Nanbeige4.3-33B vs Step 3.7 Flash
Nanbeige LLM Lab (BOSS Zhipin) · China | StepFun · China · 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 Step 3.7 Flash for a 198b-parameter sparse moe vision-language model (11b active) built specifically for agentic coding and search workflows or scmp reported it 'outshines larger rivals' from deepseek and moonshot on some benchmarks despite its smaller active size. On a tight budget at scale, Nanbeige4.3-33B is the value pick.
Nanbeige4.3-33B (Nanbeige LLM Lab (BOSS Zhipin)) and Step 3.7 Flash (StepFun) are two of the models people most often weigh against each other in 2026. 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. Step 3.7 Flash is stepFun's 198B MoE vision-language model built for coding and search agents - a distinct Chinese lab with genuinely competitive open weights. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences at a glance
- ▸Context window: Nanbeige4.3-33B holds 2× more — 512K tokens (~786 pages) vs 256K (~393 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.
Side-by-side specs
| Spec | Nanbeige4.3-33B | Step 3.7 Flash |
|---|---|---|
| Provider | Nanbeige LLM Lab (BOSS Zhipin) (China) | StepFun (China) |
| Released | October 25, 2026 | May 29, 2026 |
| Context window | 512K tokens (~786 pages) | 256K (~393 pages) |
| Price (in/out) | Open weight (self-host / free) | $0.2/$1.15 per 1M tokens |
| Open weight? | Yes — self-hostable | Yes — self-hostable |
| Modalities | text, code | text, image, 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 2× more than Step 3.7 Flash's 256K 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
Step 3.7 Flash is comparatively weak here — benchmark 'outshines rivals' claims are from press coverage of specific tests, not a full independent leaderboard sweep
A 198B-parameter sparse MoE vision-language model (11B active) built specifically for agentic coding and search workflows
Step 3.7 Flash
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
SCMP reported it 'outshines larger rivals' from DeepSeek and Moonshot on some benchmarks despite its smaller active size
Step 3.7 Flash
Step 3.7 Flash lists sCMP reported it 'outshines larger rivals' from DeepSeek and Moonshot on some benchmarks despite its smaller active size among its strengths; Nanbeige4.3-33B does not.
Open weights (Apache 2.0) at a low per-token price
Step 3.7 Flash
Nanbeige4.3-33B is comparatively weak here — no public first-party API or per-token price; Artificial Analysis lists no publicly available API
Lowest cost at scale
Nanbeige4.3-33B
Its weights are open, so at volume you pay for your own hardware instead of Step 3.7 Flash's $0.2/$1.15 per 1M tokens.
Largest single-prompt input
Nanbeige4.3-33B
Its 512K tokens window is about 2× larger than Step 3.7 Flash's 256K, fitting roughly 786 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 Step 3.7 Flash, and on millions of tokens that margin decides the monthly bill.
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 a 198b-parameter sparse moe vision-language model (11b active) built specifically for agentic coding and search workflows
→ Step 3.7 Flash
That is its strongest area.
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.
Step 3.7 Flash: where it fits
StepFun's 198B MoE vision-language model built for coding and search agents - a distinct Chinese lab with genuinely competitive open weights. Released May 29, 2026 by StepFun, it is built for a 198B-parameter sparse MoE vision-language model (11B active) built specifically for agentic coding and search workflows, sCMP reported it 'outshines larger rivals' from DeepSeek and Moonshot on some benchmarks despite its smaller active size, open weights (Apache 2.0) at a low per-token price, and includes a 1.8B vision encoder for image understanding alongside text.
Its trade-offs: stepFun is a newer, less established lab than DeepSeek, Alibaba, or Moonshot, benchmark 'outshines rivals' claims are from press coverage of specific tests, not a full independent leaderboard sweep, and smaller ecosystem and less third-party documentation than the more established Chinese labs. At $0.2 in / $1.15 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
Nanbeige4.3-33B and Step 3.7 Flash overlap enough that the right pick depends on your specific job. Nanbeige4.3-33B costs less per token; Nanbeige4.3-33B holds the larger context; and each leads in its own area — Nanbeige4.3-33B for 33b dense open-weight model under apache 2.0 with a 524,288-token context, Step 3.7 Flash for a 198b-parameter sparse moe vision-language model (11b active) built specifically for agentic coding and search workflows. Rather than crowning one, run the same hard task through both once and let the results decide.
Want both Nanbeige4.3-33B and Step 3.7 Flash 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 Step 3.7 Flash 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 Step 3.7 Flash leans toward a 198b-parameter sparse moe vision-language model (11b active) built specifically for agentic coding and search workflows, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Nanbeige4.3-33B or Step 3.7 Flash?
Nanbeige4.3-33B is cheaper — Open weight (self-host / free) vs $0.2/$1.15 per 1M tokens.
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 Step 3.7 Flash together?
Yes — a multi-model platform like LumiChats gives you Nanbeige4.3-33B, Step 3.7 Flash 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 Step 3.7 Flash?
Nanbeige4.3-33B — released October 25, 2026, about 5 months after Step 3.7 Flash.
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.