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 Mistral Medium 3.5 for strong intelligence-for-size — artificial analysis intelligence index 30, near the top of its price tier or 128b dense open-weight model — self-hostable. On a tight budget at scale, Atria Dawn Preview is the value pick.
Atria Dawn Preview (Shanghai AI Laboratory, China) and Mistral Medium 3.5 (Mistral AI, France) 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. Mistral Medium 3.5 is mistral's efficient 128B open-weight model — a single dense model unifying reasoning and coding that punches above its size on independent tests (AA Index 30). They diverge most on price and context window — each quantified below from the models' real specs.
Key differences
Context window: 256K tokens vs 256K — within a few percent of each other, so treat this as a tie and test on your own long inputs, since usable recall varies by model.
Recency: Atria Dawn Preview is the newer model by about 5 months (released September 11, 2026), usually meaning fresher training data and capabilities.
Ecosystem: this is a China-vs-France matchup — they differ in pricing philosophy, data-residency options, and tooling ecosystems, not only benchmarks.
Specifications
Spec
Atria Dawn Preview
Mistral Medium 3.5
Provider
Shanghai AI Laboratory (China)
Mistral AI (France)
Released
September 11, 2026
April 28, 2026
Context window
256K tokens (~393 pages)
256K (~384 pages)
Price (in/out)
Open weight (self-host / free)
$1.5/$7.5 per 1M tokens
Open weight?
Yes — self-hostable
Yes — self-hostable
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 it is the newer of the two.
744B-parameter MoE built on a GLM-5.2 base, released under a fully open MIT license: Atria Dawn Preview — Mistral Medium 3.5 is comparatively weak here — license framing ('open' vs enterprise) varies across sources — confirm terms for commercial use
Free to self-host — no API pricing, run entirely on your own hardware: Atria Dawn Preview — Mistral Medium 3.5 is comparatively weak here — output pricing ($7.50/M) is higher than the cheapest Chinese rivals
Strong intelligence-for-size — Artificial Analysis Intelligence Index 30, near the top of its price tier: Mistral Medium 3.5 — Mistral Medium 3.5 lists strong intelligence-for-size — Artificial Analysis Intelligence Index 30, near the top of its price tier among its strengths; Atria Dawn Preview does not.
128B dense open-weight model — self-hostable: Mistral Medium 3.5 — 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
Unifies reasoning and coding into one model with an adjustable reasoning effort: Mistral Medium 3.5 — Mistral Medium 3.5 lists unifies reasoning and coding into one model with an adjustable reasoning effort 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 Mistral Medium 3.5's $1.5/$7.5 per 1M tokens.
Which should you pick?
A cost-sensitive startup shipping high volume: Atria Dawn Preview — At Open weight (self-host / free) it undercuts Mistral Medium 3.5, 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 strong intelligence-for-size — artificial analysis intelligence index 30, near the top of its price tier: Mistral Medium 3.5 — That is its strongest area.
An enterprise with regional data-residency rules: Mistral Medium 3.5 or Atria Dawn Preview — Origin (China vs France) 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.
Mistral Medium 3.5: where it fits
Mistral's efficient 128B open-weight model — a single dense model unifying reasoning and coding that punches above its size on independent tests (AA Index 30). Released April 28, 2026 by Mistral AI, it is built for strong intelligence-for-size — Artificial Analysis Intelligence Index 30, near the top of its price tier, 128B dense open-weight model — self-hostable, unifies reasoning and coding into one model with an adjustable reasoning effort, and 256K context with text and image input.
Its trade-offs: below the absolute frontier — a value/efficiency pick, not a flagship-beater, output pricing ($7.50/M) is higher than the cheapest Chinese rivals, license framing ('open' vs enterprise) varies across sources — confirm terms for commercial use, and no native video or audio. At $1.5 in / $7.5 out per million tokens, it sits in the mid price band.
The bottom line for this matchup
This is less "which is smarter" and more "which ecosystem fits." Atria Dawn Preview (China) and Mistral Medium 3.5 (France) differ on pricing philosophy, data-residency, and tooling as much as on raw scores. Atria Dawn Preview is the cheaper option, which matters at volume. The pragmatic move is to run one real task through both and judge the outputs against your own constraints — including where your data is allowed to be processed.
Frequently asked questions
Is Atria Dawn Preview or Mistral Medium 3.5 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 Mistral Medium 3.5 leans toward strong intelligence-for-size — artificial analysis intelligence index 30, near the top of its price tier, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Atria Dawn Preview or Mistral Medium 3.5?
Atria Dawn Preview is cheaper — Open weight (self-host / free) vs $1.5/$7.5 per 1M tokens.
Which has the bigger context window?
Effectively neither — 256K tokens vs 256K is a difference of a few percent. Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both Atria Dawn Preview and Mistral Medium 3.5 together?
Yes — a multi-model platform like LumiChats gives you Atria Dawn Preview, Mistral Medium 3.5 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 Mistral Medium 3.5?
Atria Dawn Preview — released September 11, 2026, about 5 months after Mistral Medium 3.5.
