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 Inkling for the first model release from mira murati's thinking machines lab (ex-openai cto) - one of the most closely-watched new labs in ai or a 975b-parameter moe (41b active) with native text, image, and audio reasoning in one model.
Command A+ (Cohere, Canada) and Inkling (Thinking Machines Lab, 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. Inkling is mira Murati's Thinking Machines Lab debuts with Inkling - a 975B open-weight MoE with native multimodal reasoning and a dialable thinking-effort control. Their biggest split is context window, and the breakdown below shows exactly how that plays out for your workload.
Key differences
Context window: Inkling 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: Inkling is the newer model by about 57 days (released July 15, 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+
Inkling
Provider
Cohere (Canada)
Thinking Machines Lab (US)
Released
May 19, 2026
July 15, 2026
Context window
256K (unconfirmed) (~384 pages)
1M (~1,500 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, audio, 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+ — Command A+ lists cohere's newer, more efficient flagship - runs on just two H100 GPUs, unusually lean for a 218B-parameter model among its strengths; Inkling does not.
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; Inkling does not.
Supports 48 languages, including all official EU languages: Command A+ — Inkling is comparatively weak here — no official hosted API price - available via third-party hosts only at launch
The first model release from Mira Murati's Thinking Machines Lab (ex-OpenAI CTO) - one of the most closely-watched new labs in AI: Inkling — Command A+ is comparatively weak here — newer release with less independent benchmark verification than established flagships
A 975B-parameter MoE (41B active) with native text, image, and audio reasoning in one model: Inkling — Command A+ is comparatively weak here — enterprise/multilingual focus rather than topping general reasoning leaderboards
A dialable 'thinking effort' knob (0.2-0.99) that lets you trade speed for depth of reasoning per-request: Inkling — Mira Murati's Thinking Machines Lab debuts with Inkling - a 975B open-weight MoE with native multimodal reasoning and a dialable thinking-effort control — and it carries the larger 1M context.
Largest single-prompt input: Inkling — 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?
Someone analysing very long documents or codebases: Inkling — 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 the first model release from mira murati's thinking machines lab (ex-openai cto) - one of the most closely-watched new labs in ai: Inkling — That is its strongest area.
An enterprise with regional data-residency rules: Inkling 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.
Inkling: where it fits
Mira Murati's Thinking Machines Lab debuts with Inkling - a 975B open-weight MoE with native multimodal reasoning and a dialable thinking-effort control. Released July 15, 2026 by Thinking Machines Lab, it is built for the first model release from Mira Murati's Thinking Machines Lab (ex-OpenAI CTO) - one of the most closely-watched new labs in AI, a 975B-parameter MoE (41B active) with native text, image, and audio reasoning in one model, a dialable 'thinking effort' knob (0.2-0.99) that lets you trade speed for depth of reasoning per-request, and fully open weights (Apache 2.0) at frontier scale - unusual for a model this large and this new.
Its trade-offs: a brand-new lab's first release - no multi-generation track record yet, no official hosted API price - available via third-party hosts only at launch, and independent third-party benchmark verification is still limited given how recently it shipped. 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 Inkling (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 Inkling 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 Inkling leans toward the first model release from mira murati's thinking machines lab (ex-openai cto) - one of the most closely-watched new labs in ai, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Command A+ or Inkling?
They are priced almost identically, so cost will not decide between them.
Which has the bigger context window?
Inkling — 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 Inkling together?
Yes — a multi-model platform like LumiChats gives you Command A+, Inkling 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 Inkling?
Inkling — released July 15, 2026, about 57 days after Command A+.
Command A+ vs Inkling
Cohere · Canada | Thinking Machines Lab · 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 Inkling for the first model release from mira murati's thinking machines lab (ex-openai cto) - one of the most closely-watched new labs in ai or a 975b-parameter moe (41b active) with native text, image, and audio reasoning in one model.
Command A+ (Cohere, Canada) and Inkling (Thinking Machines Lab, 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. Inkling is mira Murati's Thinking Machines Lab debuts with Inkling - a 975B open-weight MoE with native multimodal reasoning and a dialable thinking-effort control. 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: Inkling 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: Inkling is the newer model by about 57 days (released July 15, 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+
Inkling
Provider
Cohere (Canada)
Thinking Machines Lab (US)
Released
May 19, 2026
July 15, 2026
Context window
256K (unconfirmed) (~384 pages)
1M (~1,500 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, audio, 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+
Command A+ lists cohere's newer, more efficient flagship - runs on just two H100 GPUs, unusually lean for a 218B-parameter model among its strengths; Inkling does not.
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; Inkling does not.
Supports 48 languages, including all official EU languages
Command A+
Inkling is comparatively weak here — no official hosted API price - available via third-party hosts only at launch
The first model release from Mira Murati's Thinking Machines Lab (ex-OpenAI CTO) - one of the most closely-watched new labs in AI
Inkling
Command A+ is comparatively weak here — newer release with less independent benchmark verification than established flagships
A 975B-parameter MoE (41B active) with native text, image, and audio reasoning in one model
Inkling
Command A+ is comparatively weak here — enterprise/multilingual focus rather than topping general reasoning leaderboards
A dialable 'thinking effort' knob (0.2-0.99) that lets you trade speed for depth of reasoning per-request
Inkling
Mira Murati's Thinking Machines Lab debuts with Inkling - a 975B open-weight MoE with native multimodal reasoning and a dialable thinking-effort control — and it carries the larger 1M context.
Largest single-prompt input
Inkling
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?
Someone analysing very long documents or codebases
→ Inkling
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 the first model release from mira murati's thinking machines lab (ex-openai cto) - one of the most closely-watched new labs in ai
→ Inkling
That is its strongest area.
An enterprise with regional data-residency rules
→ Inkling 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.
Inkling: where it fits
Mira Murati's Thinking Machines Lab debuts with Inkling - a 975B open-weight MoE with native multimodal reasoning and a dialable thinking-effort control. Released July 15, 2026 by Thinking Machines Lab, it is built for the first model release from Mira Murati's Thinking Machines Lab (ex-OpenAI CTO) - one of the most closely-watched new labs in AI, a 975B-parameter MoE (41B active) with native text, image, and audio reasoning in one model, a dialable 'thinking effort' knob (0.2-0.99) that lets you trade speed for depth of reasoning per-request, and fully open weights (Apache 2.0) at frontier scale - unusual for a model this large and this new.
Its trade-offs: a brand-new lab's first release - no multi-generation track record yet, no official hosted API price - available via third-party hosts only at launch, and independent third-party benchmark verification is still limited given how recently it shipped. 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 Inkling (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 Inkling 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 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 Inkling leans toward the first model release from mira murati's thinking machines lab (ex-openai cto) - one of the most closely-watched new labs in ai, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Command A+ or Inkling?
They are priced almost identically, so cost will not decide between them.
Which has the bigger context window?
Inkling — 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 Inkling together?
Yes — a multi-model platform like LumiChats gives you Command A+, Inkling 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 Inkling?
Inkling — released July 15, 2026, about 57 days after Command A+.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.