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 Qwen3.6 35B A3B for extreme sparsity — only 3b of 35b parameters active per token, giving near-3b inference cost or runs at roughly 120 tokens per second on a single 24gb consumer gpu.
Command A+ (Cohere, Canada) and Qwen3.6 35B A3B (Alibaba, 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. Qwen3.6 35B A3B is a sparse 35B mixture-of-experts running on 3B active parameters — strong agentic coding at near-3B cost on consumer hardware. Their biggest split is context window, and the breakdown below shows exactly how that plays out for your workload.
Key differences
Context window: 256K (unconfirmed) vs 256K — within a few percent of each other, so treat this as a tie and test on your own long inputs, since usable recall varies by model.
Recency: Command A+ is the newer model by about 33 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+
Qwen3.6 35B A3B
Provider
Cohere (Canada)
Alibaba (China)
Released
May 19, 2026
April 16, 2026
Context window
256K (unconfirmed) (~384 pages)
256K (~393 pages)
Price (in/out)
Open weight (self-host / free)
Open weight (self-host / free)
Open weight?
Yes — self-hostable
Yes — self-hostable
Modalities
text, code
text, image, code
SWE-Bench Verified
Not published
73.4%
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+ — Qwen3.6 35B A3B is comparatively weak here — loses to its smaller dense sibling Qwen3.6 27B on every coding benchmark, despite more total parameters
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 is the newer of the two.
Supports 48 languages, including all official EU languages: Command A+ — Command A+ lists supports 48 languages, including all official EU languages among its strengths; Qwen3.6 35B A3B does not.
Extreme sparsity — only 3B of 35B parameters active per token, giving near-3B inference cost: Qwen3.6 35B A3B — Command A+ is comparatively weak here — no official context window or per-token price published yet - both are estimated/unavailable
Runs at roughly 120 tokens per second on a single 24GB consumer GPU: Qwen3.6 35B A3B — Qwen3.6 35B A3B lists runs at roughly 120 tokens per second on a single 24GB consumer GPU among its strengths; Command A+ does not.
Apache 2.0 weights with a 256K native context, extensible to about 1M via YaRN: Qwen3.6 35B A3B — Qwen3.6 35B A3B lists apache 2.0 weights with a 256K native context, extensible to about 1M via YaRN among its strengths; Command A+ does not.
Which should you pick?
Someone analysing very long documents or codebases: Qwen3.6 35B A3B — Larger 256K 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 extreme sparsity — only 3b of 35b parameters active per token, giving near-3b inference cost: Qwen3.6 35B A3B — That is its strongest area.
An enterprise with regional data-residency rules: Qwen3.6 35B A3B 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.
Qwen3.6 35B A3B: where it fits
A sparse 35B mixture-of-experts running on 3B active parameters — strong agentic coding at near-3B cost on consumer hardware. Released April 16, 2026 by Alibaba, it is built for extreme sparsity — only 3B of 35B parameters active per token, giving near-3B inference cost, runs at roughly 120 tokens per second on a single 24GB consumer GPU, apache 2.0 weights with a 256K native context, extensible to about 1M via YaRN, and preserves its reasoning across turns, which cuts the overhead of agentic loops.
Its trade-offs: loses to its smaller dense sibling Qwen3.6 27B on every coding benchmark, despite more total parameters, its SWE-Bench score comes from Alibaba's internal scaffold rather than the standard public harness, and all 35B parameters must stay resident in VRAM even though only 3B compute per token. As an open-weight model, its running cost is your own hardware rather than a per-token fee.
The bottom line for this matchup
This is less "which is smarter" and more "which ecosystem fits." Command A+ (Canada) and Qwen3.6 35B A3B (China) differ on pricing philosophy, data-residency, and tooling as much as on raw scores. 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 Qwen3.6 35B A3B 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 Qwen3.6 35B A3B leans toward extreme sparsity — only 3b of 35b parameters active per token, giving near-3b inference cost, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Command A+ or Qwen3.6 35B A3B?
They are priced almost identically, so cost will not decide between them.
Which has the bigger context window?
Effectively neither — 256K (unconfirmed) vs 256K is a difference of a few percent. Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both Command A+ and Qwen3.6 35B A3B together?
Yes — a multi-model platform like LumiChats gives you Command A+, Qwen3.6 35B A3B 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 Qwen3.6 35B A3B?
Command A+ — released May 19, 2026, about 33 days after Qwen3.6 35B A3B.
