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[[{“value”:”Gemini 4 Argon is Google’s new frontier model, and the most interesting part isn’t the benchmarks: it’s a 1 million token output limit in a single response, up from 64K in earlier Gemini models. In this video I go through Argon’s official benchmarks, Arena’s cost-per-task testing, pricing, and what a million-token output means for test-time compute and long-running reasoning.
Gemini 4 Argon isn’t publicly available yet. It’s rolling out first to trusted testers through Google’s Fairwind program, with paid API customers and Google AI Ultra next.
Sources:
Google, Gemini 4 Argon announcement: https://blog.google/innovation-and-ai/models-and-research/gemini-models/gemini-4-argon/
Google DeepMind, Argon evaluation methodology: https://deepmind.google/models/evals-methodology/gemini-4-argon
Arena, cost per task results: https://x.com/arena/status/2105449871671173257
Arena Agent leaderboard (Pareto view): https://arena.ai/leaderboard/agent
Vals Index: https://www.vals.ai/benchmarks/vals_index
Zapier AutomationBench: https://zapier.com/benchmarks
CWE-bench: https://cwe-bench.com/?v=v1
Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters (UC Berkeley, Google DeepMind): https://arxiv.org/abs/2408.03314
Gemini 1.5 announcement (1M context): https://blog.google/technology/ai/google-gemini-next-generation-model-february-2024/
Gemini 1.0 announcement (natively multimodal): https://blog.google/technology/ai/google-gemini-ai/
Fairwind Program: https://deepmind.google/fairwind-program/
Claude pricing (for the Sonnet 5.5 / Opus 5.5 comparison): https://platform.claude.com/docs/en/about-claude/pricing
#Gemini4 #GeminiArgon #GoogleDeepMind #LLM #AI
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Chapters:
0:00 Gemini 4 Argon is here
0:52 Benchmarks: Arena cost per task and the Pareto frontier
1:39 Enterprise knowledge work: Vals Index and AutomationBench
2:22 Coding: DeepSWE and Google’s Rust migrations
3:10 Cybersecurity defense: CWE-bench
3:24 The 1M output token limit
4:08 Why it matters: test-time compute
5:12 Paper: small models that think longer vs 14x larger models
6:48 Fun fact and final thoughts”}]] Read More Prompt Engineering
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