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 Gemma 4 26B A4B for fast, cheap inference from a sparse moe (3.8b active of 25.2b total) or near-31b-dense quality at a fraction of the compute and memory-bandwidth cost. On a tight budget at scale, Command A+ is the value pick.
Command A+ (Cohere, Canada) and Gemma 4 26B A4B (Google, US) 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. Gemma 4 26B A4B is an Apache-2.0 open MoE with 25.2B total but only 3.8B active parameters, delivering near-31B-dense quality at a fraction of the inference cost. They diverge most on price and context window — each quantified below from the models' real specs.
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 47 days (released May 19, 2026), usually meaning fresher training data and capabilities.
Ecosystem: this is a Canada-vs-US matchup — they differ in pricing philosophy, data-residency options, and tooling ecosystems, not only benchmarks.
Specifications
Spec
Command A+
Gemma 4 26B A4B
Provider
Cohere (Canada)
Google (US)
Released
May 19, 2026
April 2, 2026
Context window
256K (unconfirmed) (~384 pages)
256K (~393 pages)
Price (in/out)
Open weight (self-host / free)
$0.12/$0.37 per 1M tokens
Open weight?
Yes — self-hostable
Yes — self-hostable
Modalities
text, code
text, image, video, 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+ — Gemma 4 26B A4B is comparatively weak here — all 25.2B parameters must be loaded into memory even though only 3.8B are active per token
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; Gemma 4 26B A4B does not.
Fast, cheap inference from a sparse MoE (3.8B active of 25.2B total): Gemma 4 26B A4B — Gemma 4 26B A4B lists fast, cheap inference from a sparse MoE (3.8B active of 25.2B total) among its strengths; Command A+ does not.
Near-31B-dense quality at a fraction of the compute and memory-bandwidth cost: Gemma 4 26B A4B — Gemma 4 26B A4B lists near-31B-dense quality at a fraction of the compute and memory-bandwidth cost among its strengths; Command A+ does not.
Strong reasoning and coding (88.3% AIME 2026 no-tools, 77.1% LiveCodeBench v6): Gemma 4 26B A4B — 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 Gemma 4 26B A4B's $0.12/$0.37 per 1M tokens.
Which should you pick?
A cost-sensitive startup shipping high volume: Command A+ — At Open weight (self-host / free) it undercuts Gemma 4 26B A4B, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: Gemma 4 26B A4B — 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 fast, cheap inference from a sparse moe (3.8b active of 25.2b total): Gemma 4 26B A4B — That is its strongest area.
An enterprise with regional data-residency rules: Gemma 4 26B A4B or Command A+ — Origin (Canada vs US) 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.
Gemma 4 26B A4B: where it fits
An Apache-2.0 open MoE with 25.2B total but only 3.8B active parameters, delivering near-31B-dense quality at a fraction of the inference cost. Released April 2, 2026 by Google, it is built for fast, cheap inference from a sparse MoE (3.8B active of 25.2B total), near-31B-dense quality at a fraction of the compute and memory-bandwidth cost, strong reasoning and coding (88.3% AIME 2026 no-tools, 77.1% LiveCodeBench v6), and multimodal input (text/image, plus video processed as frames up to 60s) with native function calling.
Its trade-offs: all 25.2B parameters must be loaded into memory even though only 3.8B are active per token, and 256K context trails 1M-token frontier rivals, and this variant has no audio input (audio is E2B/E4B/12B only). At $0.12 in / $0.37 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 Gemma 4 26B A4B (US) 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 Gemma 4 26B A4B 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 Gemma 4 26B A4B leans toward fast, cheap inference from a sparse moe (3.8b active of 25.2b total), and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Command A+ or Gemma 4 26B A4B?
Command A+ is cheaper — Open weight (self-host / free) vs $0.12/$0.37 per 1M tokens.
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 Gemma 4 26B A4B together?
Yes — a multi-model platform like LumiChats gives you Command A+, Gemma 4 26B A4B 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 Gemma 4 26B A4B?
Command A+ — released May 19, 2026, about 47 days after Gemma 4 26B A4B.
