Nanbeige4.3-33B vs Palmyra X6
Nanbeige LLM Lab (BOSS Zhipin) · China | Writer · 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 Palmyra X6 for enterprise agentic workflows - built specifically for marketing/revenue teams running multi-step agents or writer says its harness upgrades cut agent-workflow token costs by roughly 52% and improve speed by roughly 48% (writer's own figures). Choose Nanbeige4.3-33B if you need self-hosting or data privacy; Palmyra X6 if you want a managed API.
Nanbeige4.3-33B (Nanbeige LLM Lab (BOSS Zhipin), China) and Palmyra X6 (Writer, 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. Palmyra X6 is writer's enterprise agentic flagship - a GLM-5.2-based model with harness upgrades Writer says cut agent token costs by roughly half. They diverge most on context window and open vs. closed weights — each quantified below from the models' real specs.
Key differences at a glance
- ▸Cost model: Nanbeige4.3-33B ships open weights you can self-host (hardware cost only, no per-token fee), while Palmyra X6 is API-metered at Not published. Your choice depends on whether you want zero marginal cost at the price of running infrastructure.
- ▸Context window: Nanbeige4.3-33B holds 4.1× more — 512K tokens (~786 pages) vs 128K (~192 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 2 months (released October 25, 2026), usually meaning fresher training data and capabilities.
- ▸Ecosystem: this is a China-vs-US matchup — they differ in pricing philosophy, data-residency options, and tooling ecosystems, not only benchmarks.
Side-by-side specs
| Spec | Nanbeige4.3-33B | Palmyra X6 |
|---|---|---|
| Provider | Nanbeige LLM Lab (BOSS Zhipin) (China) | Writer (US) |
| Released | October 25, 2026 | August 13, 2026 |
| Context window | 512K tokens (~786 pages) | 128K (~192 pages) |
| Price (in/out) | Open weight (self-host / free) | Not published |
| Open weight? | Yes — self-hostable | No — API only |
| Modalities | text, code | text, code |
| SWE-Bench Verified | Not published | Not published |
| 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 4.1× more than Palmyra X6's 128K in a single prompt.
Artificial Analysis Intelligence Index of 20, first of the 8 models in its comparison class
Nanbeige4.3-33B
Palmyra X6 is comparatively weak here — not independently benchmarked on general leaderboards like SWE-bench or Artificial Analysis
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.
Enterprise agentic workflows - built specifically for marketing/revenue teams running multi-step agents
Palmyra X6
Palmyra X6 lists enterprise agentic workflows - built specifically for marketing/revenue teams running multi-step agents among its strengths; Nanbeige4.3-33B does not.
Writer says its harness upgrades cut agent-workflow token costs by roughly 52% and improve speed by roughly 48% (Writer's own figures)
Palmyra X6
Nanbeige4.3-33B is comparatively weak here — no public first-party API or per-token price; Artificial Analysis lists no publicly available API
A post-trained variant built on Z.ai's open-weight GLM-5.2, tuned specifically for business agent use
Palmyra X6
Palmyra X6 lists a post-trained variant built on Z.ai's open-weight GLM-5.2, tuned specifically for business agent use among its strengths; Nanbeige4.3-33B does not.
Largest single-prompt input
Nanbeige4.3-33B
Its 512K tokens window is about 4.1× larger than Palmyra X6's 128K, 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.
A team with data-privacy or self-hosting needs
→ Nanbeige4.3-33B
Open weights let you run it on your own hardware; Palmyra X6 is API-only.
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 enterprise agentic workflows - built specifically for marketing/revenue teams running multi-step agents
→ Palmyra X6
That is its strongest area.
An enterprise with regional data-residency rules
→ Palmyra X6 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.
Palmyra X6: where it fits
Writer's enterprise agentic flagship - a GLM-5.2-based model with harness upgrades Writer says cut agent token costs by roughly half. Released August 13, 2026 by Writer, it is built for enterprise agentic workflows - built specifically for marketing/revenue teams running multi-step agents, writer says its harness upgrades cut agent-workflow token costs by roughly 52% and improve speed by roughly 48% (Writer's own figures), and a post-trained variant built on Z.ai's open-weight GLM-5.2, tuned specifically for business agent use.
Its trade-offs: no public per-token API price - sold through Writer's enterprise platform, not a self-serve API, not independently benchmarked on general leaderboards like SWE-bench or Artificial Analysis, and built for a narrower enterprise-agent use case rather than general-purpose chat.
The bottom line for this matchup
The defining split here is open vs. closed. Nanbeige4.3-33B gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. Palmyra X6 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 Nanbeige4.3-33B and Palmyra X6 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 Palmyra X6 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 Palmyra X6 leans toward enterprise agentic workflows - built specifically for marketing/revenue teams running multi-step agents, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Nanbeige4.3-33B or Palmyra X6?
Nanbeige4.3-33B is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Palmyra X6 is API-metered at Not published. 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?
Nanbeige4.3-33B — 512K tokens vs 128K, about 4.1× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Nanbeige4.3-33B and Palmyra X6 together?
Yes — a multi-model platform like LumiChats gives you Nanbeige4.3-33B, Palmyra X6 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 Palmyra X6?
Nanbeige4.3-33B — released October 25, 2026, about 2 months after Palmyra X6.
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.