Both are Cohere models. Command A+ is the newer, generally stronger default; reach for Command A when a specific cost or latency profile matters more than the latest capabilities.
Command A and Command A+ are both Cohere models, so the real question is not which lab to trust but which tier fits your workload and budget. Command A is cohere's enterprise-focused model built for retrieval-augmented and grounded workloads. Command A+ is cohere's newer, leaner flagship - a 218B open-weight MoE tuned for efficiency (just two GPUs to run) and 48-language support. Since both come from the same lab, the comparison below focuses on the tier-and-cost trade-offs that actually separate them.
Key differences
Context window: both advertise 256K (~384 pages). Tie on paper — test on your own long inputs, since usable recall varies by model.
Recency: Command A+ is the newer model by about 15 months (released May 19, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
Command A
Command A+
Provider
Cohere (Global)
Cohere (Canada)
Released
March 2025
May 19, 2026
Context window
256K (~384 pages)
256K (unconfirmed) (~384 pages)
Price (in/out)
$2.5/$10 per 1M tokens
Open weight (self-host / free)
Open weight?
Yes — self-hostable
Yes — self-hostable
Modalities
text, code
text, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Enterprise RAG and retrieval: Command A — Command A+ is comparatively weak here — enterprise/multilingual focus rather than topping general reasoning leaderboards
Strong long-context retrieval accuracy: Command A — Command A+ is comparatively weak here — no official context window or per-token price published yet - both are estimated/unavailable
Multilingual: Command A — Command A lists multilingual among its strengths; Command A+ does not.
Cohere's newer, more efficient flagship - runs on just two H100 GPUs, unusually lean for a 218B-parameter model: Command A+ — Cohere's newer, leaner flagship - a 218B open-weight MoE tuned for efficiency (just two GPUs to run) and 48-language support — and it is the newer of the two.
A 218B-total/25B-active MoE released with open weights (Apache 2.0) on Hugging Face: Command A+ — Command A+ lists a 218B-total/25B-active MoE released with open weights (Apache 2.0) on Hugging Face among its strengths; Command A does not.
Supports 48 languages, including all official EU languages: Command A+ — Command A+ lists supports 48 languages, including all official EU languages among its strengths; Command A does not.
Lowest cost at scale: Command A+ — Its weights are open, so at volume you pay for your own hardware instead of Command A's $2.5/$10 per 1M tokens.
Which should you pick?
A cost-sensitive startup shipping high volume: Command A+ — At Open weight (self-host / free) it undercuts Command A, and on millions of tokens that margin decides the monthly bill.
Anyone whose priority is enterprise rag and retrieval: Command A — It is specifically built for that.
Anyone whose priority is cohere's newer, more efficient flagship - runs on just two h100 gpus, unusually lean for a 218b-parameter model: Command A+ — 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.
Command A+: where it fits
Cohere's newer, leaner flagship - a 218B open-weight MoE tuned for efficiency (just two GPUs to run) and 48-language support. Released May 19, 2026 by Cohere, it is built for cohere's newer, more efficient flagship - runs on just two H100 GPUs, unusually lean for a 218B-parameter model, a 218B-total/25B-active MoE released with open weights (Apache 2.0) on Hugging Face, supports 48 languages, including all official EU languages, and positioned by Cohere as its 'most efficient and performant model to date'.
Its trade-offs: no official context window or per-token price published yet - both are estimated/unavailable, newer release with less independent benchmark verification than established flagships, and enterprise/multilingual focus rather than topping general reasoning leaderboards. As an open-weight model, its running cost is your own hardware rather than a per-token fee.
The bottom line for this matchup
Because Command A and Command A+ come from the same lab (Cohere), they share the same training philosophy and ecosystem — the decision is purely tier vs. cost. Command A+ is the more capable, more recent option; the other earns its place only when its price or latency profile fits a specific job better. Most teams should default to Command A+ and drop down only with a concrete reason.
Frequently asked questions
Is Command A or Command A+ 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 Command A+ leans toward cohere's newer, more efficient flagship - runs on just two h100 gpus, unusually lean for a 218b-parameter model, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Command A or Command A+?
Command A+ is cheaper — $2.5/$10 per 1M tokens vs Open weight (self-host / free).
Which has the bigger context window?
Both advertise 256K (~384 pages). Remember advertised ≠ usable: recall typically degrades before the ceiling.
Should I upgrade from Command A to Command A+?
Since both are Cohere models, the newer one (Command A+) is usually the better default unless you need a specific cost or latency profile from the other.
Which is newer, Command A or Command A+?
Command A+ — released May 19, 2026, about 15 months after Command A.
