Unverified50% confidenceEventExact time
With a 128K context window, the uploader demonstrated the ability to handle a 50,000+ token session, with the terminal showing about 51,000 tokens used and the model still generating responses stably.
1
Sources
50%
Confidence
Short-term (~14 days)
Relevance
10/22/2026
First Seen
Valid until: 11/5/2026
Sources
Liquid AI LFM2.5-24B Tested on Mac mini M6: 70 TPS and 128K Context
bilibili安得广厦千万间67810/18/2026
Related Entities
Related Claims
UnverifiedIn computer use, the system prompt adds 466–499 tokens, each tool definition adds 735 tokens, and each screenshot consumes roughly 2,000–5,000 tokens.75% similarUnverifiedA 200K token context request requires approximately 25× the KV-Cache memory compared to an 8K token request.70% similarUnverifiedThe embedding model's maximum length means that inputs exceeding 512 tokens are silently truncated, so the example sets the chunk budget to 480 tokens.69% similarUnverifiedThe UP host estimates that inference speed could improve to 30–40 tokens/s after using a GPU with 50GB of VRAM (not confirmed through actual testing).69% similarUnverifiedUnder a single-request serial load, each request decodes at 648–649 tokens/s, and the whole server produces 589–593 tokens/s.69% similar
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