Pick Command A+ for cohere's newer, more efficient flagship - runs on just two h100 gpus, unusually lean for a 218b-parameter model or a 218b-total/25b-active moe released with open weights (apache 2.0) on hugging face. Pick Mistral Large 3 for open-weight (apache 2.0), self-hostable or strong multilingual performance. On a tight budget at scale, Command A+ is the value pick.
Command A+ (Cohere, Canada) and Mistral Large 3 (Mistral, France) line up two different AI ecosystems against each other — a comparison that is as much about cost philosophy and openness as raw capability. 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. Mistral Large 3 is france's frontier contender — strong multilingual model with European data residency. Their biggest split is price, and the breakdown below shows exactly how that plays out for your workload.
Key differences
Context window: both advertise 256K (unconfirmed) (~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 6 months (released May 19, 2026), usually meaning fresher training data and capabilities.
Ecosystem: this is a Canada-vs-France matchup — they differ in pricing philosophy, data-residency options, and tooling ecosystems, not only benchmarks.
Specifications
Spec
Command A+
Mistral Large 3
Provider
Cohere (Canada)
Mistral (France)
Released
May 19, 2026
December 2, 2025
Context window
256K (unconfirmed) (~384 pages)
256K (~384 pages)
Price (in/out)
Open weight (self-host / free)
$0.5/$1.5 per 1M tokens
Open weight?
Yes — self-hostable
Yes — self-hostable
Modalities
text, code
text, image, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
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; Mistral Large 3 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; Mistral Large 3 does not.
Open-weight (Apache 2.0), self-hostable: Mistral Large 3 — Mistral Large 3 lists open-weight (Apache 2.0), self-hostable among its strengths; Command A+ does not.
Strong multilingual performance: Mistral Large 3 — Command A+ is comparatively weak here — enterprise/multilingual focus rather than topping general reasoning leaderboards
Efficient inference: Mistral Large 3 — Mistral Large 3 lists efficient inference 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 Mistral Large 3's $0.5/$1.5 per 1M tokens.
Which should you pick?
A cost-sensitive startup shipping high volume: Command A+ — At Open weight (self-host / free) it undercuts Mistral Large 3, and on millions of tokens that margin decides the monthly bill.
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+ — It is specifically built for that.
Anyone whose priority is open-weight (apache 2.0), self-hostable: Mistral Large 3 — That is its strongest area.
An enterprise with regional data-residency rules: Mistral Large 3 or Command A+ — Origin (Canada vs France) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
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 are real: 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.
Mistral Large 3: where it fits
France's frontier contender — strong multilingual model with European data residency. Released December 2, 2025 by Mistral, it is built for open-weight (Apache 2.0), self-hostable, strong multilingual performance, efficient inference, and function calling.
Its trade-offs: smaller context than US/China frontier, and less benchmark coverage. At $0.5 in / $1.5 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
This is less "which is smarter" and more "which ecosystem fits." Command A+ (Canada) and Mistral Large 3 (France) differ on pricing philosophy, data-residency, and tooling as much as on raw scores. Command A+ is the cheaper option, which matters at volume. The pragmatic move is to run one real task through both and judge the outputs against your own constraints — including where your data is allowed to be processed.
Frequently asked questions
Is Command A+ or Mistral Large 3 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 cohere's newer, more efficient flagship - runs on just two h100 gpus, unusually lean for a 218b-parameter model while Mistral Large 3 leans toward open-weight (apache 2.0), self-hostable, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Command A+ or Mistral Large 3?
Command A+ is cheaper — Open weight (self-host / free) vs $0.5/$1.5 per 1M tokens.
Which has the bigger context window?
Both advertise 256K (unconfirmed) (~384 pages). Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both Command A+ and Mistral Large 3 together?
Yes — a multi-model platform like LumiChats gives you Command A+, Mistral Large 3 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 Mistral Large 3?
Command A+ — released May 19, 2026, about 6 months after Mistral Large 3.
