.80 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $2.02 / 1M | $0.21 / 1M |
Context Window Maximum input + output tokens | 256K tokens~384 A4 pages of text | 16K tokens~24 A4 pages of text |
Max Output Tokens Per single request | 16K | 4K |
Throughput Speed Tokens generated per second | 70 tok/s | 75 tok/s |
SWE-bench Verified Real-world software engineering | 46% | 32% |
GPQA Diamond Graduate-level reasoning | 61% | 51.5% |
Cached Input Price Prompt caching discount per 1M tokens | $0.75 / 1M | $0.08 / 1M |
Qui gagne où ?
At-a-glance decision frameworkScores de Benchmarks Vérifiés
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.
Autonomous multi-step tasks executed inside a real command-line terminal environment.
Accuracy when reasoning over very large inputs that fill the model context window.
Tokens emitted per second during active generation streaming.
Latence et Temps de Réponse
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
Simulateur Interactif de Coût de Tokens
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
Command A · Strengths & Key Advantages
- Engineered specifically pour autonome d'entreprise agents et fiable multi-outil chaining
- Expansive 256K fenêtre de contexte avec élevé needle-dans-un-haystack retention
- d'entreprise-grade privacy guarantees avec sur-premise déploiement options
Considerations & Trade-offs
- Premium tarification ($2.50/$10.00) par rapport à économique commodity modèles
- texte-seulement sans natif image vision features
Aya Vision 32B · Strengths & Key Advantages
- profond multilingue diagram, graphique, et technique dessin technique compréhension
- Significantly supérieur précision sur complexe visuel question answering à travers 23 langues
- à poids ouverts available pour privé d'entreprise hosting
Considerations & Trade-offs
- 16K contexte limit nécessite chunking pour massif multi-page documents
- vidéo streams pas supported
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | Command A | Aya Vision 32B |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.75 | $0.22 |
Output Tokens / Task Tokens generated per task | 38K | 25K |
Reasoning Tokens / Task Thinking tokens burned per task | 0K | 0K |
Spécifications Techniques
Architecture, release timeline, capabilities, and modalities.
| Caractéristique | Command A | Aya Vision 32B |
|---|---|---|
| Official API Model ID (SDK) | command-a | aya-vision-32b |
| 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 | Agentic Enterprise Transformer | High-Capacity Multilingual VLM |
| Parameters | Confidential (~100B+) | 32B |
| 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 ($2.5/1M in) across full 256K window | Flat rate ($0.35/1M in) across full 16K window |
| Prompt Cache Policy & TTL | Cached input at $0.75/1M tokens | Cached input at $0.08/1M tokens |
| 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) | Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) |
| Quantization & Min GPU VRAM | BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 62 GB VRAM (4-bit Quantized) · 215 GB VRAM (Native BF16) | BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 20 GB VRAM (4-bit Quantized) · 69 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 | text, vision |
| Output Modalities | text | text |
Command A vs Aya Vision 32B: Réponses Rapides (FAQ)
Which is more intelligent, Command A or Aya Vision 32B?
Command A is more intelligent. It scores 51 compared with 45 on the composite Intelligence Index.
Which model is faster?
Aya Vision 32B is faster, generating 75 tokens per second compared with 70 tokens per second.
Which model is cheaper to run?
Aya Vision 32B is cheaper at $0.21 per 1M tokens blended, compared with $2.02 (7:2:1 cache:input:output ratio).
Which model has lower latency?
Aya Vision 32B has lower latency, with a time to first token of 0.48s compared with 0.52s.
Which model has a larger context window?
Command A has a larger context window, supporting 256K tokens compared with 16K tokens.
Verdict
Verdict & Model Selection Recommendation: Choose Command A if your priority is Enterprise autonomous agents, multi-step ERP workflows, and secure corporate automation. Its performance in demanding tasks justifies its operational token cost. Choose Aya Vision 32B if your workflow prioritizes International patent document inspection, global medical chart OCR, and multilingual enterprise analytics. For large-scale batch processing or customer-facing conversational interfaces, its balance of speed and economics delivers superior ROI.
Questions fréquentes
How does Command A compare to Aya Vision 32B in API token pricing and cost per token?+
Command A costs $2.50 per 1M input tokens and $10.00 per 1M output tokens, whereas Aya Vision 32B costs $0.35 input and $0.80 output. Overall, Aya Vision 32B is the more cost-effective model for high-volume API pipelines. Both models support prompt caching discounts of up to 90% for repeated prompt prefixes.
Which model has a larger context window: Command A or Aya Vision 32B?+
Command A supports a context window of 256K tokens (~192k words), while Aya Vision 32B supports 16K tokens (~12k words). Therefore, Command A can process more textual data and document context in a single prompt.
Which AI model is better for software engineering and coding: Command A or Aya Vision 32B?+
Command A scores 46% on SWE-bench Verified while Aya Vision 32B scores 32%. For autonomous software engineering and multi-file debugging, Command A holds the verified benchmark lead.
What is the difference in reasoning capability and extended thinking between Command A and Aya Vision 32B?+
Command A is optimized for low-latency direct generation. In contrast, Aya Vision 32B focuses on standard fast inference.
How does inference speed (tokens per second) compare between Command A and Aya Vision 32B?+
Command A generates approximately 70 tokens per second, while Aya Vision 32B delivers 75 tokens per second. In latency-sensitive production environments, Aya Vision 32B provides faster time-to-first-token (TTFT) and higher streaming response velocity.
Can you implement a tiered LLM routing setup combining Command A and Aya Vision 32B to optimize costs?+
Yes! High-efficiency architectures route high-frequency routine classification and conversational tasks to Aya Vision 32B to save operational costs, and dynamically escalate complex architectural queries or reasoning tasks to Command A. This tiered routing pattern cuts overall API bills by up to 70%.
Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.
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Les scores de benchmarks, tarifs par token et limites évoluent rapidement. Vérifiez toujours les spécifications actuelles sur la documentation officielle du fournisseur.
Sources: GetInfoUs Independent AI Benchmarks & Official API Specs