Command A+ vs Gemma 4 26B A4B
Cohere · Canada | Google · US · 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 Gemma 4 26B A4B for fast, cheap inference from a sparse moe (3.8b active of 25.2b total) or near-31b-dense quality at a fraction of the compute and memory-bandwidth cost. On a tight budget at scale, Command A+ is the value pick.
Command A+ (Cohere, Canada) and Gemma 4 26B A4B (Google, US) 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. Gemma 4 26B A4B is an Apache-2.0 open MoE with 25.2B total but only 3.8B active parameters, delivering near-31B-dense quality at a fraction of the inference cost. They diverge most on price and context window — each quantified below from the models' real specs.
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 47 days (released May 19, 2026), usually meaning fresher training data and capabilities.
▸Ecosystem: this is a Canada-vs-US matchup — they differ in pricing philosophy, data-residency options, and tooling ecosystems, not only benchmarks.
Side-by-side specs
Spec
Command A+
Gemma 4 26B A4B
Provider
Cohere (Canada)
Google (US)
Released
May 19, 2026
April 2, 2026
Context window
256K (unconfirmed) (~384 pages)
256K (~393 pages)
Price (in/out)
Open weight (self-host / free)
$0.12/$0.37 per 1M tokens
Open weight?
Yes — self-hostable
Yes — self-hostable
Modalities
text, code
text, image, video, 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+
Gemma 4 26B A4B is comparatively weak here — all 25.2B parameters must be loaded into memory even though only 3.8B are active per token
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; Gemma 4 26B A4B does not.
Fast, cheap inference from a sparse MoE (3.8B active of 25.2B total)
Gemma 4 26B A4B
Gemma 4 26B A4B lists fast, cheap inference from a sparse MoE (3.8B active of 25.2B total) among its strengths; Command A+ does not.
Near-31B-dense quality at a fraction of the compute and memory-bandwidth cost
Gemma 4 26B A4B
Gemma 4 26B A4B lists near-31B-dense quality at a fraction of the compute and memory-bandwidth cost among its strengths; Command A+ does not.
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 Gemma 4 26B A4B's $0.12/$0.37 per 1M tokens.
Which should you pick?
A cost-sensitive startup shipping high volume
→ Command A+
At Open weight (self-host / free) it undercuts Gemma 4 26B A4B, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ Gemma 4 26B A4B
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 fast, cheap inference from a sparse moe (3.8b active of 25.2b total)
→ Gemma 4 26B A4B
That is its strongest area.
An enterprise with regional data-residency rules
→ Gemma 4 26B A4B or Command A+
Origin (Canada vs US) 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.
Gemma 4 26B A4B: where it fits
An Apache-2.0 open MoE with 25.2B total but only 3.8B active parameters, delivering near-31B-dense quality at a fraction of the inference cost. Released April 2, 2026 by Google, it is built for fast, cheap inference from a sparse MoE (3.8B active of 25.2B total), near-31B-dense quality at a fraction of the compute and memory-bandwidth cost, strong reasoning and coding (88.3% AIME 2026 no-tools, 77.1% LiveCodeBench v6), and multimodal input (text/image, plus video processed as frames up to 60s) with native function calling.
Its trade-offs: all 25.2B parameters must be loaded into memory even though only 3.8B are active per token, and 256K context trails 1M-token frontier rivals, and this variant has no audio input (audio is E2B/E4B/12B only). At $0.12 in / $0.37 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 Gemma 4 26B A4B (US) 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 Gemma 4 26B A4B 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 Gemma 4 26B A4B 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 Gemma 4 26B A4B leans toward fast, cheap inference from a sparse moe (3.8b active of 25.2b total), and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Command A+ or Gemma 4 26B A4B?
Command A+ is cheaper — Open weight (self-host / free) vs $0.12/$0.37 per 1M tokens.
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 Gemma 4 26B A4B together?
Yes — a multi-model platform like LumiChats gives you Command A+, Gemma 4 26B A4B 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 Gemma 4 26B A4B?
Command A+ — released May 19, 2026, about 47 days after Gemma 4 26B A4B.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.