Cohere Command A

Summary

Cohere Command A is Cohere's flagship enterprise model, an open-weight 111B-parameter model with a 256K-token context window optimized for agentic AI, multilingual workloads, and coding use cases. Where Command R+ established Cohere as a leading enterprise RAG and tool-use provider.

Overview

Cohere Command A is Cohere's flagship enterprise model, an open-weight 111B-parameter model with a 256K-token context window optimized for agentic AI, multilingual workloads, and coding use cases. Where Command R+ established Cohere as a leading enterprise RAG and tool-use provider, Command A advances the line on inference economics: at 111B parameters, Command A requires only two GPUs (A100s or H100s) to run, while delivering ~150% higher throughput than its predecessor Command R+ 08-2024. These deployment choices — open weights, modest GPU footprint, high throughput — explicitly target enterprise self-hosting in regulated environments where frontier closed-API models cannot be deployed.

Command A's positioning is the clearest example in the market of "winning by not competing on the frontier-benchmark axis." Where OpenAI, Anthropic, Google DeepMind, and the Chinese open-weight labs battle for absolute SWE-Bench / MMLU-Pro / OSWorld-V scores, Cohere builds for the operational realities of enterprise RAG / agentic deployment — data residency, on-prem support, multilingual coverage, and inference economics — and Command A delivers on each of those vectors.

Specifications

  • Developer: Cohere
  • Type: Open-weight enterprise large language model; agentic, multilingual, coding-tuned
  • Parameters: 111 billion
  • Context Window: 256,000 tokens
  • License: Open-weight (Cohere license terms — review before commercial deployment)
  • GPU Requirements: Runs on as few as two A100 / H100 GPUs
  • Throughput: ~150% higher than Command R+ 08-2024
  • Access: Cohere API + Amazon Bedrock + open-weight self-hosting + on-prem / private cloud

Capabilities

Agentic Workloads (headline focus): Specialized for agentic AI use cases — multi-step tool use, retrieval-augmented agents, and complex enterprise workflows.

Multilingual Coverage: Extends Cohere's heritage of strong multilingual coverage. Command R+ supports 10+ languages including English, French, Spanish, Italian, German, Portuguese, Japanese, Korean, Arabic, and Chinese; Command A's multilingual training extends and deepens that coverage.

Coding Use Cases: Tuned for coding workflows — performance against frontier closed models varies by benchmark but is competitive within the open-weight tier.

256K Context Window: Long-context support for enterprise document analysis, multi-turn conversations, and agentic workflows that span large state.

2-GPU Deployment: One of the most efficient frontier-tier open-weight deployment profiles. Critical for enterprises that need to self-host on commodity multi-GPU servers without the $1M+ infrastructure required for larger MoE models.

150% Higher Throughput vs. Predecessor: Substantial inference-economics improvement over Command R+ 08-2024 — translating directly into lower cost-per-query at the same hardware footprint.

On-Prem / Private Cloud Friendly: Combined with open weights and modest GPU requirements, Command A is one of the most credible enterprise on-prem AI options for regulated industries (financial services, healthcare, government).

Limitations

Not Frontier-Benchmark-Leading: Command A is competitive within open-weight enterprise deployment but does not lead on the absolute frontier benchmarks (SWE-Bench Pro, MMLU-Pro, ARC-AGI-2) where GPT-5.5, Claude Opus 4.7, Gemini 3.1 Ultra, and DeepSeek V4-Pro / Kimi K2.6 / Qwen 3.5 compete.

License Review Required: Cohere's open-weight license includes specific terms — enterprises should review carefully before commercial redistribution or service-based deployment.

API Pricing for Cohere-Hosted: Self-hosting via open weights is the cost-efficient path; Cohere-hosted API access at frontier-quality models has pricing that should be evaluated against alternatives like Claude Sonnet, GPT-5.5 standard, or DeepSeek V4-Flash for cost-sensitive workloads.

Less Public Benchmarking than Frontier Peers: Cohere publishes fewer benchmark results than the major frontier labs and Chinese open-weight competitors, making head-to-head capability comparisons sometimes harder for procurement evaluation.

Recent Developments

  • Command A Release: Marked Cohere's transition from the R+ generation to a new flagship optimized specifically for the open-weight, on-prem, enterprise deployment surface that the company has staked its strategy on.
  • 2-GPU Deployment Profile: Explicitly designed to fit into commodity multi-GPU enterprise hardware rather than requiring frontier-MoE-scale infrastructure.
  • Throughput Gains: ~150% higher throughput than Command R+ 08-2024 — direct translation into improved inference economics for high-volume enterprise workloads.
  • Industry Position: Cohere remains the strongest example of an AI lab winning by deliberately not competing on the frontier-benchmark axis — and Command A's specs (111B params, 256K context, 2-GPU deployment, open weights) are tuned exactly for that positioning.

Last Updated

May 7, 2026

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