Command A Plus vs Command A Reasoning
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (12)
Command A Plus di Cohere e Command A Reasoning di Cohere sono due modelli di IA di riferimento. Command A Plus offre una finestra di contesto di 128K token a $3.00/$12.00 per milione di token, mentre Command A Reasoning mette a disposizione 256K token di contesto a $2.50/$10.00 per milione di token. Di seguito analizziamo benchmark, latenza e costi.
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Command A Plus
Modello Base a Pesi ApertiCommand A Plus di Cohere è un modello di IA progettato per il self-hosting su infrastruttura privata, il fine-tuning e la piena sovranità dei dati, con finestra di contesto da 128K, velocità di 68 token/s, indice di intelligenza di 58/100 e
$3.00 / 1M
$12.00 / 1M
128K tokens
60.5%
Command A Reasoning
Ragionamento a Pesi ApertiCommand A Reasoning di Cohere è un modello di IA progettato per il ragionamento Chain-of-Thought a pesi aperti ad alta efficienza algoritmica, con finestra di contesto da 256K, velocità di 55 token/s, indice di intelligenza di 55/100 e tari
$2.50 / 1M
$10.00 / 1M
256K tokens
53%
Differenze Chiave a Colpo d’Occhio
- 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 |
Chi vince in ogni categoria?
At-a-glance decision frameworkPunteggi Benchmark Verificati
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.
Latenza e Tempo di Risposta
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
Simulatore Interattivo dei Costi Token
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
Command A Plus · Strengths & Key Advantages
- Finestra di contesto da 128K con capacità massima di output fino a 33K token (SWE-bench Verified 60.5% · GPQA Diamond 74%)
- Throughput elevato di 68 token/secondo con latenza al primo token (TTFT) di soli 560 ms
- Pesi aperti (Confidential (~180B+ MoE)) pronti per il self-hosting locale o su cloud privato tramite vLLM, SGLang o Ollama
Considerations & Trade-offs
- Richiede server GPU dedicati con sufficiente memoria VRAM per l’esecuzione locale a piena precisione
- Per volumi di traffico elevati in produzione si consiglia di attivare il prompt caching e la Batch API
Command A Reasoning · Strengths & Key Advantages
- Finestra di contesto da 256K con capacità massima di output fino a 33K token (SWE-bench Verified 53% · GPQA Diamond 70%)
- Throughput elevato di 55 token/secondo con latenza al primo token (TTFT) di soli 750 ms
- Pesi aperti (Confidential (~100B+)) pronti per il self-hosting locale o su cloud privato tramite vLLM, SGLang o Ollama
Considerations & Trade-offs
- Richiede server GPU dedicati con sufficiente memoria VRAM per l’esecuzione locale a piena precisione
- Per volumi di traffico elevati in produzione si consiglia di attivare il prompt caching e la Batch API
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 |
Specifiche Tecniche
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: Risposte Rapide (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.
Verdetto
Sia Command A Plus (Ideale per il self-hosting su infrastruttura privata, il fine-tuning e la piena sovranità dei dati, sistemi RAG aziendali e integrazioni API scalabili.) sia Command A Reasoning (Ideale per il ragionamento Chain-of-Thought a pesi aperti ad alta efficienza algoritmica, sistemi RAG aziendali e integrazioni API scalabili.) eccellono in produzione: Command A Plus guida nei benchmark di ragionamento e programmazione, Command A Plus garantisce una generazione più rapida e Command A Reasoning offre il miglior rapporto qualità-prezzo per carichi API elevati.
Domande Frequenti (FAQ)
Quale modello è migliore per coding e ragionamento, Command A Plus o Command A Reasoning?+
Nell’indice di intelligenza composito e nei benchmark di programmazione prevale Command A Plus. Consulta i punteggi SWE-bench e GPQA qui sopra per tutti i dettagli.
Qual è la differenza di prezzo API tra Command A Plus e Command A Reasoning?+
Command A Plus costa $3.00 / $12.00 per milione di token di input/output, mentre Command A Reasoning costa $2.50 / $10.00. Nel costo combinato, Command A Reasoning risulta più economico.
Quale modello ha la finestra di contesto più ampia e la velocità maggiore?+
Command A Plus supporta 128K token di contesto contro 256K token di Command A Reasoning, mentre Command A Plus offre una velocità di generazione superiore.
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.
Fonti ufficiali: Documentazione API ufficiale di Cohere e Cohere, schede di sistema e benchmark indipendenti (2026).