Atria Dawn Preview vs Mistral Medium 3.5
Shanghai AI Laboratory · China | Mistral AI · France · 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 Mistral Medium 3.5 for strong intelligence-for-size — artificial analysis intelligence index 30, near the top of its price tier or 128b dense open-weight model — self-hostable. On a tight budget at scale, Atria Dawn Preview is the value pick.
Atria Dawn Preview (Shanghai AI Laboratory, China) and Mistral Medium 3.5 (Mistral AI, France) 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. Mistral Medium 3.5 is mistral's efficient 128B open-weight model — a single dense model unifying reasoning and coding that punches above its size on independent tests (AA Index 30). They diverge most on price and context window — each quantified below from the models' real specs.
Key differences at a glance
▸Context window: 256K tokens vs 256K — within a few percent of each other, so treat this as a tie and test on your own long inputs, since usable recall varies by model.
▸Recency: Atria Dawn Preview is the newer model by about 5 months (released September 11, 2026), usually meaning fresher training data and capabilities.
▸Ecosystem: this is a China-vs-France matchup — they differ in pricing philosophy, data-residency options, and tooling ecosystems, not only benchmarks.
Side-by-side specs
Spec
Atria Dawn Preview
Mistral Medium 3.5
Provider
Shanghai AI Laboratory (China)
Mistral AI (France)
Released
September 11, 2026
April 28, 2026
Context window
256K tokens (~393 pages)
256K (~384 pages)
Price (in/out)
Open weight (self-host / free)
$1.5/$7.5 per 1M tokens
Open weight?
Yes — self-hostable
Yes — self-hostable
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 it is the newer of the two.
744B-parameter MoE built on a GLM-5.2 base, released under a fully open MIT license
Atria Dawn Preview
Mistral Medium 3.5 is comparatively weak here — license framing ('open' vs enterprise) varies across sources — confirm terms for commercial use
Free to self-host — no API pricing, run entirely on your own hardware
Atria Dawn Preview
Mistral Medium 3.5 is comparatively weak here — output pricing ($7.50/M) is higher than the cheapest Chinese rivals
Strong intelligence-for-size — Artificial Analysis Intelligence Index 30, near the top of its price tier
Mistral Medium 3.5
Mistral Medium 3.5 lists strong intelligence-for-size — Artificial Analysis Intelligence Index 30, near the top of its price tier among its strengths; Atria Dawn Preview does not.
128B dense open-weight model — self-hostable
Mistral Medium 3.5
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
Unifies reasoning and coding into one model with an adjustable reasoning effort
Mistral Medium 3.5
Mistral Medium 3.5 lists unifies reasoning and coding into one model with an adjustable reasoning effort 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 Mistral Medium 3.5's $1.5/$7.5 per 1M tokens.
Which should you pick?
A cost-sensitive startup shipping high volume
→ Atria Dawn Preview
At Open weight (self-host / free) it undercuts Mistral Medium 3.5, 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 strong intelligence-for-size — artificial analysis intelligence index 30, near the top of its price tier
→ Mistral Medium 3.5
That is its strongest area.
An enterprise with regional data-residency rules
→ Mistral Medium 3.5 or Atria Dawn Preview
Origin (China vs France) 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.
Mistral Medium 3.5: where it fits
Mistral's efficient 128B open-weight model — a single dense model unifying reasoning and coding that punches above its size on independent tests (AA Index 30). Released April 28, 2026 by Mistral AI, it is built for strong intelligence-for-size — Artificial Analysis Intelligence Index 30, near the top of its price tier, 128B dense open-weight model — self-hostable, unifies reasoning and coding into one model with an adjustable reasoning effort, and 256K context with text and image input.
Its trade-offs: below the absolute frontier — a value/efficiency pick, not a flagship-beater, output pricing ($7.50/M) is higher than the cheapest Chinese rivals, license framing ('open' vs enterprise) varies across sources — confirm terms for commercial use, and no native video or audio. At $1.5 in / $7.5 out per million tokens, it sits in the mid price band.
The bottom line for this matchup
This is less "which is smarter" and more "which ecosystem fits." Atria Dawn Preview (China) and Mistral Medium 3.5 (France) differ on pricing philosophy, data-residency, and tooling as much as on raw scores. Atria Dawn Preview is the cheaper option, which matters at volume. The pragmatic move is to run one real task through both and judge the outputs against your own constraints — including where your data is allowed to be processed.
Want both Atria Dawn Preview and Mistral Medium 3.5 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.
Is Atria Dawn Preview or Mistral Medium 3.5 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 Mistral Medium 3.5 leans toward strong intelligence-for-size — artificial analysis intelligence index 30, near the top of its price tier, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Atria Dawn Preview or Mistral Medium 3.5?
Atria Dawn Preview is cheaper — Open weight (self-host / free) vs $1.5/$7.5 per 1M tokens.
Which has the bigger context window?
Effectively neither — 256K tokens vs 256K is a difference of a few percent. Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both Atria Dawn Preview and Mistral Medium 3.5 together?
Yes — a multi-model platform like LumiChats gives you Atria Dawn Preview, Mistral Medium 3.5 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 Mistral Medium 3.5?
Atria Dawn Preview — released September 11, 2026, about 5 months after Mistral Medium 3.5.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.