Command A vs GPT-4o mini
Cohere · Global | OpenAI · US · Updated June 2026
Quick verdict
Pick Command A for enterprise rag and retrieval or strong long-context retrieval accuracy. Pick GPT-4o mini for very low cost per token for its capability tier or strong coding for a small model (87.2% humaneval). Choose Command A if you need self-hosting or data privacy; GPT-4o mini if you want a managed API.
Command A (Cohere) and GPT-4o mini (OpenAI) are two of the models people most often weigh against each other in 2026. Command A is cohere's enterprise-focused model built for retrieval-augmented and grounded workloads. GPT-4o mini is openAI's budget small multimodal model — cheap, fast text-and-vision intelligence that outscored peer small models like Gemini 1.5 Flash and Claude 3 Haiku on MMLU and HumanEval at launch. They diverge most on price, context window and open vs. closed weights — each quantified below from the models' real specs.
Key differences at a glance
- ▸Price: GPT-4o mini is about 17× cheaper on input ($0.15/$0.6 per 1M tokens vs $2.5/$10 per 1M tokens) — a large enough gap that at scale it can be the single biggest line item in the decision.
- ▸Context window: Command A holds 2× more — 256K (~384 pages) vs 128K (~192 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
- ▸Recency: Command A is the newer model by about 8 months (released March 2025), usually meaning fresher training data and capabilities.
Side-by-side specs
| Spec | Command A | GPT-4o mini |
|---|---|---|
| Provider | Cohere (Global) | OpenAI (US) |
| Released | March 2025 | July 18, 2024 |
| Context window | 256K (~384 pages) | 128K (~192 pages) |
| Price (in/out) | $2.5/$10 per 1M tokens | $0.15/$0.6 per 1M tokens |
| Open weight? | Yes — self-hostable | No — API only |
| Modalities | text, code | text, image |
| SWE-Bench Verified | Not published | Not published |
| MRCR v2 @ 1M | Not published | Not published |
Who wins what
Enterprise RAG and retrieval
Command A
Cohere's enterprise-focused model built for retrieval-augmented and grounded workloads — and it carries the larger 256K context.
Strong long-context retrieval accuracy
Command A
Its 256K window holds about 2× more than GPT-4o mini's 128K in a single prompt.
Multilingual
Command A
Cohere's enterprise-focused model built for retrieval-augmented and grounded workloads — and its weights are open while GPT-4o mini is API-only.
Very low cost per token for its capability tier
GPT-4o mini
At $0.15/$0.6 per 1M tokens it undercuts Command A ($2.5/$10 per 1M tokens), and that gap compounds at volume.
Strong coding for a small model (87.2% HumanEval)
GPT-4o mini
OpenAI's budget small multimodal model — cheap, fast text-and-vision intelligence that outscored peer small models like Gemini 1.5 Flash and Claude 3 Haiku on MMLU and HumanEval at launch — and it runs cheaper at $0.15/$0.6 per 1M tokens.
Leading MMLU among peer small models (82%)
GPT-4o mini
GPT-4o mini lists leading MMLU among peer small models (82%) among its strengths; Command A does not.
Lowest cost at scale
GPT-4o mini
At $0.15/$0.6 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input
Command A
Its 256K window is about 2× larger than GPT-4o mini's 128K, fitting roughly 384 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ GPT-4o mini
At $0.15/$0.6 per 1M tokens it undercuts Command A, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ Command A
Larger 256K window fits more in one prompt.
A team with data-privacy or self-hosting needs
→ Command A
Open weights let you run it on your own hardware; GPT-4o mini is API-only.
Anyone whose priority is enterprise rag and retrieval
→ Command A
It is specifically built for that.
Anyone whose priority is very low cost per token for its capability tier
→ GPT-4o mini
That is its strongest area.
Command A: where it fits
Cohere's enterprise-focused model built for retrieval-augmented and grounded workloads. Released March 2025 by Cohere, it is built for enterprise RAG and retrieval, strong long-context retrieval accuracy, multilingual, and tool use.
Its trade-offs are real: less consumer presence, and narrower modality support. At $2.5 in / $10 out per million tokens, it sits in the mid price band.
GPT-4o mini: where it fits
OpenAI's budget small multimodal model — cheap, fast text-and-vision intelligence that outscored peer small models like Gemini 1.5 Flash and Claude 3 Haiku on MMLU and HumanEval at launch. Released July 18, 2024 by OpenAI, it is built for very low cost per token for its capability tier, strong coding for a small model (87.2% HumanEval), leading MMLU among peer small models (82%), and text and image (vision) understanding in the API.
Its trade-offs: only 128K context with an October 2023 knowledge cutoff, and weaker on hard reasoning and coding than frontier models. At $0.15 in / $0.6 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
The defining split here is open vs. closed. Command A gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. GPT-4o mini gives you a managed, always-updated API with no infrastructure to run. Teams with GPUs, privacy requirements, or huge volume often favour the open model; teams that want zero ops and the latest capabilities favour the closed one. Capability is close enough that this operational question, not the benchmark, usually decides it.
Want both Command A and GPT-4o mini without two subscriptions? LumiChats gives you these plus 40+ models under one ₹69/day pass (about $1/day) — draft with one, cross-check with the other.
See pricingFrequently asked questions
Is Command A or GPT-4o mini better for coding?
Public SWE-Bench figures are not available for either model, so the honest test is your own repository — run an identical real bug through both. By design, Command A leans toward enterprise rag and retrieval while GPT-4o mini leans toward very low cost per token for its capability tier, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Command A or GPT-4o mini?
Command A is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while GPT-4o mini is API-metered at $0.15/$0.6 per 1M tokens. For most teams without GPUs, the API model is cheaper to start; at very high volume, self-hosting can win.
Which has the bigger context window?
Command A — 256K vs 128K, about 2× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Command A and GPT-4o mini together?
Yes — a multi-model platform like LumiChats gives you Command A, GPT-4o mini and 40+ others under one ₹69/day pass (about $1/day), so you can draft with one and cross-check with the other instead of buying two subscriptions.
Which is newer, Command A or GPT-4o mini?
Command A — released March 2025, about 8 months after GPT-4o mini.
Related comparisons
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.