Command A+ vs Qwen3.6 35B A3B
Cohere · Canada | Alibaba · 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 Qwen3.6 35B A3B for extreme sparsity — only 3b of 35b parameters active per token, giving near-3b inference cost or runs at roughly 120 tokens per second on a single 24gb consumer gpu.
Command A+ (Cohere, Canada) and Qwen3.6 35B A3B (Alibaba, 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. Qwen3.6 35B A3B is a sparse 35B mixture-of-experts running on 3B active parameters — strong agentic coding at near-3B cost on consumer hardware. Their biggest split is context window, and the breakdown below shows exactly how that plays out for your workload.
Key differences at a glance
▸Context window: 256K (unconfirmed) vs 256K — within a few percent of each other, so treat this as a tie and test on your own long inputs, since usable recall varies by model.
▸Recency: Command A+ is the newer model by about 33 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+
Qwen3.6 35B A3B
Provider
Cohere (Canada)
Alibaba (China)
Released
May 19, 2026
April 16, 2026
Context window
256K (unconfirmed) (~384 pages)
256K (~393 pages)
Price (in/out)
Open weight (self-host / free)
Open weight (self-host / free)
Open weight?
Yes — self-hostable
Yes — self-hostable
Modalities
text, code
text, image, code
SWE-Bench Verified
Not published
73.4%
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+
Qwen3.6 35B A3B is comparatively weak here — loses to its smaller dense sibling Qwen3.6 27B on every coding benchmark, despite more total parameters
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 is the newer of the two.
Supports 48 languages, including all official EU languages
Command A+
Command A+ lists supports 48 languages, including all official EU languages among its strengths; Qwen3.6 35B A3B does not.
Extreme sparsity — only 3B of 35B parameters active per token, giving near-3B inference cost
Qwen3.6 35B A3B
Command A+ is comparatively weak here — no official context window or per-token price published yet - both are estimated/unavailable
Runs at roughly 120 tokens per second on a single 24GB consumer GPU
Qwen3.6 35B A3B
Qwen3.6 35B A3B lists runs at roughly 120 tokens per second on a single 24GB consumer GPU among its strengths; Command A+ does not.
Apache 2.0 weights with a 256K native context, extensible to about 1M via YaRN
Qwen3.6 35B A3B
Qwen3.6 35B A3B lists apache 2.0 weights with a 256K native context, extensible to about 1M via YaRN among its strengths; Command A+ does not.
Which should you pick?
Someone analysing very long documents or codebases
→ Qwen3.6 35B A3B
Larger 256K 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 extreme sparsity — only 3b of 35b parameters active per token, giving near-3b inference cost
→ Qwen3.6 35B A3B
That is its strongest area.
An enterprise with regional data-residency rules
→ Qwen3.6 35B A3B 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.
Qwen3.6 35B A3B: where it fits
A sparse 35B mixture-of-experts running on 3B active parameters — strong agentic coding at near-3B cost on consumer hardware. Released April 16, 2026 by Alibaba, it is built for extreme sparsity — only 3B of 35B parameters active per token, giving near-3B inference cost, runs at roughly 120 tokens per second on a single 24GB consumer GPU, apache 2.0 weights with a 256K native context, extensible to about 1M via YaRN, and preserves its reasoning across turns, which cuts the overhead of agentic loops.
Its trade-offs: loses to its smaller dense sibling Qwen3.6 27B on every coding benchmark, despite more total parameters, its SWE-Bench score comes from Alibaba's internal scaffold rather than the standard public harness, and all 35B parameters must stay resident in VRAM even though only 3B compute per token. As an open-weight model, its running cost is your own hardware rather than a per-token fee.
The bottom line for this matchup
This is less "which is smarter" and more "which ecosystem fits." Command A+ (Canada) and Qwen3.6 35B A3B (China) differ on pricing philosophy, data-residency, and tooling as much as on raw scores. 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 Qwen3.6 35B A3B 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 Qwen3.6 35B A3B 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 Qwen3.6 35B A3B leans toward extreme sparsity — only 3b of 35b parameters active per token, giving near-3b inference cost, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Command A+ or Qwen3.6 35B A3B?
They are priced almost identically, so cost will not decide between them.
Which has the bigger context window?
Effectively neither — 256K (unconfirmed) vs 256K is a difference of a few percent. Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both Command A+ and Qwen3.6 35B A3B together?
Yes — a multi-model platform like LumiChats gives you Command A+, Qwen3.6 35B A3B 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 Qwen3.6 35B A3B?
Command A+ — released May 19, 2026, about 33 days after Qwen3.6 35B A3B.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.