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 DeepSeek V4 for near-frontier coding at ~1/12 the cost or open mit-licensed weights you can self-host. On a tight budget at scale, Command A+ is the value pick.
Command A+ (Cohere, Canada) and DeepSeek V4 (DeepSeek, China) 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. DeepSeek V4 is china's open-weight price earthquake — near-frontier capability at roughly a twelfth of GPT-5.5's cost. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences
Context window: DeepSeek V4 holds 3.9× more — 1M (~1,500 pages) vs 256K (unconfirmed) (~384 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 25 days (released May 19, 2026), usually meaning fresher training data and capabilities.
Ecosystem: this is a Canada-vs-China matchup — they differ in pricing philosophy, data-residency options, and tooling ecosystems, not only benchmarks.
Specifications
Spec
Command A+
DeepSeek V4
Provider
Cohere (Canada)
DeepSeek (China)
Released
May 19, 2026
April 24, 2026
Context window
256K (unconfirmed) (~384 pages)
1M (~1,500 pages)
Price (in/out)
Open weight (self-host / free)
$0.66/$1.98 per 1M tokens
Open weight?
Yes — self-hostable
Yes — self-hostable
Modalities
text, code
text, code
SWE-Bench Verified
Not published
80.6%
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; DeepSeek V4 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; DeepSeek V4 does not.
Near-frontier coding at ~1/12 the cost: DeepSeek V4 — China's open-weight price earthquake — near-frontier capability at roughly a twelfth of GPT-5.5's cost — and it carries the larger 1M context.
Open MIT-licensed weights you can self-host: DeepSeek V4 — DeepSeek V4 lists open MIT-licensed weights you can self-host among its strengths; Command A+ does not.
No long-context surcharge: DeepSeek V4 — Its 1M window holds about 3.9× more than Command A+'s 256K (unconfirmed) in a single prompt.
Lowest cost at scale: Command A+ — Its weights are open, so at volume you pay for your own hardware instead of DeepSeek V4's $0.66/$1.98 per 1M tokens.
Largest single-prompt input: DeepSeek V4 — Its 1M window is about 3.9× larger than Command A+'s 256K (unconfirmed), fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume: Command A+ — At Open weight (self-host / free) it undercuts DeepSeek V4, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: DeepSeek V4 — Larger 1M window fits more in one prompt.
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 near-frontier coding at ~1/12 the cost: DeepSeek V4 — That is its strongest area.
An enterprise with regional data-residency rules: DeepSeek V4 or Command A+ — Origin (Canada vs China) 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.
DeepSeek V4: where it fits
China's open-weight price earthquake — near-frontier capability at roughly a twelfth of GPT-5.5's cost. Released April 24, 2026 by DeepSeek, it is built for near-frontier coding at ~1/12 the cost, open MIT-licensed weights you can self-host, no long-context surcharge, and highest LiveCodeBench result.
Its trade-offs: this generic 'V4' entry mirrors DeepSeek V4-Pro's specs - see DeepSeek V4-Pro and DeepSeek V4-Flash for DeepSeek's actual named product tiers, trails the very best on hardest agentic coding, and text/code focused, less multimodal. At $0.66 in / $1.98 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 DeepSeek V4 (China) 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 DeepSeek V4 better for coding?
Public SWE-Bench figures are not available for Command A+, 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 DeepSeek V4 leans toward near-frontier coding at ~1/12 the cost, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Command A+ or DeepSeek V4?
Command A+ is cheaper — Open weight (self-host / free) vs $0.66/$1.98 per 1M tokens.
Which has the bigger context window?
DeepSeek V4 — 1M vs 256K (unconfirmed), about 3.9× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Command A+ and DeepSeek V4 together?
Yes — a multi-model platform like LumiChats gives you Command A+, DeepSeek V4 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 DeepSeek V4?
Command A+ — released May 19, 2026, about 25 days after DeepSeek V4.
