Nanbeige4.3-33B vs North Mini Code
Nanbeige LLM Lab (BOSS Zhipin) · China | Cohere · Canada · 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 North Mini Code for agentic software engineering, code generation, and terminal tasks or efficient sparse moe — 3b active of 30b, runs on a single h100.
Nanbeige4.3-33B (Nanbeige LLM Lab (BOSS Zhipin), China) and North Mini Code (Cohere, Canada) 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. North Mini Code is cohere's first agentic coding model: an open-weight 30B/3B-active MoE built for real software-engineering and terminal tasks that runs on a single H100. 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: Nanbeige4.3-33B holds 2× more — 512K tokens (~786 pages) vs 256K (~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: Nanbeige4.3-33B is the newer model by about 5 months (released October 25, 2026), usually meaning fresher training data and capabilities.
- ▸Ecosystem: this is a China-vs-Canada matchup — they differ in pricing philosophy, data-residency options, and tooling ecosystems, not only benchmarks.
Side-by-side specs
| Spec | Nanbeige4.3-33B | North Mini Code |
|---|---|---|
| Provider | Nanbeige LLM Lab (BOSS Zhipin) (China) | Cohere (Canada) |
| Released | October 25, 2026 | June 9, 2026 |
| Context window | 512K tokens (~786 pages) | 256K (~384 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 | 67.6% |
| MRCR v2 @ 1M | Not published | Not published |
Who wins what
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 North Mini Code's 256K in a single prompt.
Artificial Analysis Intelligence Index of 20, first of the 8 models in its comparison class
Nanbeige4.3-33B
North Mini Code is comparatively weak here — 256K context and modest general-intelligence index trail frontier models
Lab-reported Terminal-Bench 2.1 of 80.9 and DeepSWE of 65.5
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.
Agentic software engineering, code generation, and terminal tasks
North Mini Code
North Mini Code lists agentic software engineering, code generation, and terminal tasks among its strengths; Nanbeige4.3-33B does not.
Efficient sparse MoE — 3B active of 30B, runs on a single H100
North Mini Code
North Mini Code lists efficient sparse MoE — 3B active of 30B, runs on a single H100 among its strengths; Nanbeige4.3-33B does not.
High throughput (up to 2.8x Devstral Small 2) at low latency
North Mini Code
North Mini Code lists high throughput (up to 2.8x Devstral Small 2) at low latency among its strengths; Nanbeige4.3-33B does not.
Largest single-prompt input
Nanbeige4.3-33B
Its 512K tokens window is about 2× larger than North Mini Code's 256K, 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 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 agentic software engineering, code generation, and terminal tasks
→ North Mini Code
That is its strongest area.
An enterprise with regional data-residency rules
→ North Mini Code or Nanbeige4.3-33B
Origin (China vs Canada) 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.
North Mini Code: where it fits
Cohere's first agentic coding model: an open-weight 30B/3B-active MoE built for real software-engineering and terminal tasks that runs on a single H100. Released June 9, 2026 by Cohere, it is built for agentic software engineering, code generation, and terminal tasks, efficient sparse MoE — 3B active of 30B, runs on a single H100, high throughput (up to 2.8x Devstral Small 2) at low latency, and fully open weights under Apache 2.0 with fp8 and 4-bit builds.
Its trade-offs: text-only and coding-specialized — not multimodal or general-purpose, and 256K context and modest general-intelligence index trail frontier models. 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 North Mini Code (Canada) 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 North Mini Code 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 pricingFrequently asked questions
Is Nanbeige4.3-33B or North Mini Code better for coding?
Public SWE-Bench figures are not available for Nanbeige4.3-33B, 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 North Mini Code leans toward agentic software engineering, code generation, and terminal tasks, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Nanbeige4.3-33B or North Mini Code?
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, about 2× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Nanbeige4.3-33B and North Mini Code together?
Yes — a multi-model platform like LumiChats gives you Nanbeige4.3-33B, North Mini Code 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 North Mini Code?
Nanbeige4.3-33B — released October 25, 2026, about 5 months after North Mini Code.
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.