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Put up to 4 models beside each other — token prices, context windows, capabilities and provider, from the same catalogue the model pages read.

  1. Claude Opus 4.6 (Thinking)AnthropicRemove
  2. Perceptron Mk1.5PerceptronRemove
  3. GPT-6 Sol ProOpenAIRemove
claude-opus-4-6-thinking vs perceptron-mk1.5 vs gpt-6-sol-pro
AttributeClaude Opus 4.6 (Thinking)claude-opus-4-6-thinkingPerceptron Mk1.5perceptron-mk1.5GPT-6 Sol Progpt-6-sol-pro
Pricing
Input$4.00 / 1M$0.15 / 1M$2.00 / 1M
Output$20.00 / 1M$1.50 / 1M$10.00 / 1M
Cache Write (5m)$5.00 / 1M$0.15 / 1M$2.00 / 1M
Cache Write (1h)$8.00 / 1M$0.15 / 1M$2.00 / 1M
Cache Read$0.40 / 1M$0.15 / 1M$2.00 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M36.9K1.1M
Max outputN/AN/AN/A
Capabilities
VisionYesNoYes
Function CallingYesNoYes
JSON ModeYesNoYes
StreamingYesYesYes
Catalogue
ProviderAnthropicPerceptronOpenAI
Categorychatchatchat
Charge typePay As You GoPay As You GoPay As You Go
Released—2026-09-25—
Description
SummaryOpus 4.6 is Anthropic's most capable model for coding and long-running professional workflows, designed for agents that operate across entire workflows rather than single prompts. It demonstrates strong performance on large codebases, complex refactoring, and multi-step debugging, with improved contextual understanding, deeper problem decomposition, and higher reliability on challenging engineering tasks compared to earlier generations. Beyond software development, Opus 4.6 excels at sustained knowledge work, producing near production-ready documents, technical plans, and analyses in a single pass while maintaining coherence across long outputs and extended sessions. Its strength in persistence, judgment, and structured execution makes it well suited for technical design, migration planning, and end-to-end project execution.Perceptron Mk1.5 chat model that accepts audio input. Audio and text input are billed per token.GPT-6 Sol Pro uses the same underlying model as GPT-6 Sol, but runs with reasoning.mode set to pro for higher-quality responses on complex and demanding tasks. Optimized for deeper reasoning, greater accuracy, and more reliable multi-step execution, it is particularly well suited for agentic coding, long-horizon software engineering, professional analysis, and complex automated workflows where solution quality takes priority over latency and cost.