LongCat-Flash-Chat vs Qwen3-235B-A22B-Instruct-2507
Qwen3-235B-A22B-Instruct-2507 shows notably better performance in the majority of benchmarks. Qwen3-235B-A22B-Instruct-2507 is 1.7x cheaper per token.
Meituan · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
LongCat-Flash-Chat outperforms in 2 benchmarks (IFEval, Tau2 Airline), while Qwen3-235B-A22B-Instruct-2507 is better at 5 benchmarks (AIME 2025, GPQA, MMLU-Pro, Tau2 Retail, ZebraLogic). Qwen3-235B-A22B-Instruct-2507 shows notably better performance in the majority of benchmarks.
On price, Qwen3-235B-A22B-Instruct-2507 is roughly 1.7x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Qwen3-235B-A22B-Instruct-2507 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 LongCat-Flash-Chat
- you want the most recent training data — it shipped Aug 2025
Choose Qwen3-235B-A22B-Instruct-2507
- you want the strongest raw capability — it leads on 5 of 7 shared benchmarks
- cost matters — it's about 1.7x cheaper per token
- you process long inputs — it offers a 262,144 token context window
At a glance
The differences that matter most.
Performance Benchmarks
Comparative analysis across standard metrics
LongCat-Flash-Chat outperforms in 2 benchmarks (IFEval, Tau2 Airline), while Qwen3-235B-A22B-Instruct-2507 is better at 5 benchmarks (AIME 2025, GPQA, MMLU-Pro, Tau2 Retail, ZebraLogic).
Qwen3-235B-A22B-Instruct-2507 shows notably better performance in the majority of benchmarks.
Arena Performance
Playground indexes and blind preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, LongCat-Flash-Chat ($0.30/1M tokens) is 2.0x more expensive than Qwen3-235B-A22B-Instruct-2507 ($0.15/1M tokens).
For output processing, LongCat-Flash-Chat ($1.20/1M tokens) is 1.5x more expensive than Qwen3-235B-A22B-Instruct-2507 ($0.80/1M tokens).
In conclusion, LongCat-Flash-Chat is more expensive than Qwen3-235B-A22B-Instruct-2507.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
LongCat-Flash-Chat has 325.0B more parameters than Qwen3-235B-A22B-Instruct-2507, making it 138.3% larger.
Context Window
Maximum input and output token capacity
Qwen3-235B-A22B-Instruct-2507 accepts 262,144 input tokens compared to LongCat-Flash-Chat's 128,000 tokens. Qwen3-235B-A22B-Instruct-2507 can generate longer responses up to 131,072 tokens, while LongCat-Flash-Chat is limited to 128,000 tokens.
License
Usage and distribution terms
LongCat-Flash-Chat is licensed under MIT, while Qwen3-235B-A22B-Instruct-2507 uses Apache 2.0.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Apache 2.0
Open weights
Release Timeline
When each model was launched
LongCat-Flash-Chat was released on 2025-08-29, while Qwen3-235B-A22B-Instruct-2507 was released on 2025-07-22.
LongCat-Flash-Chat is 1 month newer than Qwen3-235B-A22B-Instruct-2507.
Aug 29, 2025
12 months ago
1mo newerJul 22, 2025
1.1 years ago
Knowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
LongCat-Flash-Chat is available from Meituan. Qwen3-235B-A22B-Instruct-2507 is available from Fireworks, Novita.
LongCat-Flash-Chat
Qwen3-235B-A22B-Instruct-2507
Outputs Comparison
Judge for yourself.
Run your own prompts against LongCat-Flash-Chat and Qwen3-235B-A22B-Instruct-2507 side-by-side, then vote on the output you prefer.
FAQ
Common questions about LongCat-Flash-Chat vs Qwen3-235B-A22B-Instruct-2507.