필터 결과
18개정렬
38:02EN
Theo - t3․gg· 2026년 10월 13일Meta’s Muse Wonder Full: A Coding Agent Tested Against Opus and SolTheo Browne · Ping LabsTheo Browne tests Meta’s new model on code review, debugging, delegation and benchmarks, finding promising strengths alongside important limits.
18:18ENTheo - t3․gg· 2026년 10월 12일Why AI Bills Can Rise as Intelligence Gets CheaperTheo Browne · Ping LabsTheo Browne explains the difference between token prices, task costs and capability, and why more useful agents can still drive larger bills.
41:10ENTheo - t3․gg· 2026년 10월 9일Haiku 5.5: Where a Cheaper Small Model Helps Coding AgentsTheo Browne · Ping LabsTheo Browne examines Haiku 5.5 pricing, benchmark results and practical tests, including a failed pull-request audit.
33:33ENTheo - t3․gg· 2026년 10월 7일Is the $200 Codex Plan Still Worth It?Theo Browne · Ping LabsTheo Browne compares subscription usage, API-equivalent estimates, model efficiency and the cost of Ultrafast.
27:29ENTheo - t3․gg· 2026년 9월 27일What Pacing the AI Frontier Could Mean for Model ReleasesTheo Browne · T3Theo argues that releasing more reliable and affordable models can be compatible with slowing the advance of the most dangerous capabilities.
0:31ENTheo - t3․gg· 2026년 9월 24일Grok 4.7’s Token Use and the Claims Around Its ReleaseTheo Browne · T3Theo compares Elon Musk’s earlier predictions for Grok 4.7 with selected benchmark results and token counts.
0:22ENTheo - t3․gg· 2026년 9월 12일Theo’s Take on GPT-6 Astra: A Next-Generation Model With Rough EdgesTheoTheo praises the model across coding and other tasks while warning that it can still over-engineer and get stuck in loops.
1:16:51ENTheo - t3․gg· 2026년 9월 11일Fable 5.1 vs GPT-6 Astra: Theo on Coding, Computer Use and CostTheoTheo compares the models through coding projects, 3D demos and agent workflows, and explains why he uses each for different jobs.
44:12ENTheo - t3․gg· 2026년 9월 4일GPT-6 Astra: Theo’s Early Tests of Computer Use, 3D and CodingTheoTheo reviews launch-era pricing and benchmarks, shows projects built with the model, and recounts a frustrating PR-review failure.
55:06ENTheo - t3․gg· 2026년 9월 3일Fable 5.1 in Practice: Theo on Costs, Agent Workflows and PR QualityTheoTheo reviews the launch, prompting guidance and his early coding experiments, including an observational comparison of pull requests.
0:24ENTheo - t3․gg· 2026년 9월 1일Theo’s Interpretation of OpenAI’s Decision on Cursor and AstraTheoTheo connects the end of the partnership to concerns about model distillation and access to Astra.
0:18ENTheo - t3․gg· 2026년 8월 14일Theo Discusses Elon Musk’s Grok 4.7 PreviewTheo Browne · Ping LabsTheo reacts to Musk’s August 2026 claims about the next Grok model, its training and an expected release window.
0:33ENTheo - t3․gg· 2026년 7월 10일Three Eras of AI Coding Agents: Tool Calls, Long Tasks, and OrchestrationTheo Browne · Ping LabsTheo Browne uses three model releases to explain how he sees coding agents developing.
24:43ENTheo - t3․gg· 2026년 7월 9일Grok 4.5 for Coding: Theo’s Benchmarks and Early ExperienceTheo Browne · Ping LabsTheo Browne examines Grok 4.5’s cost, benchmark caveats, coding work and 3D experiments after early access in Cursor.
0:37ENTheo - t3․gg· 2026년 6월 16일Theo Criticizes Fable 5 Access and Benchmark RestrictionsTheoTheo points to restricted access, fallback models and refusals in one coding benchmark as reasons for concern about Anthropic's Fable release.
0:45ENTheo - t3․gg· 2026년 6월 15일Theo’s Explanation of Fable 5 and Mythos 5TheoTheo uses a two-door analogy to explain what he sees as the difference between the two Anthropic model offerings.
37:30ENTheo - t3․gg· 2026년 5월 24일Cursor Composer 2.5: Speed, Coding Benchmarks, and the Limits of EvaluationTheo Browne · T3Theo examines Cursor’s coding model, its training methods, practical performance, and the difficulty of independent testing.
41:11ENTheo - t3․gg· 2026년 5월 5일Theo and ThePrimeagen on AI Subscriptions, Compute and Model EconomicsTheo Browne, ThePrimeagen, Dario Amodei · Ping LabsA discussion of usage limits, training costs and why the price of a token differs from the cost of useful work.