Llama 3.1 405B Instruct vs LongCat-2.5
LongCat-2.5 leads the LLM Stats Score 50.0 to 14.3. LongCat-2.5 is 1.7x cheaper per token.
Meta · Meituan · Updated for 2026
Which is better?
LongCat-2.5 leads the overall LLM Stats Score 50.0 to 14.3, ranking #20 overall.
On price, LongCat-2.5 is roughly 1.7x 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 Llama 3.1 405B Instruct
- 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
- cost matters — it's about 1.7x cheaper per token
- 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
18 reported for Llama 3.1 405B Instruct · 23 for LongCat-2.5
Llama 3.1 405B Instruct 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, Llama 3.1 405B Instruct ($0.89/1M tokens) is 3.0x more expensive than LongCat-2.5 ($0.30/1M tokens).
For output processing, Llama 3.1 405B Instruct ($0.89/1M tokens) is 1.3x cheaper than LongCat-2.5 ($1.20/1M tokens).
In conclusion, Llama 3.1 405B Instruct 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 1195.0B more parameters than Llama 3.1 405B Instruct, making it 295.1% larger.
Context Window
Maximum input and output token capacity
LongCat-2.5 accepts 1,048,576 input tokens compared to Llama 3.1 405B Instruct's 128,000 tokens. LongCat-2.5 can generate longer responses up to 131,072 tokens, while Llama 3.1 405B Instruct is limited to 128,000 tokens.
Input capabilities
Documented input modalities across available providers
LongCat-2.5 supports multimodal inputs, whereas Llama 3.1 405B Instruct does not.
LongCat-2.5 can handle both text and other forms of data like images, making it suitable for multimodal applications.
Llama 3.1 405B Instruct
LongCat-2.5
Release Timeline
When each model was launched
Llama 3.1 405B Instruct was released on 2024-07-23, while LongCat-2.5 was released on 2026-11-01.
LongCat-2.5 is 28 months newer than Llama 3.1 405B Instruct.
Jul 23, 2024
2.3 years ago
Nov 1, 2026
0 days ago
2.3yr newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
Llama 3.1 405B Instruct is available from Lambda, DeepInfra, Fireworks, Bedrock, Together, Hyperbolic, Google, Replicate. LongCat-2.5 is available from Meituan.
Llama 3.1 405B Instruct
LongCat-2.5
Outputs Comparison
Judge for yourself.
Run your own prompts against Llama 3.1 405B Instruct and LongCat-2.5 side-by-side, then vote on the output you prefer.
FAQ
Common questions about Llama 3.1 405B Instruct vs LongCat-2.5.