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DiffusionGemma 26B-A4B vs LongCat-Flash-Chat

DiffusionGemma 26B-A4B and LongCat-Flash-Chat are closely matched at 19.4 and 19.8 on the LLM Stats Score.

Google · Meituan · Updated for 2026

Which is better?

DiffusionGemma 26B-A4B and LongCat-Flash-Chat are closely matched on the overall LLM Stats Score at 19.4 and 19.8.

In the 2 individual benchmarks reported for both models, LongCat-Flash-Chat wins 2; this is a narrower head-to-head signal than the composite indexes.

Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose DiffusionGemma 26B-A4B

  • you want the most recent training data — it shipped Jun 2026

Choose LongCat-Flash-Chat

  • you value its reported benchmark strengths — it wins 2 of 2 exact shared results

At a glance

The differences that matter most.

DiffusionGemma 26B-A4B
Google
LongCat-Flash-Chat
Meituan
Core performance indexes
LLM Stats Score
19.4
#204
19.8
#197
Reasoning
19.1
#201
19.8
#193
Agents
0.5
#170
9.2
#127
Cost, coverage & limits
Benchmark wins
0 of 2
2 of 2
Input price
— / M
$0.30 / M
Output price
— / M
$1.20 / M
Context window
—
128,000

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
DiffusionGemma 26B-A4B
LongCat-Flash-Chat
Math
17.6#192
18.9#174
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

14 reported for DiffusionGemma 26B-A4B · 16 for LongCat-Flash-Chat

2 shared

DiffusionGemma 26B-A4B outperforms in 0 benchmarks, while LongCat-Flash-Chat is better at 2 benchmarks (GPQA, MMLU-Pro).

LongCat-Flash-Chat significantly outperforms across most benchmarks.

Thu Sep 10 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

534.8B diff

LongCat-Flash-Chat has 534.8B more parameters than DiffusionGemma 26B-A4B, making it 2122.2% larger.

Google
DiffusionGemma 26B-A4B
25.2Bparameters
Meituan
LongCat-Flash-Chat
560.0Bparameters
25.2B
DiffusionGemma 26B-A4B
560.0B
LongCat-Flash-Chat

Context Window

Maximum input and output token capacity

Only LongCat-Flash-Chat specifies input context (128,000 tokens). Only LongCat-Flash-Chat specifies output context (128,000 tokens).

Google
DiffusionGemma 26B-A4B
Input- tokens
Output- tokens
Meituan
LongCat-Flash-Chat
Input128,000 tokens
Output128,000 tokens
Thu Sep 10 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

DiffusionGemma 26B-A4B supports multimodal inputs, whereas LongCat-Flash-Chat does not.

DiffusionGemma 26B-A4B can handle both text and other forms of data like images, making it suitable for multimodal applications.

DiffusionGemma 26B-A4B

Text
Images
Audio
Video

LongCat-Flash-Chat

Text
Images
Audio
Video

License

Usage and distribution terms

DiffusionGemma 26B-A4B is licensed under Apache 2.0, while LongCat-Flash-Chat uses MIT.

License differences may affect how you can use these models in commercial or open-source projects.

DiffusionGemma 26B-A4B

Apache 2.0

Open weights

LongCat-Flash-Chat

MIT

Open weights

Release Timeline

When each model was launched

DiffusionGemma 26B-A4B was released on 2026-06-10, while LongCat-Flash-Chat was released on 2025-08-29.

DiffusionGemma 26B-A4B is 10 months newer than LongCat-Flash-Chat.

DiffusionGemma 26B-A4B

Jun 10, 2026

3 months ago

9mo newer
LongCat-Flash-Chat

Aug 29, 2025

1.0 years ago

Knowledge Cutoff

When training data ends

DiffusionGemma 26B-A4B has a documented knowledge cutoff of 2025-01-01, while LongCat-Flash-Chat's cutoff date is not specified.

We can confirm DiffusionGemma 26B-A4B's training data extends to 2025-01-01, but cannot make a direct comparison without LongCat-Flash-Chat's cutoff date.

DiffusionGemma 26B-A4B

Jan 2025

LongCat-Flash-Chat

—

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Judge for yourself.

Run your own prompts against DiffusionGemma 26B-A4B and LongCat-Flash-Chat side-by-side, then vote on the output you prefer.

DiffusionGemma 26B-A4B
✓ Preferred
LongCat-Flash-Chat
Open in Playground

FAQ

Common questions about DiffusionGemma 26B-A4B vs LongCat-Flash-Chat.

Which is better, DiffusionGemma 26B-A4B or LongCat-Flash-Chat?

DiffusionGemma 26B-A4B and LongCat-Flash-Chat are closely matched on the LLM Stats Score at 19.4 and 19.8. DiffusionGemma 26B-A4B is made by Google and LongCat-Flash-Chat is made by Meituan. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does DiffusionGemma 26B-A4B compare to LongCat-Flash-Chat in benchmarks?

DiffusionGemma 26B-A4B scores MMMLU: 81.5%, MMLU-Pro: 77.6%, GPQA: 73.2%, MathVision: 70.5%, AIME 2026: 69.1%. LongCat-Flash-Chat scores MATH-500: 96.4%, MMLU: 89.7%, IFEval: 89.6%, ZebraLogic: 89.3%, HumanEval: 88.4%.

What are the context window sizes for DiffusionGemma 26B-A4B and LongCat-Flash-Chat?

DiffusionGemma 26B-A4B supports an unknown number of tokens and LongCat-Flash-Chat supports 128K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between DiffusionGemma 26B-A4B and LongCat-Flash-Chat?

Key differences include LLM Stats Score (19.4 vs 19.8), multimodal support (yes vs no), licensing (Apache 2.0 vs MIT). See the full comparison above for benchmark-by-benchmark results.

Who makes DiffusionGemma 26B-A4B and LongCat-Flash-Chat?

DiffusionGemma 26B-A4B is developed by Google and LongCat-Flash-Chat is developed by Meituan.

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