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  "slug": "new-models-builders-menu",
  "edition": "2026-10-25T00",
  "url": "https://hangingcontext.com/stories/2026-10-25/new-models-builders-menu/",
  "newsroom": "artificial-intelligence",
  "beat": "models-labs",
  "newsroom_title": "Artificial Intelligence",
  "angle": "Gemini 4 Argon, MiniMax M3.1 Flash, and diffusion models give builders three different cost curves.",
  "headline": "The Model Menu Grows: A Frontier Showcase, a Faster Flash Model, and Cheaper Diffusion",
  "dek": "Google's Gemini 4 Argon builders, SambaNova's MiniMax M3.1 Flash, and a diffusion-model study show new models arriving with very different price and speed trade-offs.",
  "published_at": "2026-10-25T00:40:28Z",
  "labels": {
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    "trust_text": "Confirmed · 3 sources",
    "newsroom": "Artificial Intelligence"
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      "text": "Google released Gemini 4 Argon, a frontier model rolled out broadly last week, available via API in AI Studio and to Ultra and Pro subscribers in the Gemini app.",
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      "text": "MiniMax M3.1 Flash is 3 times faster than its predecessor and reduces usage costs by 70%, with input tokens at 0.30 dollars per million and output at 1.20 dollars per million, according to SambaNova.",
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      "text": "In a preprint, diffusion language models spend more computation on novel, rare, or incorrect outputs, and weighting candidate answers by decoding speed beats majority voting by up to 4.2 points.",
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  "sections": [
    {
      "heading": "What builders made with Gemini 4 Argon",
      "paragraphs": [
        {
          "markdown": "Google says it released a new frontier model called Gemini 4 Argon, designed for complex tasks in coding, finance, legal, cybersecurity, and science, and rolled out broadly last week, with access for developers and enterprises through the API in AI Studio and for subscribers through the Gemini app.",
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          "markdown": "The company's showcase of five builders gives a concrete picture of early use: one builder rendered a 3D simulation of a seaplane, another built an interactive 3D globe from NASA and USGS data, a third modeled a jet engine with Blender and Three.js, a fourth built a 3D carriage from a single image, and a fifth built a multiplayer browser game called Backyard Rascals.",
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          "markdown": "Google says the model outperforms other frontier models on benchmarks across domains, a company claim that builders will have to test against their own workloads, since the showcase emphasizes 3D and interactive builds rather than the finance, legal, and cybersecurity tasks the model is also designed to handle.",
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    {
      "heading": "MiniMax M3.1 Flash: faster, cheaper, benchmarked",
      "paragraphs": [
        {
          "markdown": "SambaNova says MiniMax M3.1 Flash is now available on SambaCloud, delivering over 200 tokens per second, running 3 times faster than its predecessor while reducing usage costs by 70 percent, with existing MiniMax M3 traffic on the platform being rerouted to the new model.",
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          "markdown": "The benchmark scores SambaNova reports span coding, agentic, and tool-use tasks: 73.7 percent on DeepSWE version 1.1, 82 percent on CyberGym, 61.7 on OSWorld version 2, 76.2 on BankerToolBench, and 29.6 on Agents' Last Exam, a spread that suggests the model is stronger on some agentic benchmarks than others rather than uniformly ahead.",
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          "markdown": "Pricing is explicit: cached input tokens cost 0.03 dollars per million tokens, regular input tokens cost 0.30 dollars per million, and output tokens cost 1.20 dollars per million, which gives builders a clear arithmetic for comparing the flash model against frontier models on tasks where speed matters more than peak capability.",
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    {
      "heading": "Diffusion models: cost depends on what you ask",
      "paragraphs": [
        {
          "markdown": "A preprint study of diffusion language models adds a different kind of cost curve: these models can write several tokens in one forward pass, but the number of forward passes per token depends heavily on the task, with highly tokenized languages requiring more passes per token than others.",
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        {
          "markdown": "The study finds that diffusion models spend more computation on novel, rare, or incorrect outputs, that text copied or lightly edited from the input is cheaper to generate than open-ended writing, and that generating a token for story writing in DiffusionGemma requires more than three times as many forward passes as for grammar correction.",
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          "markdown": "Two practical findings follow for builders: wrong answers on math problems take more passes per token than correct ones, and weighting candidate answers by decoding speed beats majority voting by up to 4.2 points, which means decoding speed itself carries signal about answer quality in these models.",
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    },
    {
      "heading": "Three cost curves, one choice",
      "paragraphs": [
        {
          "markdown": "The three model stories share a question but give different answers: Gemini 4 Argon offers a frontier showcase through an API and subscription apps, MiniMax M3.1 Flash offers measured speed and explicit token prices, and diffusion models offer a cost that varies with the task itself, so the right model depends on whether the work is showcase, throughput, or task-sensitive generation.",
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          "markdown": "Benchmarks alone do not settle the choice: Google says its model outperforms other frontier models across domains, SambaNova reports a spread of scores across agentic benchmarks, and the diffusion study shows decoding speed itself beating majority voting, which means builders need their own workload measurements alongside vendor numbers.",
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  "unresolved": [
    "Independent benchmark results for Gemini 4 Argon and MiniMax M3.1 Flash",
    "Whether diffusion models' speed signal generalizes beyond the studied models"
  ],
  "decision_card": {
    "useful_for": [
      "Choosing between a frontier model, a flash model, and a diffusion model",
      "Estimating inference cost per task"
    ],
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      "title": "See what 5 builders are making with Gemini 4 Argon",
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      "published_date": "2026-10-23"
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      "title": "MiniMax M3.1 Flash Now Available on SambaCloud",
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      "published_date": "2026-10-24"
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      "title": "Diffusion Language Models Change Speed Across Tasks and Languages",
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      "url": "https://hangingcontext.com/stories/2026-10-24/open-weight-agentic-race/",
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      "headline": "Diffusion-model compute patterns, time-aware quantization, TensorRT tuning, and FP8 kernels all allocate precision where it pays",
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