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 V3.2 for long-context efficiency via deepseek sparse attention (dsa) or agentic tool-use with thinking integrated into tool calls (thinking/non-thinking modes). On a tight budget at scale, Command A+ is the value pick.
Command A+ (Cohere, Canada) and DeepSeek V3.2 (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 V3.2 is a cost-efficient, open-weight (MIT) 685B-parameter MoE model whose DeepSeek Sparse Attention delivers GPT-5-comparable reasoning with far cheaper long-context inference. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences
Context window: Command A+ holds 2× more — 256K (unconfirmed) (~384 pages) vs 131K (~197 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 6 months (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 V3.2
Provider
Cohere (Canada)
DeepSeek (China)
Released
May 19, 2026
December 1, 2025
Context window
256K (unconfirmed) (~384 pages)
131K (~197 pages)
Price (in/out)
Open weight (self-host / free)
$0.28/$0.42 per 1M tokens
Open weight?
Yes — self-hostable
Yes — self-hostable
Modalities
text, code
text, code
SWE-Bench Verified
Not published
73.1%
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just two H100 GPUs, unusually lean for a 218B-parameter model: Command A+ — DeepSeek V3.2 is comparatively weak here — superseded - no longer listed on DeepSeek's current pricing page as of August 2026; DeepSeek V4-Flash/V4-Pro are the current models
A 218B-total/25B-active MoE released with open weights (Apache 2.0) on Hugging Face: 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 carries the larger 256K (unconfirmed) context.
Supports 48 languages, including all official EU languages: 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.
Long-context efficiency via DeepSeek Sparse Attention (DSA): DeepSeek V3.2 — Command A+ is comparatively weak here — no official context window or per-token price published yet - both are estimated/unavailable
Agentic tool-use with thinking integrated into tool calls (thinking/non-thinking modes): DeepSeek V3.2 — DeepSeek V3.2 lists agentic tool-use with thinking integrated into tool calls (thinking/non-thinking modes) among its strengths; Command A+ does not.
Elite competition math and reasoning (AIME 2025 93.1, Codeforces 2386): DeepSeek V3.2 — Command A+ is comparatively weak here — enterprise/multilingual focus rather than topping general reasoning leaderboards
Lowest cost at scale: Command A+ — Its weights are open, so at volume you pay for your own hardware instead of DeepSeek V3.2's $0.28/$0.42 per 1M tokens.
Largest single-prompt input: Command A+ — Its 256K (unconfirmed) window is about 2× larger than DeepSeek V3.2's 131K, fitting roughly 384 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 V3.2, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: Command A+ — Larger 256K (unconfirmed) 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 long-context efficiency via deepseek sparse attention (dsa): DeepSeek V3.2 — That is its strongest area.
An enterprise with regional data-residency rules: DeepSeek V3.2 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 V3.2: where it fits
A cost-efficient, open-weight (MIT) 685B-parameter MoE model whose DeepSeek Sparse Attention delivers GPT-5-comparable reasoning with far cheaper long-context inference. Released December 1, 2025 by DeepSeek, it is built for long-context efficiency via DeepSeek Sparse Attention (DSA), agentic tool-use with thinking integrated into tool calls (thinking/non-thinking modes), elite competition math and reasoning (AIME 2025 93.1, Codeforces 2386), and low-cost, open-weight (MIT) self-hosting.
Its trade-offs: superseded - no longer listed on DeepSeek's current pricing page as of August 2026; DeepSeek V4-Flash/V4-Pro are the current models, text-only — no image, audio, or video input, and sWE-Bench Verified (73.1) trails the top closed coding models (Claude 4.5 Sonnet 77.2, Gemini 3 Pro 76.2). At $0.28 in / $0.42 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 V3.2 (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 V3.2 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 V3.2 leans toward long-context efficiency via deepseek sparse attention (dsa), and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Command A+ or DeepSeek V3.2?
Command A+ is cheaper — Open weight (self-host / free) vs $0.28/$0.42 per 1M tokens.
Which has the bigger context window?
Command A+ — 256K (unconfirmed) vs 131K, 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 DeepSeek V3.2 together?
Yes — a multi-model platform like LumiChats gives you Command A+, DeepSeek V3.2 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 V3.2?
Command A+ — released May 19, 2026, about 6 months after DeepSeek V3.2.
