GPT-6 Sol vs LongCat-Flash-Chat
GPT-6 Sol leads the LLM Stats Score 49.4 to 19.8. LongCat-Flash-Chat is 7.6x cheaper per token.
OpenAI · Meituan · Updated for 2026
Which is better?
GPT-6 Sol leads the overall LLM Stats Score 49.4 to 19.8, ranking #21 overall.
On price, LongCat-Flash-Chat is roughly 7.6x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
GPT-6 Sol also accepts a larger context window (1,050,000 input tokens), making it the stronger choice for long documents and large codebases.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose GPT-6 Sol
- overall performance matters — it scores 49.4 and ranks #21 on LLM Stats
- your work emphasizes reasoning and coding — it leads those capability indexes
- you process long inputs — it offers a 1,050,000 token context window
- you want the most recent training data — it shipped Sep 2026
Choose LongCat-Flash-Chat
- cost matters — it's about 7.6x cheaper per token
- you need open weights you can self-host or fine-tune
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
5 reported for GPT-6 Sol · 16 for LongCat-Flash-Chat
GPT-6 Sol and LongCat-Flash-Chatdon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, GPT-6 Sol ($2.00/1M tokens) is 6.7x more expensive than LongCat-Flash-Chat ($0.30/1M tokens).
For output processing, GPT-6 Sol ($10.00/1M tokens) is 8.3x more expensive than LongCat-Flash-Chat ($1.20/1M tokens).
In conclusion, GPT-6 Sol is more expensive than LongCat-Flash-Chat.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
GPT-6 Sol accepts 1,050,000 input tokens compared to LongCat-Flash-Chat's 128,000 tokens. Both models can generate responses up to 128,000 tokens.
Input capabilities
Documented input modalities across available providers
GPT-6 Sol supports multimodal inputs, whereas LongCat-Flash-Chat does not.
GPT-6 Sol can handle both text and other forms of data like images, making it suitable for multimodal applications.
GPT-6 Sol
LongCat-Flash-Chat
License
Usage and distribution terms
GPT-6 Sol is licensed under a proprietary license, while LongCat-Flash-Chat uses MIT.
License differences may affect how you can use these models in commercial or open-source projects.
Proprietary
Closed source
MIT
Open weights
Release Timeline
When each model was launched
GPT-6 Sol was released on 2026-09-22, while LongCat-Flash-Chat was released on 2025-08-29.
GPT-6 Sol is 13 months newer than LongCat-Flash-Chat.
Sep 22, 2026
0 days ago
1.1yr newerAug 29, 2025
1.1 years ago
Knowledge Cutoff
When training data ends
GPT-6 Sol has a documented knowledge cutoff of 2026-04-20, while LongCat-Flash-Chat's cutoff date is not specified.
We can confirm GPT-6 Sol's training data extends to 2026-04-20, but cannot make a direct comparison without LongCat-Flash-Chat's cutoff date.
Apr 2026
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Provider Availability
GPT-6 Sol is available from OpenAI. LongCat-Flash-Chat is available from Meituan.
GPT-6 Sol
LongCat-Flash-Chat
Outputs Comparison
Judge for yourself.
Run your own prompts against GPT-6 Sol and LongCat-Flash-Chat side-by-side, then vote on the output you prefer.
FAQ
Common questions about GPT-6 Sol vs LongCat-Flash-Chat.