Gemma 4 31B vs LongCat-Flash-Thinking-2601
Gemma 4 31B significantly outperforms across most benchmarks. Gemma 4 31B is 2.7x cheaper per token.
Google · Meituan · Updated for 2026
Which is better?
Gemma 4 31B outperforms in 2 benchmarks (GPQA, Humanity's Last Exam), while LongCat-Flash-Thinking-2601 is better at 0 benchmarks. Gemma 4 31B significantly outperforms across most benchmarks.
On price, Gemma 4 31B is roughly 2.7x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Gemma 4 31B also accepts a larger context window (262,144 input tokens), making it the stronger choice for long documents and large codebases.
Based on current benchmark, pricing, and model metadata for 2026.
Choose Gemma 4 31B
- you want the strongest raw capability — it leads on 2 of 2 shared benchmarks
- cost matters — it's about 2.7x cheaper per token
- you process long inputs — it offers a 262,144 token context window
- you want the most recent training data — it shipped Apr 2026
Choose LongCat-Flash-Thinking-2601
- you want predictable pricing at $0.30/M input and $1.20/M output
At a glance
The differences that matter most.
Performance Benchmarks
Comparative analysis across standard metrics
Gemma 4 31B outperforms in 2 benchmarks (GPQA, Humanity's Last Exam), while LongCat-Flash-Thinking-2601 is better at 0 benchmarks.
Gemma 4 31B significantly outperforms across most benchmarks.
Arena Performance
Playground indexes and blind preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, Gemma 4 31B ($0.13/1M tokens) is 2.3x cheaper than LongCat-Flash-Thinking-2601 ($0.30/1M tokens).
For output processing, Gemma 4 31B ($0.38/1M tokens) is 3.2x cheaper than LongCat-Flash-Thinking-2601 ($1.20/1M tokens).
In conclusion, LongCat-Flash-Thinking-2601 is more expensive than Gemma 4 31B.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
LongCat-Flash-Thinking-2601 has 529.3B more parameters than Gemma 4 31B, making it 1724.1% larger.
Context Window
Maximum input and output token capacity
Gemma 4 31B accepts 262,144 input tokens compared to LongCat-Flash-Thinking-2601's 128,000 tokens. Gemma 4 31B can generate longer responses up to 131,072 tokens, while LongCat-Flash-Thinking-2601 is limited to 128,000 tokens.
Input Capabilities
Supported data types and modalities
Gemma 4 31B supports multimodal inputs, whereas LongCat-Flash-Thinking-2601 does not.
Gemma 4 31B can handle both text and other forms of data like images, making it suitable for multimodal applications.
Gemma 4 31B
LongCat-Flash-Thinking-2601
License
Usage and distribution terms
Gemma 4 31B is licensed under Apache 2.0, while LongCat-Flash-Thinking-2601 uses MIT.
License differences may affect how you can use these models in commercial or open-source projects.
Apache 2.0
Open weights
MIT
Open weights
Release Timeline
When each model was launched
Gemma 4 31B was released on 2026-04-02, while LongCat-Flash-Thinking-2601 was released on 2026-01-14.
Gemma 4 31B is 3 months newer than LongCat-Flash-Thinking-2601.
Apr 2, 2026
4 months ago
2mo newerJan 14, 2026
7 months ago
Knowledge Cutoff
When training data ends
Gemma 4 31B has a documented knowledge cutoff of 2025-01-01, while LongCat-Flash-Thinking-2601's cutoff date is not specified.
We can confirm Gemma 4 31B's training data extends to 2025-01-01, but cannot make a direct comparison without LongCat-Flash-Thinking-2601's cutoff date.
Jan 2025
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Provider Availability
Gemma 4 31B is available from DeepInfra, FriendliAI, Novita, Together. LongCat-Flash-Thinking-2601 is available from Meituan.
Gemma 4 31B
LongCat-Flash-Thinking-2601
Outputs Comparison
Judge for yourself.
Run your own prompts against Gemma 4 31B and LongCat-Flash-Thinking-2601 side-by-side, then vote on the output you prefer.
FAQ
Common questions about Gemma 4 31B vs LongCat-Flash-Thinking-2601.