Command A vs Command A+
Cohere · Global | Cohere · Canada · Updated June 2026
Quick verdict
Both are Cohere models. Command A+ is the newer, generally stronger default; reach for Command A when a specific cost or latency profile matters more than the latest capabilities.
Command A and Command A+ are both Cohere models, so the real question is not which lab to trust but which tier fits your workload and budget. Command A is cohere's enterprise-focused model built for retrieval-augmented and grounded workloads. Command A+ is cohere's newer, leaner flagship - a 218B open-weight MoE tuned for efficiency (just two GPUs to run) and 48-language support. Since both come from the same lab, the comparison below focuses on the tier-and-cost trade-offs that actually separate them.
Key differences at a glance
▸Context window: both advertise 256K (~384 pages). Tie on paper — test on your own long inputs, since usable recall varies by model.
▸Recency: Command A+ is the newer model by about 15 months (released May 19, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
Command A
Command A+
Provider
Cohere (Global)
Cohere (Canada)
Released
March 2025
May 19, 2026
Context window
256K (~384 pages)
256K (unconfirmed) (~384 pages)
Price (in/out)
$2.5/$10 per 1M tokens
Open weight (self-host / free)
Open weight?
Yes — self-hostable
Yes — self-hostable
Modalities
text, code
text, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Enterprise RAG and retrieval
Command A
Command A+ is comparatively weak here — enterprise/multilingual focus rather than topping general reasoning leaderboards
Strong long-context retrieval accuracy
Command A
Command A+ is comparatively weak here — no official context window or per-token price published yet - both are estimated/unavailable
Multilingual
Command A
Command A lists multilingual among its strengths; Command A+ does not.
Cohere's newer, more efficient flagship - runs on just two H100 GPUs, unusually lean for a 218B-parameter model
Command A+
Cohere's newer, leaner flagship - a 218B open-weight MoE tuned for efficiency (just two GPUs to run) and 48-language support — and it is the newer of the two.
A 218B-total/25B-active MoE released with open weights (Apache 2.0) on Hugging Face
Command A+
Command A+ lists a 218B-total/25B-active MoE released with open weights (Apache 2.0) on Hugging Face among its strengths; Command A does not.
Supports 48 languages, including all official EU languages
Command A+
Command A+ lists supports 48 languages, including all official EU languages among its strengths; Command A does not.
Lowest cost at scale
Command A+
Its weights are open, so at volume you pay for your own hardware instead of Command A's $2.5/$10 per 1M tokens.
Which should you pick?
A cost-sensitive startup shipping high volume
→ Command A+
At Open weight (self-host / free) it undercuts Command A, and on millions of tokens that margin decides the monthly bill.
Anyone whose priority is enterprise rag and retrieval
→ Command A
It is specifically built for that.
Anyone whose priority is cohere's newer, more efficient flagship - runs on just two h100 gpus, unusually lean for a 218b-parameter model
→ Command A+
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.
Command A+: where it fits
Cohere's newer, leaner flagship - a 218B open-weight MoE tuned for efficiency (just two GPUs to run) and 48-language support. Released May 19, 2026 by Cohere, it is built for cohere's newer, more efficient flagship - runs on just two H100 GPUs, unusually lean for a 218B-parameter model, a 218B-total/25B-active MoE released with open weights (Apache 2.0) on Hugging Face, supports 48 languages, including all official EU languages, and positioned by Cohere as its 'most efficient and performant model to date'.
Its trade-offs: no official context window or per-token price published yet - both are estimated/unavailable, newer release with less independent benchmark verification than established flagships, and enterprise/multilingual focus rather than topping general reasoning leaderboards. As an open-weight model, its running cost is your own hardware rather than a per-token fee.
The bottom line for this matchup
Because Command A and Command A+ come from the same lab (Cohere), they share the same training philosophy and ecosystem — the decision is purely tier vs. cost. Command A+ is the more capable, more recent option; the other earns its place only when its price or latency profile fits a specific job better. Most teams should default to Command A+ and drop down only with a concrete reason.
Want both Command A and Command A+ 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.
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 Command A+ leans toward cohere's newer, more efficient flagship - runs on just two h100 gpus, unusually lean for a 218b-parameter model, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Command A or Command A+?
Command A+ is cheaper — $2.5/$10 per 1M tokens vs Open weight (self-host / free).
Which has the bigger context window?
Both advertise 256K (~384 pages). Remember advertised ≠ usable: recall typically degrades before the ceiling.
Should I upgrade from Command A to Command A+?
Since both are Cohere models, the newer one (Command A+) is usually the better default unless you need a specific cost or latency profile from the other.
Which is newer, Command A or Command A+?
Command A+ — released May 19, 2026, about 15 months after Command A.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.