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 Reka Flash 3.1 for a 21b-parameter reasoning model, small enough for local/on-device deployment (a 3.5-bit quantized build exists) or strong base for fine-tuning agentic tasks - notably improved coding since the original flash 3.
Command A+ (Cohere, Canada) and Reka Flash 3.1 (Reka AI, 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. Reka Flash 3.1 is reka AI's compact 21B open-weight reasoning model - small enough to run locally, from a team of DeepMind and Meta alumni. Their biggest split is context window, and the breakdown below shows exactly how that plays out for your workload.
Key differences
Context window: Command A+ holds 7.8× more — 256K (unconfirmed) (~384 pages) vs 32K (~49 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 11 months (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+
Reka Flash 3.1
Provider
Cohere (Canada)
Reka AI (US)
Released
May 19, 2026
July 2025
Context window
256K (unconfirmed) (~384 pages)
32K (~49 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, 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+ — Reka Flash 3.1 is comparatively weak here — a relatively small 32K context window next to million-token frontier 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.
A 21B-parameter reasoning model, small enough for local/on-device deployment (a 3.5-bit quantized build exists): Reka Flash 3.1 — Command A+ is comparatively weak here — enterprise/multilingual focus rather than topping general reasoning leaderboards
Strong base for fine-tuning agentic tasks - notably improved coding since the original Flash 3: Reka Flash 3.1 — Reka Flash 3.1 lists strong base for fine-tuning agentic tasks - notably improved coding since the original Flash 3 among its strengths; Command A+ does not.
Fully open weights (Apache 2.0) from a frontier-caliber research team: Reka Flash 3.1 — Reka Flash 3.1 lists fully open weights (Apache 2.0) from a frontier-caliber research team among its strengths; Command A+ does not.
Largest single-prompt input: Command A+ — Its 256K (unconfirmed) window is about 7.8× larger than Reka Flash 3.1's 32K, fitting roughly 384 pages in one prompt.
Which should you pick?
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 a 21b-parameter reasoning model, small enough for local/on-device deployment (a 3.5-bit quantized build exists): Reka Flash 3.1 — That is its strongest area.
An enterprise with regional data-residency rules: Reka Flash 3.1 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.
Reka Flash 3.1: where it fits
Reka AI's compact 21B open-weight reasoning model - small enough to run locally, from a team of DeepMind and Meta alumni. Released July 2025 by Reka AI, it is built for a 21B-parameter reasoning model, small enough for local/on-device deployment (a 3.5-bit quantized build exists), strong base for fine-tuning agentic tasks - notably improved coding since the original Flash 3, fully open weights (Apache 2.0) from a frontier-caliber research team, and built by alumni from Google DeepMind and Meta's AI labs.
Its trade-offs: a relatively small 32K context window next to million-token frontier models, smaller and less capable overall than flagship frontier models from major labs, and reka's broader roadmap has shifted toward robotics/world models after merging with Moonvalley in June 2026, raising questions about ongoing LLM investment. 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 Reka Flash 3.1 (US) 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 Reka Flash 3.1 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 Reka Flash 3.1 leans toward a 21b-parameter reasoning model, small enough for local/on-device deployment (a 3.5-bit quantized build exists), and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Command A+ or Reka Flash 3.1?
They are priced almost identically, so cost will not decide between them.
Which has the bigger context window?
Command A+ — 256K (unconfirmed) vs 32K, about 7.8× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Command A+ and Reka Flash 3.1 together?
Yes — a multi-model platform like LumiChats gives you Command A+, Reka Flash 3.1 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 Reka Flash 3.1?
Command A+ — released May 19, 2026, about 11 months after Reka Flash 3.1.
Command A+ vs Reka Flash 3.1
Cohere · Canada | Reka AI · 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 Reka Flash 3.1 for a 21b-parameter reasoning model, small enough for local/on-device deployment (a 3.5-bit quantized build exists) or strong base for fine-tuning agentic tasks - notably improved coding since the original flash 3.
Command A+ (Cohere, Canada) and Reka Flash 3.1 (Reka AI, 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. Reka Flash 3.1 is reka AI's compact 21B open-weight reasoning model - small enough to run locally, from a team of DeepMind and Meta alumni. 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: Command A+ holds 7.8× more — 256K (unconfirmed) (~384 pages) vs 32K (~49 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 11 months (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+
Reka Flash 3.1
Provider
Cohere (Canada)
Reka AI (US)
Released
May 19, 2026
July 2025
Context window
256K (unconfirmed) (~384 pages)
32K (~49 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, 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+
Reka Flash 3.1 is comparatively weak here — a relatively small 32K context window next to million-token frontier 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.
A 21B-parameter reasoning model, small enough for local/on-device deployment (a 3.5-bit quantized build exists)
Reka Flash 3.1
Command A+ is comparatively weak here — enterprise/multilingual focus rather than topping general reasoning leaderboards
Strong base for fine-tuning agentic tasks - notably improved coding since the original Flash 3
Reka Flash 3.1
Reka Flash 3.1 lists strong base for fine-tuning agentic tasks - notably improved coding since the original Flash 3 among its strengths; Command A+ does not.
Fully open weights (Apache 2.0) from a frontier-caliber research team
Reka Flash 3.1
Reka Flash 3.1 lists fully open weights (Apache 2.0) from a frontier-caliber research team among its strengths; Command A+ does not.
Largest single-prompt input
Command A+
Its 256K (unconfirmed) window is about 7.8× larger than Reka Flash 3.1's 32K, fitting roughly 384 pages in one prompt.
Which should you pick?
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 a 21b-parameter reasoning model, small enough for local/on-device deployment (a 3.5-bit quantized build exists)
→ Reka Flash 3.1
That is its strongest area.
An enterprise with regional data-residency rules
→ Reka Flash 3.1 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.
Reka Flash 3.1: where it fits
Reka AI's compact 21B open-weight reasoning model - small enough to run locally, from a team of DeepMind and Meta alumni. Released July 2025 by Reka AI, it is built for a 21B-parameter reasoning model, small enough for local/on-device deployment (a 3.5-bit quantized build exists), strong base for fine-tuning agentic tasks - notably improved coding since the original Flash 3, fully open weights (Apache 2.0) from a frontier-caliber research team, and built by alumni from Google DeepMind and Meta's AI labs.
Its trade-offs: a relatively small 32K context window next to million-token frontier models, smaller and less capable overall than flagship frontier models from major labs, and reka's broader roadmap has shifted toward robotics/world models after merging with Moonvalley in June 2026, raising questions about ongoing LLM investment. 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 Reka Flash 3.1 (US) 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 Reka Flash 3.1 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 Reka Flash 3.1 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 Reka Flash 3.1 leans toward a 21b-parameter reasoning model, small enough for local/on-device deployment (a 3.5-bit quantized build exists), and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Command A+ or Reka Flash 3.1?
They are priced almost identically, so cost will not decide between them.
Which has the bigger context window?
Command A+ — 256K (unconfirmed) vs 32K, about 7.8× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Command A+ and Reka Flash 3.1 together?
Yes — a multi-model platform like LumiChats gives you Command A+, Reka Flash 3.1 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 Reka Flash 3.1?
Command A+ — released May 19, 2026, about 11 months after Reka Flash 3.1.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.