Command A Plus vs Claude Opus 5.5
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (12)
Command A Plus by Cohere and Claude Opus 5.5 by Anthropic 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, Command A Plus holds a notable pricing advantage for token ingestion. On output generation, Command A Plus is more economical per million generated tokens. In data-heavy architectures requiring extensive repository or document analysis, Claude Opus 5.5 provides an expanded memory horizon with 1,000K tokens. In latency-sensitive production environments, Claude Opus 5.5 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 Plus
Command plus puissantde Cohere de référence 2026 multimodal phare moteur uniting visuel document raisonnement, profond chaîne de pensée, et souverain d'entreprise déploiement.
$3.00 / 1M
$12.00 / 1M
128K tokens
60.5%
Claude Opus 5.5
Titan d'intelligence de pointed'Anthropic pinnacle modèle de pointe conçu pour à long terme agentic ingénierie logicielle, dense multimodal document synthèse, et autonome recherche flux de travail.
$4.00 / 1M
$20.00 / 1M
1M tokens
84.6%
Différences Clés en un Coup d’Œil
- Command A Plus is 1.5x cheaper for API usage (input + output tokens combined).
- Claude Opus 5.5 has a larger context window (1M vs 128K tokens).
- Claude Opus 5.5 is faster at 78 tok/s vs 68 tok/s.
- Claude Opus 5.5 leads on SWE-bench coding (84.6% vs 60.5%).
| Caractéristique | Command A Plus | Claude Opus 5.5 |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 58 | 94 |
Provider | Cohere | Anthropic |
Input Price Cost per million input tokens | $3.00 / 1M | $4.00 / 1M |
Output Price Cost per million output tokens | $12.00 / 1M | $20.00 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $2.33 / 1M | $3.08 / 1M |
Context Window Maximum input + output tokens | 128K tokens~192 A4 pages of text | 1M tokens~1,500 A4 pages of text |
Max Output Tokens Per single request | 33K | 128K |
Throughput Speed Tokens generated per second | 68 tok/s | 78 tok/s |
SWE-bench Verified Real-world software engineering | 60.5% | 84.6% |
GPQA Diamond Graduate-level reasoning | 74% | 82.3% |
Cached Input Price Prompt caching discount per 1M tokens | $0.75 / 1M | $0.40 / 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.
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.
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 Plus · Strengths & Key Advantages
- de Cohere la plupart puissant modèle de fondation à date, blending vision, raisonnement, et agents
- Flawless récupération ancrage avec strict anti-hallucination citations vérification
- à poids ouverts availability pour souverain national et regulated d'entreprise déploiements
Considerations & Trade-offs
- Premium API token tarification ($3.00/$12.00)
- élevé matériel requirements pour local cluster auto-hébergement
Claude Opus 5.5 · Strengths & Key Advantages
- inégalé autonome multi-étapes codage agentique et refactorisation
- Flawless multidocument raisonnement sur 1M token contexte avec no long-prompt surcharge
- le plus élevé Artificial analyse intelligence Index ever measured (58/100), leading SWE-bench Pro à 89.9%
- Precise outil exécution avec robust error-recovery boucles
Considerations & Trade-offs
- Premium sortie tarification ($20.00/M) plus heavy raisonnement-token usage (~119K sortie tokens par index tâche) keeps long agentic fonctionne expensive
- long pensée times à maximum effort peut push un unique hard agentic tâche toward ~$13
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | Command A Plus | Claude Opus 5.5 |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.85 | $3.85 |
Output Tokens / Task Tokens generated per task | 45K | 68K |
Reasoning Tokens / Task Thinking tokens burned per task | 22K | 42K |
Spécifications Techniques
Architecture, release timeline, capabilities, and modalities.
