NewPoint any agent at UberLLM — one key, every model, list price or less.

Trinity Large Thinking vs DeepSeek V4 Flash

arcee-ai/trinity-large-thinking · deepseek/deepseek-v4-flash

As of October 31, 2026, DeepSeek V4 Flash is the cheaper API on UberLLM: $0.0414 per million input tokens and $0.0828 per million output, versus $0.2344 / $0.8438 for Trinity Large Thinking, about 90% less when output is 3 tokens for every input token. These are the median prices buyers paid over the last 24 hours. Both work with one OpenAI-compatible key and UberLLM adds no fee. Choose DeepSeek V4 Flash to cut cost; choose Trinity Large Thinking when its capabilities fit your task better.

Trinity Large Thinking vs DeepSeek V4 Flash, side by side

SpecTrinity Large ThinkingDeepSeek V4 Flash
Price · input / 1M$0.2344$0.0414
Price · output / 1M$0.8438$0.0828
Context length256,0001,000,000
Max output tokens32,768128,000
Input modalitiestexttext
Output modalitiestexttext
Tools / functionsYesYes
ReasoningYesYes
% off list22% off55% off

Median prices buyers paid on UberLLM over the last 24 hours. No UberLLM fee on requests; adding credit by card costs 5.5% + $0.50. Updated October 31, 2026.

Trinity Large Thinking vs DeepSeek V4 Flash — FAQ

Is Trinity Large Thinking or DeepSeek V4 Flash cheaper?

DeepSeek V4 Flash is cheaper on a blended token mix, by about 90%. A request costs what its provider charged, UberLLM adds no fee, and every request is listed with its cost in Activity.

What's the price difference between Trinity Large Thinking and DeepSeek V4 Flash?

Trinity Large Thinking: $0.2344 in / $0.8438 out per 1M tokens. DeepSeek V4 Flash: $0.0414 in / $0.0828 out per 1M tokens. That's roughly a 90% blended difference. Prices are live; UberLLM adds no fee.

Can I use both Trinity Large Thinking and DeepSeek V4 Flash with one API?

Yes. Both are served through a single OpenAI-compatible endpoint — set the base URL to https://api.uberllm.dev/v1 and your UberLLM key, then switch between them by changing the model id. Anthropic SDKs work via https://api.uberllm.dev/v1/messages.

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