Atria Dawn Preview vs Step 5 Preview

Shanghai AI Laboratory · China  |  StepFun · China · Updated June 2026

Quick verdict

Pick Atria Dawn Preview for best-in-class among tested models on several of shanghai ai lab's own benchmarks, including browsecomp (92.5, ahead of gpt-5.6 sol's 92.2) and deepsearchqa (96.0) or 744b-parameter moe built on a glm-5.2 base, released under a fully open mit license. 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 Atria Dawn Preview if you need self-hosting or data privacy; Step 5 Preview if you want a managed API.

Atria Dawn Preview (Shanghai AI Laboratory) and Step 5 Preview (StepFun) are two of the models people most often weigh against each other in 2026. Atria Dawn Preview is a free, MIT-licensed 744B open-weight model from Shanghai AI Lab that beat GPT-5.6 Sol on the BrowseComp benchmark — released quietly, weights before paper. 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, context window and open vs. closed weights — each quantified below from the models' real specs.

Key differences at a glance

Side-by-side specs

SpecAtria Dawn PreviewStep 5 Preview
ProviderShanghai AI Laboratory (China) StepFun (China)
ReleasedSeptember 11, 2026 September 20, 2026
Context window256K tokens (~393 pages) 1M tokens (~1,500 pages)
Price (in/out)Open weight (self-host / free) $1/$2.7 per 1M tokens
Open weight?Yes — self-hostable No — API only
Modalitiestext text, image, code
SWE-Bench VerifiedNot published Not published
MRCR v2 @ 1MNot published Not published

Who wins what

Best-in-class among tested models on several of Shanghai AI Lab's own benchmarks, including BrowseComp (92.5, ahead of GPT-5.6 Sol's 92.2) and DeepSearchQA (96.0)

Atria Dawn Preview

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%

744B-parameter MoE built on a GLM-5.2 base, released under a fully open MIT license

Atria Dawn Preview

Open weights make this possible at all — Step 5 Preview is API-only, so it cannot leave the vendor's servers.

Free to self-host — no API pricing, run entirely on your own hardware

Atria Dawn Preview

Step 5 Preview is comparatively weak here — a 'Preview' release, not StepFun's finished flagship — positioning and pricing may change once weights ship

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

Its 1M tokens window holds about 3.8× more than Atria Dawn Preview's 256K tokens in a single prompt.

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

Atria Dawn Preview is comparatively weak here — context window is reported inconsistently across trackers — most list 256K tokens, at least one lists 1M; unconfirmed which is accurate

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

Step 5 Preview

Atria Dawn Preview is comparatively weak here — released quietly, with weights and an API posted to GitHub before Shanghai AI Lab's own technical report went up on arXiv days later

Lowest cost at scale

Atria Dawn Preview

Its weights are open, so at volume you pay for your own hardware instead of Step 5 Preview's $1/$2.7 per 1M tokens.

Largest single-prompt input

Step 5 Preview

Its 1M tokens window is about 3.8× larger than Atria Dawn Preview's 256K tokens, fitting roughly 1,500 pages in one prompt.

Which should you pick?

A cost-sensitive startup shipping high volume

→ Atria Dawn Preview

At Open weight (self-host / free) it undercuts Step 5 Preview, and on millions of tokens that margin decides the monthly bill.

Someone analysing very long documents or codebases

→ Step 5 Preview

Larger 1M tokens window fits more in one prompt.

A team with data-privacy or self-hosting needs

→ Atria Dawn Preview

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

Anyone whose priority is best-in-class among tested models on several of shanghai ai lab's own benchmarks, including browsecomp (92.5, ahead of gpt-5.6 sol's 92.2) and deepsearchqa (96.0)

→ Atria Dawn Preview

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.

Atria Dawn Preview: where it fits

A free, MIT-licensed 744B open-weight model from Shanghai AI Lab that beat GPT-5.6 Sol on the BrowseComp benchmark — released quietly, weights before paper. Released September 11, 2026 by Shanghai AI Laboratory, it is built for best-in-class among tested models on several of Shanghai AI Lab's own benchmarks, including BrowseComp (92.5, ahead of GPT-5.6 Sol's 92.2) and DeepSearchQA (96.0), 744B-parameter MoE built on a GLM-5.2 base, released under a fully open MIT license, and free to self-host — no API pricing, run entirely on your own hardware.

Its trade-offs are real: context window is reported inconsistently across trackers — most list 256K tokens, at least one lists 1M; unconfirmed which is accurate, released quietly, with weights and an API posted to GitHub before Shanghai AI Lab's own technical report went up on arXiv days later, and a lab research preview rather than a commercial product — support and update cadence are unclear. As an open-weight model, its running cost is your own hardware rather than a per-token fee.

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. Atria Dawn Preview 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 Atria Dawn Preview 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 Atria Dawn Preview 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, Atria Dawn Preview leans toward best-in-class among tested models on several of shanghai ai lab's own benchmarks, including browsecomp (92.5, ahead of gpt-5.6 sol's 92.2) and deepsearchqa (96.0) 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, Atria Dawn Preview or Step 5 Preview?

Atria Dawn Preview 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?

Step 5 Preview — 1M tokens vs 256K tokens, about 3.8× larger. Useful only if the model actually reasons over the full window, which not all do.

Can I use both Atria Dawn Preview and Step 5 Preview together?

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

Step 5 Preview — released September 20, 2026, about 9 days after Atria Dawn 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.