Atria Dawn Preview vs GLM 5
Shanghai AI Laboratory · China | Z.ai · 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 GLM 5 for agentic planning and long-horizon coding workflows or complex systems design and backend reasoning. On a tight budget at scale, Atria Dawn Preview is the value pick.
Atria Dawn Preview (Shanghai AI Laboratory) and GLM 5 (Z.ai) 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. GLM 5 is z.ai's flagship open-weight (MIT) MoE foundation model, engineered for complex systems design and long-horizon agentic coding. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences at a glance
- ▸Context window: Atria Dawn Preview holds 1.3× more — 256K tokens (~393 pages) vs 200K (~300 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
- ▸Recency: Atria Dawn Preview is the newer model by about 7 months (released September 11, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
| Spec | Atria Dawn Preview | GLM 5 |
|---|---|---|
| Provider | Shanghai AI Laboratory (China) | Z.ai (China) |
| Released | September 11, 2026 | February 12, 2026 |
| Context window | 256K tokens (~393 pages) | 200K (~300 pages) |
| Price (in/out) | Open weight (self-host / free) | $1/$3.2 per 1M tokens |
| Open weight? | Yes — self-hostable | Yes — self-hostable |
| Modalities | text | text, code |
| SWE-Bench Verified | Not published | 77.8% |
| MRCR v2 @ 1M | Not 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
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 — and it carries the larger 256K tokens context.
744B-parameter MoE built on a GLM-5.2 base, released under a fully open MIT license
Atria Dawn Preview
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 — and it is the newer of the two.
Free to self-host — no API pricing, run entirely on your own hardware
Atria Dawn Preview
Atria Dawn Preview lists free to self-host — no API pricing, run entirely on your own hardware among its strengths; GLM 5 does not.
Agentic planning and long-horizon coding workflows
GLM 5
GLM 5 lists agentic planning and long-horizon coding workflows among its strengths; Atria Dawn Preview does not.
Complex systems design and backend reasoning
GLM 5
GLM 5 lists complex systems design and backend reasoning among its strengths; Atria Dawn Preview does not.
Iterative self-correction on autonomous tasks
GLM 5
GLM 5 lists iterative self-correction on autonomous tasks among its strengths; Atria Dawn Preview does not.
Lowest cost at scale
Atria Dawn Preview
Its weights are open, so at volume you pay for your own hardware instead of GLM 5's $1/$3.2 per 1M tokens.
Largest single-prompt input
Atria Dawn Preview
Its 256K tokens window is about 1.3× larger than GLM 5's 200K, fitting roughly 393 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 GLM 5, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ Atria Dawn Preview
Larger 256K tokens window fits more in one prompt.
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 agentic planning and long-horizon coding workflows
→ GLM 5
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.
GLM 5: where it fits
Z.ai's flagship open-weight (MIT) MoE foundation model, engineered for complex systems design and long-horizon agentic coding. Released February 12, 2026 by Z.ai, it is built for agentic planning and long-horizon coding workflows, complex systems design and backend reasoning, iterative self-correction on autonomous tasks, and open weights under the permissive MIT license.
Its trade-offs: 200K context trails 1M-context rivals, and quickly superseded by GLM-5.1 and GLM-5.2. At $1 in / $3.2 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
Atria Dawn Preview and GLM 5 overlap enough that the right pick depends on your specific job. Atria Dawn Preview costs less per token; Atria Dawn Preview holds the larger context; and each leads in its own area — 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), GLM 5 for agentic planning and long-horizon coding workflows. Rather than crowning one, run the same hard task through both once and let the results decide.
Want both Atria Dawn Preview and GLM 5 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 Atria Dawn Preview or GLM 5 better for coding?
Public SWE-Bench figures are not available for Atria Dawn Preview, 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 GLM 5 leans toward agentic planning and long-horizon coding workflows, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Atria Dawn Preview or GLM 5?
Atria Dawn Preview is cheaper — Open weight (self-host / free) vs $1/$3.2 per 1M tokens.
Which has the bigger context window?
Atria Dawn Preview — 256K tokens vs 200K, about 1.3× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Atria Dawn Preview and GLM 5 together?
Yes — a multi-model platform like LumiChats gives you Atria Dawn Preview, GLM 5 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 GLM 5?
Atria Dawn Preview — released September 11, 2026, about 7 months after GLM 5.
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.