Command A+ vs DeepSeek V4
Cohere · Canada | DeepSeek · China · 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 DeepSeek V4 for near-frontier coding at ~1/12 the cost or open mit-licensed weights you can self-host. On a tight budget at scale, Command A+ is the value pick.
Command A+ (Cohere, Canada) and DeepSeek V4 (DeepSeek, China) 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. DeepSeek V4 is china's open-weight price earthquake — near-frontier capability at roughly a twelfth of GPT-5.5's cost. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences at a glance
▸Context window: DeepSeek V4 holds 3.9× more — 1M (~1,500 pages) vs 256K (unconfirmed) (~384 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 25 days (released May 19, 2026), usually meaning fresher training data and capabilities.
▸Ecosystem: this is a Canada-vs-China matchup — they differ in pricing philosophy, data-residency options, and tooling ecosystems, not only benchmarks.
Side-by-side specs
Spec
Command A+
DeepSeek V4
Provider
Cohere (Canada)
DeepSeek (China)
Released
May 19, 2026
April 24, 2026
Context window
256K (unconfirmed) (~384 pages)
1M (~1,500 pages)
Price (in/out)
Open weight (self-host / free)
$0.66/$1.98 per 1M tokens
Open weight?
Yes — self-hostable
Yes — self-hostable
Modalities
text, code
text, code
SWE-Bench Verified
Not published
80.6%
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; DeepSeek V4 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; DeepSeek V4 does not.
Near-frontier coding at ~1/12 the cost
DeepSeek V4
China's open-weight price earthquake — near-frontier capability at roughly a twelfth of GPT-5.5's cost — and it carries the larger 1M context.
Open MIT-licensed weights you can self-host
DeepSeek V4
DeepSeek V4 lists open MIT-licensed weights you can self-host among its strengths; Command A+ does not.
No long-context surcharge
DeepSeek V4
Its 1M window holds about 3.9× more than Command A+'s 256K (unconfirmed) in a single prompt.
Lowest cost at scale
Command A+
Its weights are open, so at volume you pay for your own hardware instead of DeepSeek V4's $0.66/$1.98 per 1M tokens.
Largest single-prompt input
DeepSeek V4
Its 1M window is about 3.9× larger than Command A+'s 256K (unconfirmed), fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ Command A+
At Open weight (self-host / free) it undercuts DeepSeek V4, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ DeepSeek V4
Larger 1M window fits more in one prompt.
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 near-frontier coding at ~1/12 the cost
→ DeepSeek V4
That is its strongest area.
An enterprise with regional data-residency rules
→ DeepSeek V4 or Command A+
Origin (Canada vs China) 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.
DeepSeek V4: where it fits
China's open-weight price earthquake — near-frontier capability at roughly a twelfth of GPT-5.5's cost. Released April 24, 2026 by DeepSeek, it is built for near-frontier coding at ~1/12 the cost, open MIT-licensed weights you can self-host, no long-context surcharge, and highest LiveCodeBench result.
Its trade-offs: this generic 'V4' entry mirrors DeepSeek V4-Pro's specs - see DeepSeek V4-Pro and DeepSeek V4-Flash for DeepSeek's actual named product tiers, trails the very best on hardest agentic coding, and text/code focused, less multimodal. At $0.66 in / $1.98 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 DeepSeek V4 (China) 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 DeepSeek V4 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 Command A+, 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 DeepSeek V4 leans toward near-frontier coding at ~1/12 the cost, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Command A+ or DeepSeek V4?
Command A+ is cheaper — Open weight (self-host / free) vs $0.66/$1.98 per 1M tokens.
Which has the bigger context window?
DeepSeek V4 — 1M vs 256K (unconfirmed), about 3.9× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Command A+ and DeepSeek V4 together?
Yes — a multi-model platform like LumiChats gives you Command A+, DeepSeek V4 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 DeepSeek V4?
Command A+ — released May 19, 2026, about 25 days after DeepSeek V4.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.