| Caractéristique | Command A Plus | Claude Opus 5.5 |
|---|---|---|
| Official API Model ID (SDK) | command-a-plus | claude-opus-5-5-20260901 |
| API Protocol | OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI | Anthropic Messages API + AWS Bedrock + Vertex AI |
| Release Date | 2026-05 | 2026-09 |
| Knowledge Cutoff | March 2026 | June 2026 |
| Architecture | Flagship Multimodal Agentic MoE | Extended Autonomous Hybrid Reasoning Transformer |
| Parameters | Confidential (~180B+ MoE) | Confidential |
| Enterprise Rate Limits (RPM / TPM) | Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud | 4,000 – 10,000 RPM (Tier 4 + Priority Tier) · 4,000,000 – 10,000,000 TPM |
| Long-Context Tier (>128K/200K) | Flat rate ($3/1M in) across full 128K window | Standard rate up to 200K tokens; 2x input/output tier above 200K tokens |
| Prompt Cache Policy & TTL | Cached input at $0.75/1M tokens | $0.4/1M cached read (90% off); 5-min default & 1-hour extended 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 | Native Web Search Citations + Code Execution Tool + MCP Connectors |
| Official Fine-Tuning Support | Full Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory) | Custom Model Tuning via Amazon Bedrock & Prompt 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) |
| Quantization & Min GPU VRAM | BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 112 GB VRAM (4-bit Quantized) · 387 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) | Anthropic RSP ASL-2 / ASL-3 Constitutional Safety Evaluated |
| 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 |
| Output Modalities | text | text |
Command A Plus vs Claude Opus 5.5: Réponses Rapides (FAQ)
Which is more intelligent, Command A Plus or Claude Opus 5.5?
Claude Opus 5.5 is more intelligent. It scores 94 compared with 58 on the composite Intelligence Index.
Which model is faster?
Claude Opus 5.5 is faster, generating 78 tokens per second compared with 68 tokens per second.
Which model is cheaper to run?
Command A Plus is cheaper at $2.33 per 1M tokens blended, compared with $3.08 (7:2:1 cache:input:output ratio).
Which model has lower latency?
Command A Plus has lower latency, with a time to first token of 0.56s compared with 1.40s.
Which model has a larger context window?
Claude Opus 5.5 has a larger context window, supporting 1M tokens compared with 128K tokens.
Verdict
Verdict & Model Selection Recommendation: Choose Command A Plus if your priority is Enterprise intelligence platforms, sovereign government automation, and mission-critical agent workflows. Its performance in demanding tasks justifies its operational token cost. Choose Claude Opus 5.5 if your workflow prioritizes Large-scale software development agents, enterprise codebases, and mission-critical scientific synthesis. 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 Plus compare to Claude Opus 5.5 in API token pricing and cost per token?+
Command A Plus costs $3.00 per 1M input tokens and $12.00 per 1M output tokens, whereas Claude Opus 5.5 costs $4.00 input and $20.00 output. Overall, Command A Plus 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 Plus or Claude Opus 5.5?+
Command A Plus supports a context window of 128K tokens (~96k words), while Claude Opus 5.5 supports 1,000K tokens (~750k words). Therefore, Claude Opus 5.5 can process more textual data and document context in a single prompt.
Which AI model is better for software engineering and coding: Command A Plus or Claude Opus 5.5?+
Command A Plus scores 60.5% on SWE-bench Verified while Claude Opus 5.5 scores 84.6%. For autonomous software engineering and multi-file debugging, Claude Opus 5.5 holds the verified benchmark lead.
What is the difference in reasoning capability and extended thinking between Command A Plus and Claude Opus 5.5?+
Command A Plus features native chain-of-thought extended thinking mode with configurable reasoning effort. In contrast, Claude Opus 5.5 provides chain-of-thought reasoning depth for complex math and science.
How does inference speed (tokens per second) compare between Command A Plus and Claude Opus 5.5?+
Command A Plus generates approximately 68 tokens per second, while Claude Opus 5.5 delivers 78 tokens per second. In latency-sensitive production environments, Claude Opus 5.5 provides faster time-to-first-token (TTFT) and higher streaming response velocity.
Can you implement a tiered LLM routing setup combining Command A Plus and Claude Opus 5.5 to optimize costs?+
Yes! High-efficiency architectures route high-frequency routine classification and conversational tasks to Command A Plus to save operational costs, and dynamically escalate complex architectural queries or reasoning tasks to Claude Opus 5.5. 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.
Related reading
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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