Command A+ vs Nanbeige4.3-33B

Cohere · Canada  |  Nanbeige LLM Lab (BOSS Zhipin) · 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 Nanbeige4.3-33B for 33b dense open-weight model under apache 2.0 with a 524,288-token context or artificial analysis intelligence index of 20, first of the 8 models in its comparison class.

Command A+ (Cohere, Canada) and Nanbeige4.3-33B (Nanbeige LLM Lab (BOSS Zhipin), 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. Nanbeige4.3-33B is nanbeige LLM Lab's October 25, 2026 Apache 2.0 open model - 33B parameters and 512K context, aimed at agentic coding on modest 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

Side-by-side specs

SpecCommand A+Nanbeige4.3-33B
ProviderCohere (Canada) Nanbeige LLM Lab (BOSS Zhipin) (China)
ReleasedMay 19, 2026 October 25, 2026
Context window256K (unconfirmed) (~384 pages) 512K tokens (~786 pages)
Price (in/out)Open weight (self-host / free) Open weight (self-host / free)
Open weight?Yes — self-hostable Yes — self-hostable
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+

Nanbeige4.3-33B is comparatively weak here — coding benchmarks are self-reported, with non-standard settings noted on the model card and no independent reproduction

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; Nanbeige4.3-33B does not.

Supports 48 languages, including all official EU languages

Command A+

Command A+ lists supports 48 languages, including all official EU languages among its strengths; Nanbeige4.3-33B does not.

33B dense open-weight model under Apache 2.0 with a 524,288-token context

Nanbeige4.3-33B

Its 512K tokens window holds about 2× more than Command A+'s 256K (unconfirmed) in a single prompt.

Artificial Analysis Intelligence Index of 20, first of the 8 models in its comparison class

Nanbeige4.3-33B

Nanbeige LLM Lab's October 25, 2026 Apache 2.0 open model - 33B parameters and 512K context, aimed at agentic coding on modest hardware — and it carries the larger 512K tokens context.

Lab-reported Terminal-Bench 2.1 of 80.9 and DeepSWE of 65.5

Nanbeige4.3-33B

Command A+ is comparatively weak here — newer release with less independent benchmark verification than established flagships

Largest single-prompt input

Nanbeige4.3-33B

Its 512K tokens window is about 2× larger than Command A+'s 256K (unconfirmed), fitting roughly 786 pages in one prompt.

Which should you pick?

Someone analysing very long documents or codebases

→ Nanbeige4.3-33B

Larger 512K tokens 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 33b dense open-weight model under apache 2.0 with a 524,288-token context

→ Nanbeige4.3-33B

That is its strongest area.

An enterprise with regional data-residency rules

→ Nanbeige4.3-33B 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.

Nanbeige4.3-33B: where it fits

Nanbeige LLM Lab's October 25, 2026 Apache 2.0 open model - 33B parameters and 512K context, aimed at agentic coding on modest hardware. Released October 25, 2026 by Nanbeige LLM Lab (BOSS Zhipin), it is built for 33B dense open-weight model under Apache 2.0 with a 524,288-token context, artificial Analysis Intelligence Index of 20, first of the 8 models in its comparison class, and lab-reported Terminal-Bench 2.1 of 80.9 and DeepSWE of 65.5.

Its trade-offs: coding benchmarks are self-reported, with non-standard settings noted on the model card and no independent reproduction, no public first-party API or per-token price; Artificial Analysis lists no publicly available API, and text-only input. 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 Nanbeige4.3-33B (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 Nanbeige4.3-33B 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 Nanbeige4.3-33B 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 Nanbeige4.3-33B leans toward 33b dense open-weight model under apache 2.0 with a 524,288-token context, and that positioning usually predicts which feels better on your codebase.

Which is cheaper, Command A+ or Nanbeige4.3-33B?

They are priced almost identically, so cost will not decide between them.

Which has the bigger context window?

Nanbeige4.3-33B — 512K tokens vs 256K (unconfirmed), about 2× larger. Useful only if the model actually reasons over the full window, which not all do.

Can I use both Command A+ and Nanbeige4.3-33B together?

Yes — a multi-model platform like LumiChats gives you Command A+, Nanbeige4.3-33B 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 Nanbeige4.3-33B?

Nanbeige4.3-33B — released October 25, 2026, about 5 months 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.