Command A+ vs Qwen 3.7 Max

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 Qwen 3.7 Max for long-horizon agentic coding (swe-bench pro 60.6, terminal-bench 2.0 69.7) or 1m-token long-document and full-codebase analysis. Choose Command A+ if you need self-hosting or data privacy; Qwen 3.7 Max if you want a managed API.

Command A+ (Cohere, Canada) and Qwen 3.7 Max (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. Qwen 3.7 Max is alibaba's agent-first frontier model — a 1M-token context and long-horizon coding at about half the cost of US flagships. They diverge most on price, context window and open vs. closed weights — each quantified below from the models' real specs.

Key differences at a glance

Side-by-side specs

SpecCommand A+Qwen 3.7 Max
ProviderCohere (Canada) Alibaba (China)
ReleasedMay 19, 2026 May 20, 2026
Context window256K (unconfirmed) (~384 pages) 1M (~1,500 pages)
Price (in/out)Open weight (self-host / free) $2.5/$7.5 per 1M tokens
Open weight?Yes — self-hostable No — API only
Modalitiestext, code text, code
SWE-Bench VerifiedNot published Not published
MRCR v2 @ 1MNot 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+

Cohere's newer, leaner flagship - a 218B open-weight MoE tuned for efficiency (just two GPUs to run) and 48-language support — and its weights are open while Qwen 3.7 Max is API-only.

A 218B-total/25B-active MoE released with open weights (Apache 2.0) on Hugging Face

Command A+

Open weights make this possible at all — Qwen 3.7 Max is API-only, so it cannot leave the vendor's servers.

Supports 48 languages, including all official EU languages

Command A+

Command A+ lists supports 48 languages, including all official EU languages among its strengths; Qwen 3.7 Max does not.

Long-horizon agentic coding (SWE-Bench Pro 60.6, Terminal-Bench 2.0 69.7)

Qwen 3.7 Max

Its 1M window holds about 3.9× more than Command A+'s 256K (unconfirmed) in a single prompt.

1M-token long-document and full-codebase analysis

Qwen 3.7 Max

Command A+ is comparatively weak here — no official context window or per-token price published yet - both are estimated/unavailable

MCP tool orchestration and multi-hour autonomous runs

Qwen 3.7 Max

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 Qwen 3.7 Max's $2.5/$7.5 per 1M tokens.

Largest single-prompt input

Qwen 3.7 Max

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?

A cost-sensitive startup shipping high volume

Command A+

At Open weight (self-host / free) it undercuts Qwen 3.7 Max, and on millions of tokens that margin decides the monthly bill.

Someone analysing very long documents or codebases

Qwen 3.7 Max

Larger 1M window fits more in one prompt.

A team with data-privacy or self-hosting needs

Command A+

Open weights let you run it on your own hardware; Qwen 3.7 Max is API-only.

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-horizon agentic coding (swe-bench pro 60.6, terminal-bench 2.0 69.7)

Qwen 3.7 Max

That is its strongest area.

An enterprise with regional data-residency rules

Qwen 3.7 Max 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.

Qwen 3.7 Max: where it fits

Alibaba's agent-first frontier model — a 1M-token context and long-horizon coding at about half the cost of US flagships. Released May 20, 2026 by Alibaba, it is built for long-horizon agentic coding (SWE-Bench Pro 60.6, Terminal-Bench 2.0 69.7), 1M-token long-document and full-codebase analysis, mCP tool orchestration and multi-hour autonomous runs, and frontier intelligence at roughly half the price of US flagships.

Its trade-offs: text-only — no vision input (the Plus variant adds images), closed-weight, API-only — no self-hosting, trails GPT-5.5 and Claude Opus on the hardest one-shot reasoning, and chinese-jurisdiction data-residency considerations. At $2.5 in / $7.5 out per million tokens, it sits in the mid price band.

The bottom line for this matchup

The defining split here is open vs. closed. Command A+ gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. Qwen 3.7 Max gives you a managed, always-updated API with no infrastructure to run. Teams with GPUs, privacy requirements, or huge volume often favour the open model; teams that want zero ops and the latest capabilities favour the closed one. Capability is close enough that this operational question, not the benchmark, usually decides it.

Want both Command A+ and Qwen 3.7 Max 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.

See pricing

Frequently asked questions

Is Command A+ or Qwen 3.7 Max 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 Qwen 3.7 Max leans toward long-horizon agentic coding (swe-bench pro 60.6, terminal-bench 2.0 69.7), and that positioning usually predicts which feels better on your codebase.

Which is cheaper, Command A+ or Qwen 3.7 Max?

Command A+ is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Qwen 3.7 Max is API-metered at $2.5/$7.5 per 1M tokens. For most teams without GPUs, the API model is cheaper to start; at very high volume, self-hosting can win.

Which has the bigger context window?

Qwen 3.7 Max — 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 Qwen 3.7 Max together?

Yes — a multi-model platform like LumiChats gives you Command A+, Qwen 3.7 Max 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 Qwen 3.7 Max?

Qwen 3.7 Max — released May 20, 2026, about 1 days after Command A+.

Related comparisons

Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.