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 GPT-5.1 for adaptive reasoning that scales compute to task difficulty or general-purpose reasoning, coding and tool use. Choose Atria Dawn Preview if you need self-hosting or data privacy; GPT-5.1 if you want a managed API.
Atria Dawn Preview (Shanghai AI Laboratory, China) and GPT-5.1 (OpenAI, US) line up two different AI ecosystems against each other — a comparison that is as much about cost philosophy and openness as raw capability. 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. GPT-5.1 is openAI's late-2025 GPT-5.1 at $1.25/$10 — a capable general model since surpassed by the GPT-5.2–5.6 line. They diverge most on price, context window and open vs. closed weights — each quantified below from the models' real specs.
Key differences
Cost model: Atria Dawn Preview ships open weights you can self-host (hardware cost only, no per-token fee), while GPT-5.1 is API-metered at $1.25/$10 per 1M tokens. Your choice depends on whether you want zero marginal cost at the price of running infrastructure.
Context window: GPT-5.1 holds 1.5× more — 400K (~600 pages) vs 256K tokens (~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: Atria Dawn Preview is the newer model by about 10 months (released September 11, 2026), usually meaning fresher training data and capabilities.
Ecosystem: this is a China-vs-US matchup — they differ in pricing philosophy, data-residency options, and tooling ecosystems, not only benchmarks.
Specifications
Spec
Atria Dawn Preview
GPT-5.1
Provider
Shanghai AI Laboratory (China)
OpenAI (US)
Released
September 11, 2026
November 13, 2025
Context window
256K tokens (~393 pages)
400K (~600 pages)
Price (in/out)
Open weight (self-host / free)
$1.25/$10 per 1M tokens
Open weight?
Yes — self-hostable
No — API only
Modalities
text
text, image, code
SWE-Bench Verified
Not published
Not published
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 its weights are open while GPT-5.1 is API-only.
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 — GPT-5.1 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 — 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.
Adaptive reasoning that scales compute to task difficulty: GPT-5.1 — OpenAI's late-2025 GPT-5.1 at $1.25/$10 — a capable general model since surpassed by the GPT-5.2–5.6 line — and it carries the larger 400K context.
General-purpose reasoning, coding and tool use: GPT-5.1 — GPT-5.1 lists general-purpose reasoning, coding and tool use among its strengths; Atria Dawn Preview does not.
A large ~400K context for long documents and sessions: GPT-5.1 — Its 400K window holds about 1.5× more than Atria Dawn Preview's 256K tokens in a single prompt.
Lowest cost at scale: Atria Dawn Preview — Its weights are open, so at volume you pay for your own hardware instead of GPT-5.1's $1.25/$10 per 1M tokens.
Largest single-prompt input: GPT-5.1 — Its 400K window is about 1.5× larger than Atria Dawn Preview's 256K tokens, fitting roughly 600 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 GPT-5.1, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: GPT-5.1 — Larger 400K 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; GPT-5.1 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 adaptive reasoning that scales compute to task difficulty: GPT-5.1 — That is its strongest area.
An enterprise with regional data-residency rules: GPT-5.1 or Atria Dawn Preview — Origin (China vs US) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
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.
GPT-5.1: where it fits
OpenAI's late-2025 GPT-5.1 at $1.25/$10 — a capable general model since surpassed by the GPT-5.2–5.6 line. Released November 13, 2025 by OpenAI, it is built for adaptive reasoning that scales compute to task difficulty, general-purpose reasoning, coding and tool use, a large ~400K context for long documents and sessions, and text and image input.
Its trade-offs: superseded by GPT-5.2 through GPT-5.6 — kept for compatibility rather than being current, no reliably published SWE-Bench Verified figure, exact context window unconfirmed (400K vs 410K across trackers), and premium output price at $10/1M for a now-older model. At $1.25 in / $10 out per million tokens, it sits in the mid 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. GPT-5.1 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.
Frequently asked questions
Is Atria Dawn Preview or GPT-5.1 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 GPT-5.1 leans toward adaptive reasoning that scales compute to task difficulty, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Atria Dawn Preview or GPT-5.1?
Atria Dawn Preview is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while GPT-5.1 is API-metered at $1.25/$10 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?
GPT-5.1 — 400K vs 256K tokens, about 1.5× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Atria Dawn Preview and GPT-5.1 together?
Yes — a multi-model platform like LumiChats gives you Atria Dawn Preview, GPT-5.1 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 GPT-5.1?
Atria Dawn Preview — released September 11, 2026, about 10 months after GPT-5.1.
