GLM 5.2 vs Step 5 Preview

Z.ai · China  |  StepFun · China · Updated June 2026

Quick verdict

Pick GLM 5.2 for long-horizon agentic coding or project-level software engineering. Pick Step 5 Preview for sparse moe architecture — 600b total parameters, only 27b active per token — built for long-horizon agentic work across large codebases and documents or 1m-token context window (64k max output) at $1/$2.70 per million tokens, among the cheapest frontier-scale context windows available. Choose GLM 5.2 if you need self-hosting or data privacy; Step 5 Preview if you want a managed API.

GLM 5.2 (Z.ai) and Step 5 Preview (StepFun) are two of the models people most often weigh against each other in 2026. GLM 5.2 is an open-weight reasoning model built for long-horizon coding and multi-step agent workflows — strong and cheap. Step 5 Preview is stepFun's September 20, 2026 flagship preview — a 600B-parameter sparse MoE model (27B active) with a 1M-token context window at $1/$2.70 per million tokens, open weights promised for mid-October. They diverge most on price and open vs. closed weights — each quantified below from the models' real specs.

Key differences at a glance

Side-by-side specs

SpecGLM 5.2Step 5 Preview
ProviderZ.ai (China) StepFun (China)
ReleasedJune 16, 2026 September 20, 2026
Context window1M (~1,500 pages) 1M tokens (~1,500 pages)
Price (in/out)$1.4/$4.4 per 1M tokens $1/$2.7 per 1M tokens
Open weight?Yes — self-hostable No — API only
Modalitiestext, code text, image, code
SWE-Bench VerifiedNot published Not published
MRCR v2 @ 1MNot published Not published

Who wins what

Long-horizon agentic coding

GLM 5.2

Step 5 Preview is comparatively weak here — trails closed frontier models on coding — 67.7% on DeepSWE v1.1 vs GPT-6 Astra's 74.1% and Claude Opus 5's 74.0%

Project-level software engineering

GLM 5.2

An open-weight reasoning model built for long-horizon coding and multi-step agent workflows — strong and cheap — and its weights are open while Step 5 Preview is API-only.

Tool use across long-running tasks

GLM 5.2

GLM 5.2 lists tool use across long-running tasks among its strengths; Step 5 Preview does not.

Sparse MoE architecture — 600B total parameters, only 27B active per token — built for long-horizon agentic work across large codebases and documents

Step 5 Preview

StepFun's September 20, 2026 flagship preview — a 600B-parameter sparse MoE model (27B active) with a 1M-token context window at $1/$2.70 per million tokens, open weights promised for mid-October — and it runs cheaper at $1/$2.7 per 1M tokens.

1M-token context window (64K max output) at $1/$2.70 per million tokens, among the cheapest frontier-scale context windows available

Step 5 Preview

At $1/$2.7 per 1M tokens it undercuts GLM 5.2 ($1.4/$4.4 per 1M tokens), and that gap compounds at volume.

67.7% on DeepSWE v1.1, ahead of open-weight rivals Kimi K3 (67.5%) and GLM-5.3 (66.9%)

Step 5 Preview

StepFun's September 20, 2026 flagship preview — a 600B-parameter sparse MoE model (27B active) with a 1M-token context window at $1/$2.70 per million tokens, open weights promised for mid-October — and it is the newer of the two.

Lowest cost at scale

Step 5 Preview

At $1/$2.7 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.

Which should you pick?

A cost-sensitive startup shipping high volume

→ Step 5 Preview

At $1/$2.7 per 1M tokens it undercuts GLM 5.2, and on millions of tokens that margin decides the monthly bill.

A team with data-privacy or self-hosting needs

→ GLM 5.2

Open weights let you run it on your own hardware; Step 5 Preview is API-only.

Anyone whose priority is long-horizon agentic coding

→ GLM 5.2

It is specifically built for that.

Anyone whose priority is sparse moe architecture — 600b total parameters, only 27b active per token — built for long-horizon agentic work across large codebases and documents

→ Step 5 Preview

That is its strongest area.

GLM 5.2: where it fits

An open-weight reasoning model built for long-horizon coding and multi-step agent workflows — strong and cheap. Released June 16, 2026 by Z.ai, it is built for long-horizon agentic coding, project-level software engineering, tool use across long-running tasks, and tops the open-weight intelligence index (SWE-bench Pro 62.1).

Its trade-offs are real: text-only — no native multimodal input, and new release with a limited third-party track record. At $1.4 in / $4.4 out per million tokens, it sits in the mid price band.

Step 5 Preview: where it fits

StepFun's September 20, 2026 flagship preview — a 600B-parameter sparse MoE model (27B active) with a 1M-token context window at $1/$2.70 per million tokens, open weights promised for mid-October. Released September 20, 2026 by StepFun, it is built for sparse MoE architecture — 600B total parameters, only 27B active per token — built for long-horizon agentic work across large codebases and documents, 1M-token context window (64K max output) at $1/$2.70 per million tokens, among the cheapest frontier-scale context windows available, 67.7% on DeepSWE v1.1, ahead of open-weight rivals Kimi K3 (67.5%) and GLM-5.3 (66.9%), and scores 44 on the Artificial Analysis Intelligence Index, ranking 27th of 653 models tracked.

Its trade-offs: trails closed frontier models on coding — 67.7% on DeepSWE v1.1 vs GPT-6 Astra's 74.1% and Claude Opus 5's 74.0%, open weights were promised for October 15, 2026 but hadn't shipped as of this writing — API-only for now despite the open-weight roadmap, a 'Preview' release, not StepFun's finished flagship — positioning and pricing may change once weights ship, and stepCodeBench and DeepSWE figures are StepFun's own reported numbers, not yet independently reproduced at scale. At $1 in / $2.7 out per million tokens, it sits in the budget price band.

The bottom line for this matchup

The defining split here is open vs. closed. GLM 5.2 gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. Step 5 Preview 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 GLM 5.2 and Step 5 Preview 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 GLM 5.2 or Step 5 Preview 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, GLM 5.2 leans toward long-horizon agentic coding while Step 5 Preview leans toward sparse moe architecture — 600b total parameters, only 27b active per token — built for long-horizon agentic work across large codebases and documents, and that positioning usually predicts which feels better on your codebase.

Which is cheaper, GLM 5.2 or Step 5 Preview?

GLM 5.2 is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Step 5 Preview is API-metered at $1/$2.7 per 1M tokens. 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?

Both advertise 1M (~1,500 pages). Remember advertised ≠ usable: recall typically degrades before the ceiling.

Can I use both GLM 5.2 and Step 5 Preview together?

Yes — a multi-model platform like LumiChats gives you GLM 5.2, Step 5 Preview 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, GLM 5.2 or Step 5 Preview?

Step 5 Preview — released September 20, 2026, about 3 months after GLM 5.2.

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.