LLMcompare

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A · open · Other

Atria Dawn Preview

Shanghai AI Lab

B · open · Other

LongCat-Flash-Chat

Meituan

2:0

overall capability wins (0 ties across 2 scored). Atria Dawn Preview leads overall.

  • Specs2:0

Verdict

Atria Dawn Preview offers ~2.0x larger context (256K vs 131K).

Cost for 1M in + 250K out

Illustrative chat workload at primary-provider list prices.

Atria Dawn Preview
-
LongCat-Flash-Chat
-

Price per 1M tokens

Full comparison

Organization

Shanghai AI Lab

Meituan

Family

Other

Other

License

MIT

MIT

Open weights

Yes

Yes

Release

Sep 11, 2026

Sep 1, 2025

Knowledge cutoff

-

-

API / provider

No primary API price listed

No primary API price listed

Modalities

text → text

text → text

Specs

Context window

256K

131K

A +125K

Max output

66K

-

—

Parameters

744B

560B (27B act.)

A +184

Pricing

Input $/1M

—

—

—

Output $/1M

—

—

—

Blended $/1M (3∶1)

-

-

—

Speed

tok/s

-

-

—

TTFT (s)

-

-

—

Reasoning

MMLU-Pro

—

—

—

GPQA Diamond

—

—

—

Humanity's Last Exam

—

—

—

AIME 2025

—

—

—

MATH-500

—

—

—

Humanity's Last Exam (with tools)

—

—

—

AA-Omniscience Accuracy

—

—

—

AA-LCR v1.1

—

—

—

CritPt

—

—

—

MMMU-Pro

—

—

—

IFBench

—

—

—

Chartography

—

—

—

Chartography (With Tools)

—

—

—

Coding

SWE-bench Verified

—

—

—

SWE-bench Pro

59.6

—

—

SWE-bench Multilingual

—

—

—

LiveCodeBench

—

—

—

Terminal-Bench 2.1

—

—

—

Aider Polyglot

—

—

—

Terminal-Bench 3

—

—

—

BigCodeBench

—

—

—

SciCode

—

—

—

CursorBench

—

—

—

SWE-Rebench

—

—

—

NL2Repo-Bench

—

—

—

DeepSWE

—

—

—

WebDev Arena

—

—

—

Terminal-Bench 4.0

—

—

—

CursorBench 4.0

—

—

—

FrontierCode v1.1 (Main)

—

—

—

Arena

LMArena Elo

—

1,401

—

Atria Dawn Preview

Context
256K / 66K out
Parameters
744B
Price
—
Speed
—
Modalities
text → text
License
MIT

Shanghai AI Laboratory's open-weight agentic MoE (744B total, MIT license, 256K context), built on a GLM-5.2 base and trained by the cross-institutional ATRIA initiative (with Fudan NLP Lab) for long-horizon research and engineering workflows: problem analysis, tool use, code, experiments, and failure recovery. Benchmark scores are from the model's own technical report and have not yet been independently verified by a third-party evaluator.

LongCat-Flash-Chat

Context
131K
Parameters
560B (27B act.)
Price
—
Speed
—
Modalities
text → text
License
MIT

Meituan's LongCat-Flash foundation model (560B total, ~27B average active MoE with Zero-Computation Experts for adaptive per-token compute), released Sept 2025 under MIT — predates the LongCat-2.0 flagship.

Benchmark charts

Winner bars are emphasized. Per-benchmark deltas sit above each chart.

These two models have no overlapping published benchmarks in our dataset. Compare specs and pricing instead.

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