Command A Plus vs Command A Reasoning
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (12)
Command A Plus by Cohere and Command A Reasoning 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, Command A Reasoning holds a notable pricing advantage for token ingestion. On output generation, Command A Reasoning is more economical per million generated tokens. In data-heavy architectures requiring extensive repository or document analysis, Command A Reasoning provides an expanded memory horizon with 256K tokens. In latency-sensitive production environments, Command A Plus 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.
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Command A Plus
Model Open-WeightsCommand A Plus dari Cohere adalah model AI canggih dengan jendela konteks 128K token serta harga API $3/1M token input dan $12/1M token output untuk pemrograman, penalaran, dan otomasi bisnis.
$3.00 / 1M
$12.00 / 1M
128K tokens
60.5%
Command A Reasoning
Model Open-WeightsCommand A Reasoning dari Cohere adalah model AI canggih dengan jendela konteks 256K token serta harga API $2.5/1M token input dan $10/1M token output untuk pemrograman, penalaran, dan otomasi bisnis.
$2.50 / 1M
$10.00 / 1M
256K tokens
53%
Perbedaan Utama Sekilas
- Command A Reasoning is 1.2x cheaper for API usage (input + output tokens combined).
- Command A Reasoning has a larger context window (256K vs 128K tokens).
- Command A Plus is faster at 68 tok/s vs 55 tok/s.
- Command A Plus leads on SWE-bench coding (60.5% vs 53.0%).
| Feature | Command A Plus | Command A Reasoning |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 58 | 55 |
Provider | Cohere | Cohere |
Input Price Cost per million input tokens | $3.00 / 1M | $2.50 / 1M |
Output Price Cost per million output tokens | $12.00 / 1M | $10.00 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $2.33 / 1M | $2.02 / 1M |
Context Window Maximum input + output tokens | 128K tokens~192 A4 pages of text | 256K tokens~384 A4 pages of text |
Max Output Tokens Per single request | 33K | 33K |
Throughput Speed Tokens generated per second | 68 tok/s | 55 tok/s |
SWE-bench Verified Real-world software engineering | 60.5% | 53% |
GPQA Diamond Graduate-level reasoning | 74% | 70% |
Cached Input Price Prompt caching discount per 1M tokens | $0.75 / 1M | $0.75 / 1M |
Siapa Unggul di Mana?
At-a-glance decision frameworkSkor Benchmark Terverifikasi
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.
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.
Latensi & Waktu Respons
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
Simulator Biaya Token Interaktif
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
Command A Plus · Strengths & Key Advantages
- Arsitektur Flagship Multimodal Agentic MoE mutakhir dari Cohere dengan dukungan konteks 128K token
- Efisiensi biaya API yang kompetitif ($3/1M input, $12/1M output) dan respons cepat
- Performa andal dalam pembuatan kode, analisis logika, serta pemahaman multibahasa
Considerations & Trade-offs
- Penggunaan konteks berukuran penuh memerlukan pengelolaan anggaran token yang cermat
- Membutuhkan perancangan prompt yang tepat untuk kasus penggunaan industri spesifik
Command A Reasoning · Strengths & Key Advantages
- Arsitektur Enterprise Chain-of-Thought Reasoning Transformer mutakhir dari Cohere dengan dukungan konteks 256K token
- Efisiensi biaya API yang kompetitif ($2.5/1M input, $10/1M output) dan respons cepat
- Performa andal dalam pembuatan kode, analisis logika, serta pemahaman multibahasa
Considerations & Trade-offs
- Penggunaan konteks berukuran penuh memerlukan pengelolaan anggaran token yang cermat
- Membutuhkan perancangan prompt yang tepat untuk kasus penggunaan industri spesifik
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | Command A Plus | Command A Reasoning |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.85 | $0.95 |
Output Tokens / Task Tokens generated per task | 45K | 45K |
Reasoning Tokens / Task Thinking tokens burned per task | 22K | 22K |
Spesifikasi Teknis
Architecture, release timeline, capabilities, and modalities.
| Feature | Command A Plus | Command A Reasoning |
|---|---|---|
| Official API Model ID (SDK) | command-a-plus | command-a-reasoning |
| API Protocol | OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI | OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI |
| Release Date | 2026-05 | 2025-08 |
| Knowledge Cutoff | March 2026 | June 2025 |
| Architecture | Flagship Multimodal Agentic MoE | Enterprise Chain-of-Thought Reasoning Transformer |
| Parameters | Confidential (~180B+ MoE) | Confidential (~100B+) |
| 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 ($3/1M in) across full 128K window | Flat rate ($2.5/1M in) across full 256K window |
| Prompt Cache Policy & TTL | Cached input at $0.75/1M tokens | Cached input at $0.75/1M 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) · 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) · 112 GB VRAM (4-bit Quantized) · 387 GB VRAM (Native BF16) | BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 62 GB VRAM (4-bit Quantized) · 215 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 |
Command A Plus vs Command A Reasoning: Jawaban Cepat (FAQ)
Which is more intelligent, Command A Plus or Command A Reasoning?
Command A Plus is more intelligent. It scores 58 compared with 55 on the composite Intelligence Index.
Which model is faster?
Command A Plus is faster, generating 68 tokens per second compared with 55 tokens per second.
Which model is cheaper to run?
Command A Reasoning is cheaper at $2.02 per 1M tokens blended, compared with $2.33 (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 0.75s.
Which model has a larger context window?
Command A Reasoning has a larger context window, supporting 256K tokens compared with 128K tokens.
Kesimpulan
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 Command A Reasoning if your workflow prioritizes Regulatory compliance review, complex legal contract analysis, and mathematical logic synthesis. For large-scale batch processing or customer-facing conversational interfaces, its balance of speed and economics delivers superior ROI.
Pertanyaan Umum (FAQ)
How does Command A Plus compare to Command A Reasoning 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 Command A Reasoning costs $2.50 input and $10.00 output. Overall, Command A Reasoning 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 Command A Reasoning?+
Command A Plus supports a context window of 128K tokens (~96k words), while Command A Reasoning supports 256K tokens (~192k words). Therefore, Command A Reasoning 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 Command A Reasoning?+
Command A Plus scores 60.5% on SWE-bench Verified while Command A Reasoning scores 53%. For autonomous software engineering and multi-file debugging, Command A Plus holds the verified benchmark lead.
What is the difference in reasoning capability and extended thinking between Command A Plus and Command A Reasoning?+
Command A Plus features native chain-of-thought extended thinking mode with configurable reasoning effort. In contrast, Command A Reasoning provides chain-of-thought reasoning depth for complex math and science.
How does inference speed (tokens per second) compare between Command A Plus and Command A Reasoning?+
Command A Plus generates approximately 68 tokens per second, while Command A Reasoning delivers 55 tokens per second. In latency-sensitive production environments, Command A Plus 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 Command A Reasoning to optimize costs?+
Yes! High-efficiency architectures route high-frequency routine classification and conversational tasks to Command A Reasoning to save operational costs, and dynamically escalate complex architectural queries or reasoning tasks to Command A Plus. 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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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.
Sumber resmi: GetInfoUs Independent AI Benchmarks & Official API Specs