Hot take on what comes next, after the sudden decline of tokenmaxxing:
– OpenAI will struggle – with the decline of tokenmaxxing Anthropic will struggle (aside from this quarter) to make a profit – Google will catch up to Anthropic – some Chinese companies might, too
– LLMs
LLMS
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Hot take on AI companies after tokenmaxxing decline
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8B MoE Model Trained for Agentic Local Workflows
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8B MoE (1B Activated) trained on 38 trillion tokens for local and agentic workflows
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Jeremy Howard now using GPT-5.5, likes it nearly as much as Opus 4.6/4.7
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I've largely switched over to using GPT-5.5 in recent weeks, which I like nearly as much as Opus 4.6 and 4.7, and is *very* reasonably priced (since I can use my subscription with the @OpenAI API.)
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Anthropic criticized for failing to lower API costs
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Has @AnthropicAI completely given up on making API usage reasonably-priced? Following the token-usage changes recently they announced various updates to *subscription* usage to make it more reasonable. But they've done NOTHING for API users. The cost is insane at this point.
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Model 4.7 preferred but GPT 5.5 better value for price
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I still enjoyed 4.7. It remained my preferred model until today, although I liked GPT 5.5 nearly as much (and greatly preferred it when taking price into account, since it can be used with API at subscription pricing).
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Opus 4.8 more cooperative but still expensive
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Worked on some code this morning using Opus 4.8 and so far I'm really liking it. Much more cooperative than 4.7 and less "over agentic". Stops and asks for my input when needed in places 4.7 (and GPT 5.5) would just foolishly blast ahead. (Still WAY too expensive.)
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ChatLLM Smart Model Router for Task-Specific AI Selection
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ChatLLM smartly routes to the best model based on your prompt Opus 4.8 – front-end
GPT 5.5 – back-end coding
Grok 4.5 – real-time
Flash 3.5 – chat Nano Banana Pro – image
Seedance 2.0 – video
ElevenLabs – voice
Gemini Pro 3.1 – research
DeepSeek Flash – simple We smartly -
Claude roleplays an economist and self-evaluates a paper
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Claude really can roleplay an economist. I love this little comment Claude made after some robustness checks on the paper it wrote: "On a 1–10 identification scale, I'd now put the paper at about 4.5 — better than the 3.5 I'd have given before these tests, but well short of
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GPT-5 Pro models leading single-shot performance
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Interesting that the GPT-5 Pro series models have consistently been the best models for single-shot attempts at the hardest problems since last summer. There has been no real competition in all that time.
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Step 3.7 Flash MoE Model with 256K Context Released
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Step 3.7 Flash is here ICYMI: 198B MoE with 11B active params, 256K context, native image + video support. Day 0 support is live on http://
build.nvidia.com with GPU-accelerated endpoints, deploy with NVIDIA NIM inference microservices, and fine-tune with the NVIDIA NeMo