Command A+ vs Mistral Large 3
Cohere · Canada | Mistral · France · Updated June 2026
Quick verdict
Pick Command A+ for cohere's newer, more efficient flagship - runs on just two h100 gpus, unusually lean for a 218b-parameter model or a 218b-total/25b-active moe released with open weights (apache 2.0) on hugging face. Pick Mistral Large 3 for open-weight (apache 2.0), self-hostable or strong multilingual performance. On a tight budget at scale, Command A+ is the value pick.
Command A+ (Cohere, Canada) and Mistral Large 3 (Mistral, France) line up two different AI ecosystems against each other — a comparison that is as much about cost philosophy and openness as raw capability. 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. Mistral Large 3 is france's frontier contender — strong multilingual model with European data residency. Their biggest split is price, and the breakdown below shows exactly how that plays out for your workload.
Key differences at a glance
▸Context window: both advertise 256K (unconfirmed) (~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 6 months (released May 19, 2026), usually meaning fresher training data and capabilities.
▸Ecosystem: this is a Canada-vs-France matchup — they differ in pricing philosophy, data-residency options, and tooling ecosystems, not only benchmarks.
Side-by-side specs
Spec
Command A+
Mistral Large 3
Provider
Cohere (Canada)
Mistral (France)
Released
May 19, 2026
December 2, 2025
Context window
256K (unconfirmed) (~384 pages)
256K (~384 pages)
Price (in/out)
Open weight (self-host / free)
$0.5/$1.5 per 1M tokens
Open weight?
Yes — self-hostable
Yes — self-hostable
Modalities
text, code
text, image, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
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; Mistral Large 3 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; Mistral Large 3 does not.
Open-weight (Apache 2.0), self-hostable
Mistral Large 3
Mistral Large 3 lists open-weight (Apache 2.0), self-hostable among its strengths; Command A+ does not.
Strong multilingual performance
Mistral Large 3
Command A+ is comparatively weak here — enterprise/multilingual focus rather than topping general reasoning leaderboards
Efficient inference
Mistral Large 3
Mistral Large 3 lists efficient inference 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 Mistral Large 3's $0.5/$1.5 per 1M tokens.
Which should you pick?
A cost-sensitive startup shipping high volume
→ Command A+
At Open weight (self-host / free) it undercuts Mistral Large 3, and on millions of tokens that margin decides the monthly bill.
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+
It is specifically built for that.
Anyone whose priority is open-weight (apache 2.0), self-hostable
→ Mistral Large 3
That is its strongest area.
An enterprise with regional data-residency rules
→ Mistral Large 3 or Command A+
Origin (Canada vs France) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
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 are real: 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.
Mistral Large 3: where it fits
France's frontier contender — strong multilingual model with European data residency. Released December 2, 2025 by Mistral, it is built for open-weight (Apache 2.0), self-hostable, strong multilingual performance, efficient inference, and function calling.
Its trade-offs: smaller context than US/China frontier, and less benchmark coverage. At $0.5 in / $1.5 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
This is less "which is smarter" and more "which ecosystem fits." Command A+ (Canada) and Mistral Large 3 (France) differ on pricing philosophy, data-residency, and tooling as much as on raw scores. Command A+ is the cheaper option, which matters at volume. The pragmatic move is to run one real task through both and judge the outputs against your own constraints — including where your data is allowed to be processed.
Want both Command A+ and Mistral Large 3 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.
Is Command A+ or Mistral Large 3 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 cohere's newer, more efficient flagship - runs on just two h100 gpus, unusually lean for a 218b-parameter model while Mistral Large 3 leans toward open-weight (apache 2.0), self-hostable, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Command A+ or Mistral Large 3?
Command A+ is cheaper — Open weight (self-host / free) vs $0.5/$1.5 per 1M tokens.
Which has the bigger context window?
Both advertise 256K (unconfirmed) (~384 pages). Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both Command A+ and Mistral Large 3 together?
Yes — a multi-model platform like LumiChats gives you Command A+, Mistral Large 3 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 Mistral Large 3?
Command A+ — released May 19, 2026, about 6 months after Mistral Large 3.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.