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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. Qwen3.8 2.4T A95BAlibabaRemove
  2. GPT-6 LunaOpenAIRemove
  3. Grok 4.7SpaceXAIRemove
qwen3.8-2.4t-a95b vs gpt-6-luna vs grok-4.7
AttributeQwen3.8 2.4T A95Bqwen3.8-2.4t-a95bGPT-6 Lunagpt-6-lunaGrok 4.7grok-4.7
Pricing
Input$1.80 / 1M$0.10 / 1M$1.60 / 1M
Output$5.40 / 1M$0.50 / 1M$4.80 / 1M
Cache Write (5m)$1.80 / 1M$0.10 / 1M$1.60 / 1M
Cache Write (1h)$1.80 / 1M$0.10 / 1M$1.60 / 1M
Cache Read$1.80 / 1M$0.10 / 1M$1.60 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max context262K1.1M500K
Max outputN/AN/AN/A
Capabilities
VisionYesYesYes
Function CallingYesYesYes
JSON ModeYesYesYes
StreamingYesYesYes
Catalogue
ProviderAlibabaOpenAISpaceXAI
Categorychatchatchat
Charge typePay As You GoPay As You GoPay As You Go
Released———
Description
SummaryQwen3.8 2.4T A95B is Qwen's open-weight sparse Mixture-of-Experts (MoE) model and the open-weight counterpart to Qwen3.8 Max. It features 2.4T total parameters with 95B activated per token, combining frontier-scale capacity with efficient sparse inference. Designed for coding, research, complex reasoning, and agentic workflows, the model is well suited for demanding long-horizon tasks and advanced autonomous systems while providing the flexibility and customization benefits of open weights.GPT-6 Luna is the fast, cost-efficient model in OpenAI's GPT-6 series, optimized for high-volume and latency-sensitive workloads such as chat, classification, and lightweight agentic tasks. It combines low-cost, responsive inference with the GPT-6 family’s improvements in factual reliability and clear, concise communication. At higher reasoning effort, GPT-6 Luna can also handle complex software engineering and computer-use workflows that previously required a Sol-tier model, making it a versatile choice for scalable production applications that need to balance speed, cost, and capability.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.