Hunyuan Hy4 Preview vs Nanbeige4.3-33B
Tencent · China | Nanbeige LLM Lab (BOSS Zhipin) · China · Updated June 2026
Quick verdict
Pick Hunyuan Hy4 Preview for gpqa diamond (92.3) or terminal-bench (85.4). 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. On a tight budget at scale, Nanbeige4.3-33B is the value pick.
Hunyuan Hy4 Preview (Tencent) and Nanbeige4.3-33B (Nanbeige LLM Lab (BOSS Zhipin)) are two of the models people most often weigh against each other in 2026. Hunyuan Hy4 Preview is tencent's open-sourced (Apache 2.0) next-generation Hunyuan flagship preview, released August 28, 2026 as a 770B-parameter (49B active) MoE model that helped optimize its own training pipeline. 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. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences at a glance
- ▸Context window: Hunyuan Hy4 Preview holds 1.9× more — 1M+ tokens (~1,500 pages) vs 512K tokens (~786 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 58 days (released October 25, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
| Spec | Hunyuan Hy4 Preview | Nanbeige4.3-33B |
|---|---|---|
| Provider | Tencent (China) | Nanbeige LLM Lab (BOSS Zhipin) (China) |
| Released | August 28, 2026 | October 25, 2026 |
| Context window | 1M+ tokens (~1,500 pages) | 512K tokens (~786 pages) |
| Price (in/out) | $0.834/$2.501 per 1M tokens | Open weight (self-host / free) |
| Open weight? | Yes — self-hostable | Yes — self-hostable |
| Modalities | text | text, code |
| SWE-Bench Verified | Not published | Not published |
| MRCR v2 @ 1M | Not published | Not published |
Who wins what
GPQA Diamond (92.3)
Hunyuan Hy4 Preview
Tencent's open-sourced (Apache 2.0) next-generation Hunyuan flagship preview, released August 28, 2026 as a 770B-parameter (49B active) MoE model that helped optimize its own training pipeline — and it carries the larger 1M+ tokens context.
Terminal-Bench (85.4)
Hunyuan Hy4 Preview
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
SWE-bench Multilingual (82.9)
Hunyuan Hy4 Preview
Hunyuan Hy4 Preview lists sWE-bench Multilingual (82.9) 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
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.
Artificial Analysis Intelligence Index of 20, first of the 8 models in its comparison class
Nanbeige4.3-33B
Nanbeige4.3-33B lists artificial Analysis Intelligence Index of 20, first of the 8 models in its comparison class among its strengths; Hunyuan Hy4 Preview does not.
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; Hunyuan Hy4 Preview does not.
Lowest cost at scale
Nanbeige4.3-33B
Its weights are open, so at volume you pay for your own hardware instead of Hunyuan Hy4 Preview's $0.834/$2.501 per 1M tokens.
Largest single-prompt input
Hunyuan Hy4 Preview
Its 1M+ tokens 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?
A cost-sensitive startup shipping high volume
→ Nanbeige4.3-33B
At Open weight (self-host / free) it undercuts Hunyuan Hy4 Preview, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ Hunyuan Hy4 Preview
Larger 1M+ tokens window fits more in one prompt.
Anyone whose priority is gpqa diamond (92.3)
→ Hunyuan Hy4 Preview
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.
Hunyuan Hy4 Preview: where it fits
Tencent's open-sourced (Apache 2.0) next-generation Hunyuan flagship preview, released August 28, 2026 as a 770B-parameter (49B active) MoE model that helped optimize its own training pipeline. Released August 28, 2026 by Tencent, it is built for gPQA Diamond (92.3), terminal-Bench (85.4), sWE-bench Multilingual (82.9), and large jump in long-horizon coding vs prior Hunyuan model (DeepSWE 28.0 to 64.3).
Its trade-offs are real: text-only, no native vision support, labeled a 'preview', not yet Tencent's finalized GA flagship, and sWE-Marathon score still low in absolute terms (31.9) despite a large relative jump. At $0.834 in / $2.501 out per million tokens, it sits in the budget price band.
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
Hunyuan Hy4 Preview and Nanbeige4.3-33B overlap enough that the right pick depends on your specific job. Nanbeige4.3-33B costs less per token; Hunyuan Hy4 Preview holds the larger context; and each leads in its own area — Hunyuan Hy4 Preview for gpqa diamond (92.3), Nanbeige4.3-33B for 33b dense open-weight model under apache 2.0 with a 524,288-token context. Rather than crowning one, run the same hard task through both once and let the results decide.
Want both Hunyuan Hy4 Preview 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 pricingFrequently asked questions
Is Hunyuan Hy4 Preview 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, Hunyuan Hy4 Preview leans toward gpqa diamond (92.3) 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, Hunyuan Hy4 Preview or Nanbeige4.3-33B?
Nanbeige4.3-33B is cheaper — $0.834/$2.501 per 1M tokens vs Open weight (self-host / free).
Which has the bigger context window?
Hunyuan Hy4 Preview — 1M+ tokens 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 Hunyuan Hy4 Preview and Nanbeige4.3-33B together?
Yes — a multi-model platform like LumiChats gives you Hunyuan Hy4 Preview, 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, Hunyuan Hy4 Preview or Nanbeige4.3-33B?
Nanbeige4.3-33B — released October 25, 2026, about 58 days after Hunyuan Hy4 Preview.
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.