AI Models · Paid vs Paid

GPT-6 Astra Pro (batch) Paid vs KWKAT-Coder-Pro V2 Paid

GPT-6 Astra Pro (batch) vs KAT-Coder-Pro V2 compared — price per token, context window, multimodality, openness and which to choose. Full 2026 breakdown.

Prices & specs refreshed from live data · olud.ai

Open-model prices = cheapest provider via OpenRouter; official maker rates may be higher.

GPT-6 Astra Pro (batch)PaidOpenAI
$5 /M input
$25 /M outputManaged API (no infra to run)
TypeProprietary
Context window1.1M tokens
MultimodalYes
Self-hostNo
KWKAT-Coder-Pro V2PaidKwaipilot
$0.3 /M input
$1.2 /M outputManaged API (no infra to run)
TypeProprietary
Context window262K tokens
MultimodalNo
Self-hostNo
Choose KAT-Coder-Pro V2 for the lower output price ($1.2/M vs $25/M). Choose GPT-6 Astra Pro (batch) if you need the larger 1.1M context window.

GPT-6 Astra Pro (batch) vs KAT-Coder-Pro V2 specs

SpecGPT-6 Astra Pro (batch)KAT-Coder-Pro V2Winner
MakerOpenAIKwaipilot
TypeProprietaryProprietary
Context window1.1M tokens262K tokensGPT-6 Astra Pro (batch)
Input price$5/M$0.3/MKWKAT-Coder-Pro V2
Output price$25/M$1.2/MKWKAT-Coder-Pro V2
Vision / multimodalYesNoGPT-6 Astra Pro (batch)
Tool / function callingYesYes= Tie
Self-hostableNo (API only)No (API only)
LicenseProprietaryProprietary

Price gap & when to choose each

21×cheaper per output token

KAT-Coder-Pro V2 is ~21× cheaper than GPT-6 Astra Pro (batch) on output tokens ($1.2 vs $25 per M tokens).

Choose GPT-6 Astra Pro (batch) if…
  • You want frontier performance through a managed API
  • You need the longer 1.1M context window
  • You value reliability & ecosystem
  • You don't want to manage infrastructure
KWChoose KAT-Coder-Pro V2 if…
  • You want frontier performance through a managed API
  • You want the lower output price
  • You value reliability & ecosystem
  • You don't want to manage infrastructure

Feature comparison

CapabilityGPT-6 Astra Pro (batch)KAT-Coder-Pro V2
Open weights (downloadable)
Self-hostable
Runs fully offline
Vision / multimodal
Tool / function calling
1M+ context window

Benchmarks: GPT-6 Astra Pro (batch) vs KAT-Coder-Pro V2

Independent benchmark scores measured by Artificial Analysis. Higher is better (except latency).

GPT-6 Astra Pro (batch)
KAT-Coder-Pro V2
Intelligence index
21.7
Coding index
59.5
GPQA
85.5%
Humanity's Last Exam
16.1%
Long Context Reasoning
73%
IFBench
66.7%
τ²-Bench
89.5%
τ-Bench Banking
4.5%
Terminal-Bench
70%
Terminal-Bench Hard
49.2%
Speed
0 tok/s
Latency
0s
Intelligence per $
41.3

Benchmark data by Artificial Analysis.

How GPT-6 Astra Pro (batch) and KAT-Coder-Pro V2 score

🤝 Neck and neck on these criteria (3.1 vs 2.9 / 5).
CriterionGPT-6 Astra Pro (batch)KAT-Coder-Pro V2
Cost-efficiency3.04.5
Context window5.04.0
Openness1.51.5
Self-hosting1.01.0
Multimodality5.03.5

Scores come from live data — output price (cost), context length, open vs closed weights (openness & self-hosting) and vision/tool support (multimodality). Raw task quality isn't scored here; it depends on your benchmark — see the verdict.

What each model is

GPT-6 Astra Pro (batch) Paid

OpenAI · Proprietary

GPT-6 Astra Pro is the same underlying model as [GPT-6 Astra](https://openrouter.ai/openai/gpt-6-astra), served with `reasoning.mode` set to `pro` for higher-quality responses on complex tasks. Learn more in OpenAI's docs: https://develope

KAT-Coder-Pro V2 Paid

Kwaipilot · Proprietary

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,...

Frequently asked questions

GPT-6 Astra Pro (batch) vs KAT-Coder-Pro V2 — which is cheaper?

KAT-Coder-Pro V2 is cheaper on output ($1.2/M vs $25/M).

Which has the larger context window?

GPT-6 Astra Pro (batch) offers the larger context window (1.1M tokens).

GPT-6 Astra Pro (batch) vs KAT-Coder-Pro V2 — which should I pick in 2026?

Choose KAT-Coder-Pro V2 for the lower output price ($1.2/M vs $25/M). Choose GPT-6 Astra Pro (batch) if you need the larger 1.1M context window.

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