DeepSeek-V4-Pro-Max vs LongCat-2.5
LongCat-2.5 leads the LLM Stats Score 50.0 to 42.6. LongCat-2.5 is 3.1x cheaper per token.
DeepSeek · Meituan · Updated for 2026
Which is better?
LongCat-2.5 leads the overall LLM Stats Score 50.0 to 42.6, ranking #20 overall.
In the 2 individual benchmarks reported for both models, LongCat-2.5 wins 2; this is a narrower head-to-head signal than the composite indexes.
On price, LongCat-2.5 is roughly 3.1x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose DeepSeek-V4-Pro-Max
- 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 value its reported benchmark strengths — it wins 2 of 2 exact shared results
- cost matters — it's about 3.1x cheaper per token
- 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
22 reported for DeepSeek-V4-Pro-Max · 23 for LongCat-2.5
DeepSeek-V4-Pro-Max outperforms in 0 benchmarks, while LongCat-2.5 is better at 2 benchmarks (BrowseComp, MCP Atlas).
LongCat-2.5 significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek-V4-Pro-Max ($1.30/1M tokens) is 4.3x more expensive than LongCat-2.5 ($0.30/1M tokens).
For output processing, DeepSeek-V4-Pro-Max ($2.60/1M tokens) is 2.2x more expensive than LongCat-2.5 ($1.20/1M tokens).
In conclusion, DeepSeek-V4-Pro-Max is more expensive than LongCat-2.5.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
LongCat-2.5 has 0.0B more parameters than DeepSeek-V4-Pro-Max, making it 0.0% larger.
Context Window
Maximum input and output token capacity
Both models have the same input context window of 1,048,576 tokens. DeepSeek-V4-Pro-Max can generate longer responses up to 1,048,576 tokens, while LongCat-2.5 is limited to 131,072 tokens.
Input capabilities
Documented input modalities across available providers
LongCat-2.5 supports multimodal inputs, whereas DeepSeek-V4-Pro-Max does not.
LongCat-2.5 can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek-V4-Pro-Max
LongCat-2.5
Release Timeline
When each model was launched
DeepSeek-V4-Pro-Max was released on 2026-04-23, while LongCat-2.5 was released on 2026-11-01.
LongCat-2.5 is 6 months newer than DeepSeek-V4-Pro-Max.
Apr 23, 2026
6 months ago
Nov 1, 2026
0 days ago
6mo 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-V4-Pro-Max is available from DeepInfra, Novita, DeepSeek, Fireworks, Together. LongCat-2.5 is available from Meituan.
DeepSeek-V4-Pro-Max
LongCat-2.5
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V4-Pro-Max and LongCat-2.5 side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V4-Pro-Max vs LongCat-2.5.