Model profile
KwaiKAT
New in 2026

Kwaipilot: KAT-Coder-Pro V2

Kwaipilot: KAT-Coder-Pro V2 is a budget-priced text-first model from KwaiKAT with balanced runtime profile, large context posture, and the clearest fit around long-context research / agent workflows.

Best for: Long-context research / Agent workflowsBalanced latencyLarge contextBudget pricing
Intelligence
43.8

Benchmark blend

Coding
45.6

Dev workflow signal

Context
256K Tokens

Large

Input Price
$0.30

Budget tier

Decision snapshot
61

Kwaipilot: KAT-Coder-Pro V2 currently reads as a budget text-first option with large context and a balanced runtime profile.

Overall profile
Selective fit
Best for
Long-context research / Agent workflows
Latency tier
Balanced
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
43.8
44

General reasoning and benchmark headroom.

Situational
Speed
99 tok/s
62

TTFT 2.02s

Competitive
Context
256K Tokens
88

How much prompt and task state can stay in view.

Above average
Price
$0.30
86

$1.20 output / 1M

Efficient

Editorial Profile

Kwaipilot: KAT-Coder-Pro V2 in one narrative

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

Selective fitCoding score 46Math score N/A

KAT-Coder-Pro V2 is the latest high-performance model in KwaiKAT’s KAT-Coder series, designed for complex enterprise-grade software engineering and SaaS integration. It builds on the agentic coding strengths of earlier versions, with a focus on large-scale production environments, multi-system coordination, and seamless integration across modern software stacks, while also supporting web aesthetics generation to produce production-grade landing pages and presentation decks.

Identity

KwaiKAT text-first profile

Positioning

Long-context research / Agent workflows with large context and balanced 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 is balanced rather than ultra-fast, which is fine for most workflows but not the snappiest tier.

  • 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.

Explore Next

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KwaiKAT

KAT-Coder-Pro V1

Intelligence
36.0
Context
N/A
Input Price
$0.30

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
43.8
GPQA
85.5%
HLE
16.0%
Coding

Software implementation, debugging quality, and coding benchmark signal.

Coding Index
45.6
SciCode
38.3%
Agent / tool use

Long-horizon execution quality and interactive benchmark evidence.

IFBench
66.7%
TAU2
89.5%
TerminalBench Hard
49.2%
LCR
66.0%

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
256K Tokens
Vision
Text-first
Modalities
text
Tokenizer
Other
Max Completion
80000
Moderation
No
Supported Parameters
frequency_penaltylogit_biasmax_tokensmin_ppresence_penaltyrepetition_penaltyresponse_formatseedstopstructured_outputstemperaturetool_choicetoolstop_ktop_p
Input Modalities
text
Output Modalities
text
Price architecture
Input
per 1M input tokens
$0.30
Output
per 1M output tokens
$1.20
Blended
AA 3:1 mix
$0.53

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.