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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. Grok 4.7SpaceXAIRemove
  2. Gemini 4 ArgonGoogleRemove
  3. GPT-6.1 TerraOpenAIRemove
grok-4.7 vs gemini-4-argon vs gpt-6.1-terra
AttributeGrok 4.7grok-4.7Gemini 4 Argongemini-4-argonGPT-6.1 Terragpt-6.1-terra
Pricing
Input$1.60 / 1M$2.00 / 1M$1.00 / 1M
Output$4.80 / 1M$10.00 / 1M$5.00 / 1M
Cache Write (5m)$1.60 / 1M$2.00 / 1M$1.00 / 1M
Cache Write (1h)$1.60 / 1M$2.00 / 1M$1.00 / 1M
Cache Read$1.60 / 1M$2.00 / 1M$1.00 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max context500K1M1M
Max outputN/AN/AN/A
Capabilities
VisionYesYesYes
Function CallingYesYesYes
JSON ModeYesYesYes
StreamingYesYesNo
Catalogue
ProviderSpaceXAIGoogleOpenAI
Categorychatchatchat
Charge typePay As You GoPay As You GoPay As You Go
Released———
Description
SummaryGrok 4.7 is SpaceXAI's flagship model for coding, agentic workflows, and professional knowledge work, succeeding Grok 4.6. It is particularly strong at long-running software engineering, self-verification, and long-context execution, while improving capabilities in document drafting, presentations, and other professional tasks. Trained with extended reinforcement learning focused on multi-hour problems, Grok 4.7 is optimized for sustained, complex task execution and natively supports the Grok Bot harness for conversational workflows. It also introduces an enhanced safeguard stack designed to combine strong jailbreak resistance with low refusal rates for legitimate technical work. Reported benchmark results use xhigh reasoning effort.Gemini 4 Argon is Google's flagship reasoning model, built for complex software engineering, deep mathematical and scientific problem solving, and autonomous multi-step agents. Google trained it to keep context across long, multi-step tasks and to turn long documents mixing text, tables, charts and images into a single grounded output. It leads the Vals Index across finance, legal, coding and tax work, and supports long decode of up to 1M output tokens in a single response.GPT-6.1 Terra is OpenAI’s mid-tier model in the GPT-6.1 series, designed to balance capability, speed, and cost efficiency. Positioned below GPT-6.1 Sol, it delivers strong performance across everyday agentic workflows, coding, and professional writing, with particular strengths in screenshot understanding and on-screen content analysis. Optimized for high-volume production workloads, GPT-6.1 Terra is well suited for coding assistants, visual interface analysis, workflow automation, and scalable agentic applications that require reliable performance at an accessible cost.