Nanbeige4.3-33B vs NVIDIA Nemotron 3 Ultra

Nanbeige LLM Lab (BOSS Zhipin) · China  |  NVIDIA · US · Updated June 2026

Quick verdict

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. Pick NVIDIA Nemotron 3 Ultra for the most capable open-weight model from a us lab (artificial analysis intelligence index of about 48) or fast, efficient long-horizon agentic reasoning via a hybrid mamba-transformer design.

Nanbeige4.3-33B (Nanbeige LLM Lab (BOSS Zhipin), China) and NVIDIA Nemotron 3 Ultra (NVIDIA, US) line up two different AI ecosystems against each other — a comparison that is as much about cost philosophy and openness as raw capability. 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. NVIDIA Nemotron 3 Ultra is nVIDIA's open-weight reasoning flagship (about 550B total, 55B active) — the most capable open model from a US lab, built for long-running agents. 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

SpecNanbeige4.3-33BNVIDIA Nemotron 3 Ultra
ProviderNanbeige LLM Lab (BOSS Zhipin) (China) NVIDIA (US)
ReleasedOctober 25, 2026 June 4, 2026
Context window512K tokens (~786 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
Modalitiestext, code text, code
SWE-Bench VerifiedNot published Not published
MRCR v2 @ 1MNot published Not published

Who wins what

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

Nanbeige4.3-33B

NVIDIA Nemotron 3 Ultra is comparatively weak here — trails the best Chinese open models on overall intelligence

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 is the newer of the two.

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

Nanbeige4.3-33B

Nanbeige4.3-33B lists lab-reported Terminal-Bench 2.1 of 80.9 and DeepSWE of 65.5 among its strengths; NVIDIA Nemotron 3 Ultra does not.

The most capable open-weight model from a US lab (Artificial Analysis Intelligence Index of about 48)

NVIDIA Nemotron 3 Ultra

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

Fast, efficient long-horizon agentic reasoning via a hybrid Mamba-Transformer design

NVIDIA Nemotron 3 Ultra

Its 1M window holds about 1.9× more than Nanbeige4.3-33B's 512K tokens in a single prompt.

A fully open release — weights, training data, and recipes under a permissive license

NVIDIA Nemotron 3 Ultra

NVIDIA's open-weight reasoning flagship (about 550B total, 55B active) — the most capable open model from a US lab, built for long-running agents — and it carries the larger 1M context.

Largest single-prompt input

NVIDIA Nemotron 3 Ultra

Its 1M window is about 1.9× larger than Nanbeige4.3-33B's 512K tokens, fitting roughly 1,500 pages in one prompt.

Which should you pick?

Someone analysing very long documents or codebases

→ NVIDIA Nemotron 3 Ultra

Larger 1M window fits more in one prompt.

Anyone whose priority is 33b dense open-weight model under apache 2.0 with a 524,288-token context

→ Nanbeige4.3-33B

It is specifically built for that.

Anyone whose priority is the most capable open-weight model from a us lab (artificial analysis intelligence index of about 48)

→ NVIDIA Nemotron 3 Ultra

That is its strongest area.

An enterprise with regional data-residency rules

→ NVIDIA Nemotron 3 Ultra or Nanbeige4.3-33B

Origin (China vs US) affects where data is processed and which compliance regime applies — check the provider's terms for your region.

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 are real: 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.

NVIDIA Nemotron 3 Ultra: where it fits

NVIDIA's open-weight reasoning flagship (about 550B total, 55B active) — the most capable open model from a US lab, built for long-running agents. Released June 4, 2026 by NVIDIA, it is built for the most capable open-weight model from a US lab (Artificial Analysis Intelligence Index of about 48), fast, efficient long-horizon agentic reasoning via a hybrid Mamba-Transformer design, a fully open release — weights, training data, and recipes under a permissive license, and strong coding for an open model (SWE-Bench Verified in the high 60s).

Its trade-offs: trails the best Chinese open models on overall intelligence, and a 550B mixture-of-experts is heavy to self-host, and the 1M context is rarely served in full. 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." Nanbeige4.3-33B (China) and NVIDIA Nemotron 3 Ultra (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 Nanbeige4.3-33B and NVIDIA Nemotron 3 Ultra 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 Nanbeige4.3-33B or NVIDIA Nemotron 3 Ultra 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, Nanbeige4.3-33B leans toward 33b dense open-weight model under apache 2.0 with a 524,288-token context while NVIDIA Nemotron 3 Ultra leans toward the most capable open-weight model from a us lab (artificial analysis intelligence index of about 48), and that positioning usually predicts which feels better on your codebase.

Which is cheaper, Nanbeige4.3-33B or NVIDIA Nemotron 3 Ultra?

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

Which has the bigger context window?

NVIDIA Nemotron 3 Ultra — 1M vs 512K tokens, about 1.9× larger. Useful only if the model actually reasons over the full window, which not all do.

Can I use both Nanbeige4.3-33B and NVIDIA Nemotron 3 Ultra together?

Yes — a multi-model platform like LumiChats gives you Nanbeige4.3-33B, NVIDIA Nemotron 3 Ultra 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, Nanbeige4.3-33B or NVIDIA Nemotron 3 Ultra?

Nanbeige4.3-33B — released October 25, 2026, about 5 months after NVIDIA Nemotron 3 Ultra.

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.