Atria Dawn Preview vs GPT-5.1
Shanghai AI Laboratory · China | OpenAI · US · 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 GPT-5.1 for adaptive reasoning that scales compute to task difficulty or general-purpose reasoning, coding and tool use. Choose Atria Dawn Preview if you need self-hosting or data privacy; GPT-5.1 if you want a managed API.
Atria Dawn Preview (Shanghai AI Laboratory, China) and GPT-5.1 (OpenAI, US) line up two different AI ecosystems against each other — a comparison that is as much about cost philosophy and openness as raw capability. 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. GPT-5.1 is openAI's late-2025 GPT-5.1 at $1.25/$10 — a capable general model since surpassed by the GPT-5.2–5.6 line. 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
▸Cost model: Atria Dawn Preview ships open weights you can self-host (hardware cost only, no per-token fee), while GPT-5.1 is API-metered at $1.25/$10 per 1M tokens. Your choice depends on whether you want zero marginal cost at the price of running infrastructure.
▸Context window: GPT-5.1 holds 1.5× more — 400K (~600 pages) vs 256K tokens (~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: Atria Dawn Preview is the newer model by about 10 months (released September 11, 2026), usually meaning fresher training data and capabilities.
▸Ecosystem: this is a China-vs-US matchup — they differ in pricing philosophy, data-residency options, and tooling ecosystems, not only benchmarks.
Side-by-side specs
Spec
Atria Dawn Preview
GPT-5.1
Provider
Shanghai AI Laboratory (China)
OpenAI (US)
Released
September 11, 2026
November 13, 2025
Context window
256K tokens (~393 pages)
400K (~600 pages)
Price (in/out)
Open weight (self-host / free)
$1.25/$10 per 1M tokens
Open weight?
Yes — self-hostable
No — API only
Modalities
text
text, image, code
SWE-Bench Verified
Not published
Not published
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 its weights are open while GPT-5.1 is API-only.
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 — GPT-5.1 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
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.
Adaptive reasoning that scales compute to task difficulty
GPT-5.1
OpenAI's late-2025 GPT-5.1 at $1.25/$10 — a capable general model since surpassed by the GPT-5.2–5.6 line — and it carries the larger 400K context.
General-purpose reasoning, coding and tool use
GPT-5.1
GPT-5.1 lists general-purpose reasoning, coding and tool use among its strengths; Atria Dawn Preview does not.
A large ~400K context for long documents and sessions
GPT-5.1
Its 400K window holds about 1.5× more than Atria Dawn Preview's 256K tokens in a single prompt.
Lowest cost at scale
Atria Dawn Preview
Its weights are open, so at volume you pay for your own hardware instead of GPT-5.1's $1.25/$10 per 1M tokens.
Largest single-prompt input
GPT-5.1
Its 400K window is about 1.5× larger than Atria Dawn Preview's 256K tokens, fitting roughly 600 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 GPT-5.1, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ GPT-5.1
Larger 400K 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; GPT-5.1 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 adaptive reasoning that scales compute to task difficulty
→ GPT-5.1
That is its strongest area.
An enterprise with regional data-residency rules
→ GPT-5.1 or Atria Dawn Preview
Origin (China vs US) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
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.
GPT-5.1: where it fits
OpenAI's late-2025 GPT-5.1 at $1.25/$10 — a capable general model since surpassed by the GPT-5.2–5.6 line. Released November 13, 2025 by OpenAI, it is built for adaptive reasoning that scales compute to task difficulty, general-purpose reasoning, coding and tool use, a large ~400K context for long documents and sessions, and text and image input.
Its trade-offs: superseded by GPT-5.2 through GPT-5.6 — kept for compatibility rather than being current, no reliably published SWE-Bench Verified figure, exact context window unconfirmed (400K vs 410K across trackers), and premium output price at $10/1M for a now-older model. At $1.25 in / $10 out per million tokens, it sits in the mid 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. GPT-5.1 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 GPT-5.1 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.
Is Atria Dawn Preview or GPT-5.1 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 GPT-5.1 leans toward adaptive reasoning that scales compute to task difficulty, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Atria Dawn Preview or GPT-5.1?
Atria Dawn Preview is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while GPT-5.1 is API-metered at $1.25/$10 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?
GPT-5.1 — 400K vs 256K tokens, about 1.5× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Atria Dawn Preview and GPT-5.1 together?
Yes — a multi-model platform like LumiChats gives you Atria Dawn Preview, GPT-5.1 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 GPT-5.1?
Atria Dawn Preview — released September 11, 2026, about 10 months after GPT-5.1.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.