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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 AstraOpenAIRemove
  2. Muse Glimmer 30BMetaRemove
  3. Grok 4.7SpaceXAIRemove
gpt-6-astra vs muse-glimmer-30b vs grok-4.7
AttributeGPT-6 Astragpt-6-astraMuse Glimmer 30Bmuse-glimmer-30bGrok 4.7grok-4.7
Pricing
Input$10.00 / 1M$0.35 / 1M$1.60 / 1M
Output$50.00 / 1M$1.50 / 1M$4.80 / 1M
Cache Write (5m)$10.00 / 1M$0.35 / 1M$1.60 / 1M
Cache Write (1h)$10.00 / 1M$0.35 / 1M$1.60 / 1M
Cache Read$10.00 / 1M$0.35 / 1M$1.60 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M131K500K
Max outputN/AN/AN/A
Capabilities
VisionYesYesYes
Function CallingYesYesYes
JSON ModeYesYesYes
StreamingYesYesYes
Catalogue
ProviderOpenAIMetaSpaceXAI
Categorychatchatchat
Charge typePay As You GoPay As You GoPay As You Go
Released———
Description
SummaryGPT-6 Astra is OpenAI's flagship model for demanding end-to-end professional work, designed for advanced analysis, software engineering, deep research, scientific tasks, and document creation. It is particularly strong in long-horizon agentic workflows, including tasks that require sustained reasoning, tool orchestration, and computer and browser use, making it well suited for complex autonomous workflows and production-grade knowledge work.Muse Glimmer 30B is a dense, open-weight multimodal model from Meta Superintelligence Labs, distilled from Muse Spark and optimized for autonomous agents on consumer hardware. It combines strong multi-step reasoning, reliable tool use, failure recovery, image understanding, and multilingual support across 100+ languages. Designed for long-horizon agentic and coding workflows, Muse Glimmer 30B offers a practical balance of capability and deployment efficiency, making it well suited for local coding assistants, multimodal agents, and production workflows that require sustained autonomous execution.Grok 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.