Cohere

Aya Expanse

Maker
Cohere
Origin
Canada
Released
Oct 2024
Category
Language Models

Strengths & weaknesses

  • Purpose-built for broad multilingual coverage across dozens of languages, including many under-served ones
  • Open-weight, useful for research and localization-heavy applications
  • Not intended to compete with frontier models on English-centric reasoning
  • Smaller production track record than Cohere's commercial Command line

Evaluation

In assessment · 60% measured

Scored on Aya Expanse 32B · sources as of Sep 19, 2026

w = weight, each criterion’s share of the overall score. Missing marks don’t count for or against. How scoring works

Enterprise fit

Highest-ROI use cases

Where Aya Expanse fits inside a company, ranked by the strength of published ROI evidence for each use case, then by its independent rating for the work.

All 100 enterprise use cases →
  1. 01
    Research, analysis & reportingControlled trial
    Strategy, consulting, finance
    • ▸ Rated #21 of 22 directory models on LMArena text (hard prompts), the closest independent rating for this work
    • ▸ Built for this kind of work (Language Models)
  2. 02
    Marketing, content & salesControlled trial
    Marketing & sales
    • ▸ Rated #21 of 22 directory models on LMArena text (creative writing), the closest independent rating for this work
    • ▸ Built for this kind of work (Language Models)
  3. 03
    Customer supportField study
    Customer service
    • ▸ Rated #21 of 22 directory models on LMArena text (overall), the closest independent rating for this work
    • ▸ Built for this kind of work (Language Models)

More in Language Models

View all →
OpenAI

GPT-5.6

7.2/10
  • Best-in-class agentic reasoning, with search, code execution, and computer use in one API
  • Disciplined, low-hallucination output on long, multi-step tasks
  • Long-context requests above roughly 272K tokens get repriced sharply higher
  • Slower to produce a first answer than most rivals at max reasoning
Anthropic

Claude Opus 5

7.1/10
  • Anthropic's recommended model for complex, high-stakes work, with strong reasoning-to-cost
  • Zero-data-retention eligible, useful for regulated or enterprise deployments
  • Sits below the flagship tier in branding despite strong practical scores
  • Costs meaningfully more per token than the Sonnet tier for everyday tasks
Anthropic

Claude Sonnet 5

6.4/10
  • Fast and capable, priced for everyday production use
  • Strong default for coding and long documents without Opus-level cost
  • Enabling maximum thinking mode can quietly balloon token spend
  • Trails Opus on the hardest multi-step reasoning problems
Anthropic

Claude Haiku 4.5

5.7/10
  • Cheapest Claude tier, well suited to high-volume, simple tasks
  • Low latency, good for chat-style and classification workloads
  • Smaller context window (200K tokens) than Sonnet 5 and Opus 5 (1M)
  • Noticeably weaker on hard reasoning than Sonnet or Opus