DeepSeek-V2.5 vs LongCat-2.5
LongCat-2.5 leads the LLM Stats Score 50.0 to 7.6. DeepSeek-V2.5 is 3.0x cheaper per token.
DeepSeek · Meituan · Updated for 2026
Which is better?
LongCat-2.5 leads the overall LLM Stats Score 50.0 to 7.6, ranking #20 overall.
On price, DeepSeek-V2.5 is roughly 3.0x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
LongCat-2.5 also accepts a larger context window (1,048,576 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 DeepSeek-V2.5
- cost matters — it's about 3.0x cheaper per token
- you need open weights you can self-host or fine-tune
Choose LongCat-2.5
- overall performance matters — it scores 50.0 and ranks #20 on LLM Stats
- your work emphasizes reasoning and coding — it leads those capability indexes
- you process long inputs — it offers a 1,048,576 token context window
- you want the most recent training data — it shipped Nov 2026
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
15 reported for DeepSeek-V2.5 · 23 for LongCat-2.5
DeepSeek-V2.5 and LongCat-2.5don'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, DeepSeek-V2.5 ($0.14/1M tokens) is 2.1x cheaper than LongCat-2.5 ($0.30/1M tokens).
For output processing, DeepSeek-V2.5 ($0.28/1M tokens) is 4.3x cheaper than LongCat-2.5 ($1.20/1M tokens).
In conclusion, LongCat-2.5 is more expensive than DeepSeek-V2.5.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
LongCat-2.5 has 1364.0B more parameters than DeepSeek-V2.5, making it 578.0% larger.
Context Window
Maximum input and output token capacity
LongCat-2.5 accepts 1,048,576 input tokens compared to DeepSeek-V2.5's 8,192 tokens. LongCat-2.5 can generate longer responses up to 131,072 tokens, while DeepSeek-V2.5 is limited to 8,192 tokens.
Input capabilities
Documented input modalities across available providers
LongCat-2.5 supports multimodal inputs, whereas DeepSeek-V2.5 does not.
LongCat-2.5 can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek-V2.5
LongCat-2.5
Release Timeline
When each model was launched
DeepSeek-V2.5 was released on 2024-05-08, while LongCat-2.5 was released on 2026-11-01.
LongCat-2.5 is 30 months newer than DeepSeek-V2.5.
May 8, 2024
2.5 years ago
Nov 1, 2026
1 days ago
2.5yr newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
DeepSeek-V2.5 is available from DeepSeek, DeepInfra, Hyperbolic. LongCat-2.5 is available from Meituan.
DeepSeek-V2.5
LongCat-2.5
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V2.5 and LongCat-2.5 side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V2.5 vs LongCat-2.5.