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Compare models

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

  1. GPT-6.1 SolOpenAIRemove
  2. Perceptron Mk1.5PerceptronRemove
  3. Gemini 3.5 TranscribeGoogleRemove
  4. Claude Opus 5.5AnthropicRemove

4 is the maximum. Remove one to add another.

gpt-6.1-sol vs perceptron-mk1.5 vs gemini-3.5-transcribe vs claude-opus-5.5
AttributeGPT-6.1 Solgpt-6.1-solPerceptron Mk1.5perceptron-mk1.5Gemini 3.5 Transcribegemini-3.5-transcribeClaude Opus 5.5claude-opus-5.5
Pricing
Input$2.00 / 1M$0.15 / 1M$0 / 1M$4.00 / 1M
Output$10.00 / 1M$1.50 / 1M$0 / 1M$20.00 / 1M
Cache Write (5m)$2.00 / 1M$0.15 / 1MNot applicable$5.00 / 1M
Cache Write (1h)$2.00 / 1M$0.15 / 1MNot applicable$8.00 / 1M
Cache Read$2.00 / 1M$0.15 / 1MNot applicable$0.40 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M36.9K98.3K1M
Max outputN/AN/AN/AN/A
Capabilities
VisionYesNoYesYes
Function CallingYesNoYesYes
JSON ModeYesNoNoYes
StreamingYesYesNoYes
Catalogue
ProviderOpenAIPerceptronGoogleAnthropic
Categorychatchatvoicechat
Charge typePay As You GoPay As You GoPay As You GoPay As You Go
Released—2026-09-252026-09-25—
Description
SummaryGPT-6.1 Sol is an upgraded high-end model in OpenAI's GPT-6 series, positioned below the flagship GPT-6 Astra. It is optimized for agentic coding, computer use, document-heavy professional work, and multi-step business automation, delivering near-Astra-level capability at significantly lower cost. Compared with GPT-6 Sol, it offers improved factual reliability and stronger adherence to explicit constraints and user intent, making it well suited for complex, long-running agentic workflows where accurate and dependable execution is critical.Perceptron Mk1.5 chat model that accepts audio input. Audio and text input are billed per token.Google Gemini 3.5 Transcribe speech-to-text. Billed per input and output token.Claude Opus 5.5 is Anthropic's flagship model for advanced reasoning, coding, and long-horizon agentic workflows, succeeding Opus 5. It excels at multi-step changes across large codebases, code review and bug detection, financial and scientific analysis, and understanding dense charts, diagrams, and screenshots, with stronger grounding when reporting figures and citing sources. Compared with Opus 5, it completes comparable tasks with fewer steps and lower token usage while providing clearer, more concise progress reporting. With adaptive thinking and configurable effort levels, Opus 5.5 can balance reasoning depth, latency, and cost, making it well suited for both demanding autonomous workflows and latency-sensitive professional tasks.