Which AI Model Fits Your Business? A Practical Guide to Cohere, Gemini, Llama, GPT-OSS, and Grok

  • September 17, 2025
  • Posted by: Onsys
  • Category: Artificial Intelligence
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Generative AI is no longer experimental—it’s powering real-world enterprise, research, and consumer use cases. Five models stand out in 2025: Cohere Command R, Google Gemini 2.5 Pro, Meta Llama 4 Maverick, OpenAI gpt-oss-120B, and xAI Grok 4. Below we compare their strengths, limitations, and practical applications.

Cohere Command R

Overview
A 32-billion-parameter text-only model with retrieval-augmented generation (RAG), fine-tuned for precision, safety, and multilingual support. Optimised for enterprise throughput and low latency.

Key Specs

  • Context: 128k tokens
  • Modality: Text-only
  • Strengths: High-accuracy RAG, citation generation, enterprise-grade tool use
  • Limitations: Text-only, capped at 4k output tokens

Use Cases

  • Financial services: Automating compliance checks by retrieving and citing regulations.
  • Healthcare: Building multilingual clinical knowledge assistants that cite research papers.
  • Legal firms: Drafting contracts with embedded case citations.

Example: A bank uses Command R to build a compliance chatbot that retrieves regulations in English and Spanish, returning results with full citations for auditors.

Google Gemini 2.5 Pro (Beta)

Overview
Google’s multimodal “thinking model” with advanced reasoning and 1-million-token context. Capable of analysing long documents, codebases, images, audio, and video.

Key Specs

  • Context: 1M tokens (planned 2M)
  • Modality: Fully multimodal
  • Strengths: Long-context reasoning, research-grade step-by-step analysis
  • Limitations: Beta, not fully open, high compute cost

Use Cases

  • Research: Analysing massive genomic datasets or scientific papers.
  • Software engineering: Reviewing entire enterprise codebases in a single pass.
  • Media: Summarising hour-long podcasts or video transcripts.

Example: A legal research platform feeds thousands of case law documents into Gemini to trace precedent across decades, something unmanageable with smaller context models.

Meta Llama 4 Maverick

Overview
An open-source model with enhanced math, code, and conversation stability. Reported multimodal input, though details remain incomplete.

Key Specs

  • Context: Reported long (undisclosed)
  • Modality: Text + some image input
  • Strengths: Coding, math reasoning, open-weight accessibility
  • Limitations: Performance varies with fine-tuning, benchmarks still sparse

Use Cases

  • Startups: Deploying cost-effective open-source copilots without licensing fees.
  • Education: Local deployment for math tutors that explain solutions step-by-step.
  • SMBs: Private deployment for sensitive IP (e.g., legal documents or proprietary code).

Example: A university fine-tunes Maverick locally to provide students with math and coding help while maintaining data privacy.

OpenAI gpt-oss-120B (Beta)

Overview
OpenAI’s Mixture-of-Experts (MoE) text-only model (117B parameters, 5.1B active per token). Open-weight release for reasoning and tool-use at scale.

Key Specs

  • Context: 128k tokens
  • Modality: Text-only
  • Strengths: Strong reasoning and tool integration, scalable MoE design
  • Limitations: No multimodal support, heavy compute requirements

Use Cases

  • Enterprises: Running in-house reasoning systems without vendor lock-in.
  • Developers: Building tool-use agents that integrate with APIs.
  • Academia: Research on efficiency trade-offs in large MoE models.

Example: A logistics company uses gpt-oss-120B to optimise delivery routes, feeding 100k+ lines of historical shipment data into the model for reasoning.

xAI Grok 4

Overview
xAI’s Grok 4 integrates directly with X (Twitter), pulling live data for real-time answers. Supports text, image, code, and video.

Key Specs

  • Context: 128k tokens
  • Modality: Multimodal (text, images, code, video)
  • Strengths: Real-time integration, conversational persona with humour
  • Limitations: X Premium+ only, moderation/privacy concerns, informal tone

Use Cases

  • Media: Summarising breaking news and live streams in real time.
  • Retail: Monitoring social sentiment for product launches.
  • Entertainment: Conversational agents that combine humour with live trending data.

Example: A sports broadcaster uses Grok 4 to generate live match summaries and highlight reels, integrating fan tweets in real time.

Choosing the Right Model

  • Regulated enterprises: Cohere Command R for auditable RAG with citations
  • Deep research & multimodal: Google Gemini 2.5 Pro for long-context analysis
  • Open-source & customisable: Meta Llama 4 Maverick for private deployments
  • Scalable reasoning at scale: OpenAI gpt-oss-120B for tool-integrated agents
  • Real-time social awareness: xAI Grok 4 for live content and conversational AI

Conclusion

Generative AI is diverging into specialised paths: compliance-ready RAG (Cohere), multimodal reasoning (Gemini), open-source flexibility (Llama), scalable open reasoning (gpt-oss), and real-time integration (Grok).

For enterprises, the choice depends on balancing accuracy, scalability, data privacy, and domain needs. The most effective strategy may not be selecting a single model but combining them to suit use-specific workflows.