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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. Muse Spark 1.3MetaRemove
  3. Qwen3 ASR 0.6BQwenRemove
  4. S2 ProFish AudioRemove

4 is the maximum. Remove one to add another.

grok-4.7 vs muse-spark-1.3 vs qwen3-asr-0.6b vs s2-pro
AttributeGrok 4.7grok-4.7Muse Spark 1.3muse-spark-1.3Qwen3 ASR 0.6Bqwen3-asr-0.6bS2 Pros2-pro
Pricing
Input$1.60 / 1M$1.25 / 1M$0 / 1M$0 / 1M
Output$4.80 / 1M$4.25 / 1M$0 / 1M$0 / 1M
Cache Write (5m)$1.60 / 1M$1.25 / 1MNot applicableNot applicable
Cache Write (1h)$1.60 / 1M$1.25 / 1MNot applicableNot applicable
Cache Read$1.60 / 1M$1.25 / 1MNot applicableNot applicable
Web Search$0 / 1M$0 / 1M$0 / 1M$0 / 1M
Context
Max context500K1MN/AN/A
Max outputN/AN/AN/AN/A
Capabilities
VisionYesYesNoNo
Function CallingYesYesNoNo
JSON ModeYesYesNoNo
StreamingYesYesNoNo
Catalogue
ProviderSpaceXAIMetaQwenFish Audio
Categorychatchatvoicevoice
Charge typePay As You GoPay As You GoPay As You GoPay As You Go
Released——2026-08-132026-07-29
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.Muse Spark 1.3 is Meta's multimodal reasoning model designed for long-running agentic, multi-agent, and coding workflows. It maintains context and information across extended tasks, enabling reliable execution in complex, multi-step environments. The model is optimized to resolve conflicting information, seek clarification or confirmation when necessary, and execute concisely, making it well suited for autonomous agents, collaborative multi-agent systems, and long-horizon software engineering workflows.Qwen3-ASR 0.6B speech-to-text. Billed per second of audio.Fish Audio S2 Pro text-to-speech. Billed per UTF-8 byte of input text.