Model profile
LongCat
New in 2026

Meituan: LongCat 2.0

Meituan: LongCat 2.0 is a budget-priced text-first model from LongCat with heavy runtime profile, large context posture, and the clearest fit around long-context research / agent workflows.

Best for: Long-context research / Agent workflowsHeavy latencyLarge contextBudget pricing
Intelligence
34.0

Benchmark blend

Coding
45.3

Dev workflow signal

Context
1049K Tokens

Large

Input Price
$0.75

Budget tier

Decision snapshot
57

Meituan: LongCat 2.0 currently reads as a budget text-first option with large context and a heavy runtime profile.

Overall profile
Selective fit
Best for
Long-context research / Agent workflows
Latency tier
Heavy
Price tier
Budget
Source coverage
OpenRouterArtificial Analysis

Decision Strip

Decision rail before the raw tables

Core buy-side signals stay in one pass. The rest of the page expands only after intelligence, speed, context, and price are clear.

Intelligence
34.0
34

General reasoning and benchmark headroom.

Limited
Speed
39 tok/s
46

TTFT 1.69s

Situational
Context
1049K Tokens
100

How much prompt and task state can stay in view.

Above average
Price
$0.75
86

$2.95 output / 1M

Efficient

Editorial Profile

Meituan: LongCat 2.0 in one narrative

Positioning, tradeoffs, and fit are consolidated into one read instead of repeating the same story across separate cards.

Selective fitCoding score 45Math score N/A

LongCat 2.0 is a sparse mixture-of-experts language model from Meituan, with 48B active parameters out of 1.6T total. It is suited for coding, repository-level changes, long-horizon problem solving, and agentic...

Identity

LongCat text-first profile

Positioning

Long-context research / Agent workflows with large context and heavy runtime.

Cost posture

Efficient spend profile. More comfortable for sustained prompt volume if the capability fit is right.

Strengths
  • Large context headroom supports repo-wide prompts and long research sessions.

Tradeoffs
  • Budget-friendly input pricing is a strength, but raw capability may vary by workload.

  • Latency profile is better for deliberate runs than rapid back-and-forth chat.

  • Current metadata points to a text-first profile rather than a broad multimodal one.

Best fit
  • Long-context summarization, repo analysis, and policy or document review.

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Intelligence
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Context
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Input Price
$0.00

Benchmarks

Grouped by job-to-be-done

Only benchmark categories with actual signal are shown. Secondary values stay as simple definitions instead of nested micro-cards.

General intelligence

Broad reasoning, knowledge depth, and flagship benchmark posture.

Intelligence Index
34.0
GPQA
78.0%
HLE
33.7%
Coding

Software implementation, debugging quality, and coding benchmark signal.

Coding Index
45.3
SciCode
35.4%
Agent / tool use

Long-horizon execution quality and interactive benchmark evidence.

LCR
62.7%

Extra benchmark cuts are not available for this category yet.

Specs & Pricing

Technical snapshot and cost posture

Specs stay neutral, pricing gets emphasis through values rather than extra containers. Raw provider internals remain in metadata at the end.

Technical snapshot
Context Window
1049K Tokens
Vision
Text-first
Modalities
text
Tokenizer
Other
Max Completion
262144
Moderation
No
Supported Parameters
frequency_penaltyinclude_reasoninglogit_biasmax_tokensmin_ppresence_penaltyreasoningrepetition_penaltyseedstoptemperaturetool_choicetoolstop_ktop_p
Input Modalities
text
Output Modalities
text
Price architecture
Input
per 1M input tokens
$0.75
Output
per 1M output tokens
$2.95
Blended
AA 3:1 mix
$1.30

This model is relatively efficient on price. It is the easier fit when sustained prompt volume matters.

OR Cache Read
$0.00

Metadata

Raw source tables at the end

Verification details remain available, but the page no longer forces them ahead of the editorial read.