Model decision surface

Compare AI models

Start with Qwen3.8 Flash and Grok 4.7, or choose any two current ranked language models. Compare capability evidence, price, context, provider availability, and weight access without pretending one field decides every use case.

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Current public data

Qwen3.8 Flash vs Grok 4.7

Live dataset updated 9/22/2026, 1:40:35 AM UTC

Open 1200×630 evidence receipt

Factual comparison of Qwen3.8 Flash and Grok 4.7
Field	Qwen3.8 Flash Qwen	Grok 4.7 xAI
ModelCap position	#17	#4
Index score	78.9	85.0
Evidence	Measured1 public benchmark observation across 1 board	Measured1 public benchmark observation across 1 board
Input / 1M	$0.15	$1.60
Output / 1M	$0.47	$4.80
Pricing status	fresh	fresh
Context	1M	500K
Providers	1	1
Weight access	Restricted license	API only

Decision facts

Qwen3.8 Flash is #17; Grok 4.7 is #4 on the same current language board.
Index scores are 78.9 for Qwen3.8 Flash and 85.0 for Grok 4.7. Their published uncertainty intervals overlap, so the rank difference alone does not establish a reliable capability advantage for your workload.
Both positions use Measured evidence.
Listed output price per 1M tokens is $0.47 for Qwen3.8 Flash and $4.80 for Grok 4.7. For 1,000 requests with 2,000 input and 500 output tokens each (2M input + 0.5M output), the listed-rate estimate is $0.53 for Qwen3.8 Flash versus $5.60 for Grok 4.7. Qwen3.8 Flash costs 90.4% less in this scenario. This excludes caching, batch discounts, prompt-length tiers, tool charges and retries; verify the selected endpoint before budgeting.
Published context is 1,000,000 tokens for Qwen3.8 Flash and 500,000 for Grok 4.7.
Weight access differs: Qwen3.8 Flash is restricted; Grok 4.7 is none.

These are separate published fields, not a synthetic winner. ModelCap does not collapse price, access, context, and capability evidence into a hidden recommendation score.

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