Command A+ vs DeepSeek V3.2
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 V3.2 for long-context efficiency via deepseek sparse attention (dsa) or agentic tool-use with thinking integrated into tool calls (thinking/non-thinking modes). On a tight budget at scale, Command A+ is the value pick.
Command A+ (Cohere, Canada) and DeepSeek V3.2 (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 V3.2 is a cost-efficient, open-weight (MIT) 685B-parameter MoE model whose DeepSeek Sparse Attention delivers GPT-5-comparable reasoning with far cheaper long-context inference. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences at a glance
▸Context window: Command A+ holds 2× more — 256K (unconfirmed) (~384 pages) vs 131K (~197 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 6 months (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 V3.2
Provider
Cohere (Canada)
DeepSeek (China)
Released
May 19, 2026
December 1, 2025
Context window
256K (unconfirmed) (~384 pages)
131K (~197 pages)
Price (in/out)
Open weight (self-host / free)
$0.28/$0.42 per 1M tokens
Open weight?
Yes — self-hostable
Yes — self-hostable
Modalities
text, code
text, code
SWE-Bench Verified
Not published
73.1%
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+
DeepSeek V3.2 is comparatively weak here — superseded - no longer listed on DeepSeek's current pricing page as of August 2026; DeepSeek V4-Flash/V4-Pro are the current models
A 218B-total/25B-active MoE released with open weights (Apache 2.0) on Hugging Face
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 carries the larger 256K (unconfirmed) context.
Supports 48 languages, including all official EU languages
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.
Long-context efficiency via DeepSeek Sparse Attention (DSA)
DeepSeek V3.2
Command A+ is comparatively weak here — no official context window or per-token price published yet - both are estimated/unavailable
Agentic tool-use with thinking integrated into tool calls (thinking/non-thinking modes)
DeepSeek V3.2
DeepSeek V3.2 lists agentic tool-use with thinking integrated into tool calls (thinking/non-thinking modes) among its strengths; Command A+ does not.
Elite competition math and reasoning (AIME 2025 93.1, Codeforces 2386)
DeepSeek V3.2
Command A+ is comparatively weak here — enterprise/multilingual focus rather than topping general reasoning leaderboards
Lowest cost at scale
Command A+
Its weights are open, so at volume you pay for your own hardware instead of DeepSeek V3.2's $0.28/$0.42 per 1M tokens.
Largest single-prompt input
Command A+
Its 256K (unconfirmed) window is about 2× larger than DeepSeek V3.2's 131K, fitting roughly 384 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 V3.2, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ Command A+
Larger 256K (unconfirmed) 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 long-context efficiency via deepseek sparse attention (dsa)
→ DeepSeek V3.2
That is its strongest area.
An enterprise with regional data-residency rules
→ DeepSeek V3.2 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 V3.2: where it fits
A cost-efficient, open-weight (MIT) 685B-parameter MoE model whose DeepSeek Sparse Attention delivers GPT-5-comparable reasoning with far cheaper long-context inference. Released December 1, 2025 by DeepSeek, it is built for long-context efficiency via DeepSeek Sparse Attention (DSA), agentic tool-use with thinking integrated into tool calls (thinking/non-thinking modes), elite competition math and reasoning (AIME 2025 93.1, Codeforces 2386), and low-cost, open-weight (MIT) self-hosting.
Its trade-offs: superseded - no longer listed on DeepSeek's current pricing page as of August 2026; DeepSeek V4-Flash/V4-Pro are the current models, text-only — no image, audio, or video input, and sWE-Bench Verified (73.1) trails the top closed coding models (Claude 4.5 Sonnet 77.2, Gemini 3 Pro 76.2). At $0.28 in / $0.42 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 V3.2 (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 V3.2 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 V3.2 leans toward long-context efficiency via deepseek sparse attention (dsa), and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Command A+ or DeepSeek V3.2?
Command A+ is cheaper — Open weight (self-host / free) vs $0.28/$0.42 per 1M tokens.
Which has the bigger context window?
Command A+ — 256K (unconfirmed) vs 131K, 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 DeepSeek V3.2 together?
Yes — a multi-model platform like LumiChats gives you Command A+, DeepSeek V3.2 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 V3.2?
Command A+ — released May 19, 2026, about 6 months after DeepSeek V3.2.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.