六款前沿模型性价比对比：Gemini 4 Argon 被列为「未知数」
作者把 Claude Opus 5.5、GPT-6 Astra、Gemini 4 Argon 等六款模型按 BenchLM 分数、每百万 token 价格和单次 agent 会话成本做成一张 HTML 对比表，Argon 因输入价未公布只能给出 80.5 的估算分（区间 70.8–90.3）。
6 frontier models. 1 board. the #1 is not the one you should run all day i put the october top of the leaderboard on one glass desk: BenchLM overall score, list price per 1M tokens, score per dollar and what one agent session actually costs. MODEL ARENA, one html, no keys, no backend the idea: pick a model like you pick a crew. each one has one job meet the crew: 1. CLAUDE OPUS 5.5 · the closer: 85.4, #1 overall · $4 in / $20 out · 1M context · one session (1M in + 200K out) = $8.00 2. GPT-6 ASTRA · the heavyweight: 83.3 · $10 / $50 · 1.05M context · same session = $20.00 · 1.67 points per $ of output 3. CLAUDE SONNET 5.5 · the workhorse: 82.5 · $2 / $10 · 8.25 points per $, best on the board · session = $4.00 4. GPT-6.1 SOL · the twin: 81.6 · same $2 / $10 as Sonnet · 0.9 behind · 8.16 points per $ 5. CLAUDE FABLE 5.1 · the specialist: 81.2 · $10 / $50, Astra-level bill for the #5 score · 1.62 points per $ 6. GEMINI 4 ARGON · the wildcard: 80.5 but estimated, range 70.8–90.3 · $10 out · input price not published the split that matters: two models at $50 output, four at $10–20. the whole board sits inside 4.9 points of score. output price across it spans 5×, $10 → $50 alone each model is a benchmark row. together they're a routing table: closer for the hard merge, workhorse for the 200 small tasks, twin as the fallback, wildcard when the estimate firms up the novelty is not who's #1. the novelty is that #3 does 97% of the #1 score for half the price data: BenchLM frontier top 10 + provider pricing verified 8 oct · list prices, no cache, no batch bookmark this before your agent bill teaches you the same table the hard way edge is open until everyone else stops running the #1 model on every task