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Model Comparison

KAT-Coder-Pro V2.5 vs Qwen2.5 Coder 32B InstructWhich Is Better in 2026?

KwaiPilot•Qwen2.5 Coder 32B Instruct logoQwen

KAT-Coder-Pro V2.5 vs Qwen2.5 Coder 32B Instruct: which should you choose in 2026?

KAT-Coder-Pro V2.5 (by KwaiPilot) and Qwen2.5 Coder 32B Instruct (by Qwen) are compared below. Here is how they stack up on benchmarks, price, and capabilities, and which one to pick in 2026.

There are not enough shared, protocol-compatible benchmark results to declare a performance leader.

Qwen2.5 Coder 32B Instruct is about 1.7× cheaper on a blended 3:1 input/output basis ($0.745 vs $1.30 per 1M tokens).

KAT-Coder-Pro V2.5 has the larger context window (256,000 tokens vs 32,768 tokens).

Choose KAT-Coder-Pro V2.5 if…

  • • you work with longer documents, transcripts, or codebases

Choose Qwen2.5 Coder 32B Instruct if…

  • • lower blended API cost matters for your workload

The benchmark count includes only results measured with a matching benchmark version and protocol. Arena scores are shown separately. Missing, preliminary, and incompatible data is not treated as a controlled win. Published point-score comparisons are labeled separately when protocol details are incomplete. For text-output models, the verdict also compares token pricing and context windows.

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Performance benchmarks

Every value links to its source. A dash means that no reviewed result is available for that exact model and protocol.

KAT-Coder-Pro V2.5 and Qwen2.5 Coder 32B Instruct benchmark results
BenchmarkKAT-Coder-Pro V2.5Qwen2.5 Coder 32B Instruct
AutomationBench-AA

A 657-task benchmark of multi-step work across simulated SaaS applications in six business domains. The Artificial Analysis protocol reports a guardrail-aware score and is distinct from both the public Zapier split and the unrelated dynamic AutoBench framework.

Guardrail-aware score

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BrowseComp

A benchmark of difficult, verifiable information-seeking questions designed to measure an agent's ability to locate hard-to-find facts through web browsing.

Accuracy

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OSWorld-Verified

A verified computer-use benchmark in which multimodal agents operate desktop applications and are graded from the resulting environment state.

Mean task reward

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SWE-Bench Verified

A human-validated subset of real GitHub issues used to measure whether a coding agent can produce repository patches that resolve the associated tests.

Resolved

—
9.0%
SWE-bench
Terminal-Bench 2.1

Version 2.1 of the benchmark for completing realistic tasks in terminal environments. Harness, resource limits, and attempt count are part of the protocol.

Mean task success

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AutoBench

A dynamic LLM evaluation framework in which models generate questions, answer them, and participate in reciprocal peer assessment. AutoBench is distinct from Zapier's AutomationBench.

Weighted peer-assessment score

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GPQA Diamond

The highest-quality subset of Graduate-Level Google-Proof Q&A, designed to test expert-level scientific reasoning in biology, physics, and chemistry.

Accuracy

——
Humanity's Last Exam

A 2,500-question expert-level benchmark spanning dozens of academic fields. Tool-assisted and no-tools results are separate protocols and must not be merged.

Accuracy

——

Benchmark sources

Reviewed evidence last updated 2026-08-09.

Pricing, capabilities, and model facts

KAT-Coder-Pro V2.5 and Qwen2.5 Coder 32B Instruct model facts
FeatureKAT-Coder-Pro V2.5Qwen2.5 Coder 32B Instruct
Context & model facts
DeveloperKwaiPilotQwen
API providerKwaipilotQwen2.5 Coder 32B Instruct
Input context256,000 tokens32,768 tokens
Maximum output80,000 tokens32,768 tokens
Released——
Added to WritingmateJul 10, 2026Nov 11, 2024
LicenseNot availableNot available
Knowledge cutoff—2024-06-30
Capabilities
InputsTextText
OutputsTextText
Provider endpoint accepts tool parametersYesNo
ReasoningNoNo
VisionNoNo
Image GenerationNoNo
Video GenerationNoNo
API pricing
Input (per 1M tokens)$0.74$0.66
Output (per 1M tokens)$2.96$1.00
Blended 3:1 input/output$1.30$0.745
API performance
p95 latencyNot measuredNot measured
Output throughputNot measuredNot measured
Writingmate shows API performance only when both models have enough observations from the same measurement window, prompt profile, and provider. Third-party latency values are not copied into this table.

Data sources

  • Writingmate model catalog (pricing, limits, and availability)

Catalog data last updated Jul 10, 2026.

Why Pay for Multiple Subscriptions?

Comparing KAT-Coder-Pro V2.5 from KwaiPilot with Qwen2.5 Coder 32B Instruct from Qwen? Instead of managing separate API keys and subscriptions, get both with Writingmate.

Subscription-plan access for KAT-Coder-Pro V2.5 and Qwen2.5 Coder 32B Instruct
PlanPriceKAT-Coder-Pro V2.5Qwen2.5 Coder 32B InstructAI ImagesAI Video
Writingmate Pro
Most popular
$20/moIncludedIncludedNano Banana Pro, FLUX.2, DALL-E & moreSora 2, VEO 3.1
Writingmate Ultimate
Power users
$60/moIncludedIncludedNano Banana Pro, FLUX.2, DALL-E & moreSora 2, VEO 3.1
View Plans & Pricing

KAT-Coder-Pro V2.5 vs Qwen2.5 Coder 32B Instruct FAQ

Which is better, KAT-Coder-Pro V2.5 or Qwen2.5 Coder 32B Instruct?

There are not enough shared, protocol-compatible benchmark results to declare a performance leader. Qwen2.5 Coder 32B Instruct is about 1.7× cheaper on a blended 3:1 input/output basis ($0.745 vs $1.30 per 1M tokens). KAT-Coder-Pro V2.5 has the larger context window (256,000 tokens vs 32,768 tokens).

Which model is cheaper to use through an API?

Qwen2.5 Coder 32B Instruct is about 1.7× cheaper on a blended 3:1 input/output basis ($0.745 vs $1.30 per 1M tokens).

Which model supports more context?

KAT-Coder-Pro V2.5 has the larger context window (256,000 tokens vs 32,768 tokens).

Can I switch between KAT-Coder-Pro V2.5 and Qwen2.5 Coder 32B Instruct?

Yes. Use the model selector on this page to open any current Writingmate model comparison. You can also run the same prompt with both models in Writingmate.