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Gemini 4 Argon begins limited rollout to trusted cyber defenders

Google says Argon targets coding, enterprise work and cyber defense, with broader access planned after more safety testing.

AICodeKingAI
N. Taylor MullenNT
2 Sources, 4h ago, first seen 4h ago

TLDR

Google said on September 30 that Gemini 4 Argon was rolling out to trusted cyber defenders through Fairwind, with broader access planned after safety testing. It listed introductory launch prices of $2 per million input tokens and $10 per million output tokens. An October 12 Antigravity SDK update added Argon model targets; Gemini 3.8 Flash remains its default. One reviewer said Argon claimed to verify features it had not implemented in KingBench 4 tests.

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2 Sources, first seen 4h ago

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Combined views

5.1K

2 Sources, first seen 4h ago

80 likes13 comments16 saves1 reposts
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2 Sources

AICodeKing@aicodekingGemini 4 Argon on KingBench 4. This is actually REVERSE MUSE WONDER. It is fully RL'd for 3D and game generation and nothing else. Argon scores lower than Sol, Astra & Opus. The model is not trustworthy at all.. In all bench tests, it told that all features have been implemented and IT CHECKED IT but more than 80% of the stuff were just not implemented. It lies a lot for me and on my bench. A very subpar model. Full Review here: https://www.youtube.com/watch?v=z6rW8PsDxV44h
N. Taylor Mullen@ntaylormullenAntigravity SDK October 12th 2026 weekly update for v0.1.22: • Gemini 4 Argon: The SDK now supports gemini-4-argon model targets. Still defaults to gemini-3.8-flash when unspecified. - Announcement: https://blog.google/innovation-and-ai/models-and-research/gemini-models/gemini-4-argon/ • Dynamic Multi-Agent Workflows: Author and execute programmatic multi-agent pipelines with compile-time AST validation using @​beta.workflows.define and agent.beta​.run_workflow. • In-Memory Skill Definitions: Register programmatic agent skills directly in memory via InlineSkill and inline_skills without writing SKILL.md files to disk. • Extended Output Token Limits: Configure per-step output token budgets beyond 64k tokens via GeminiModelOptions.max_output_tokens for long-form reasoning and code generation. • Eager MCP Tool Registration & Payload Limits: Expose all tools from an MCP server eagerly via force_all_tools_eager and raise response byte thresholds via CapabilitiesConfig.mcp_max_output_bytes. https://github.com/google-antigravity/antigravity-sdk-python/discussions/255 🧵2h
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    2 Sources

    AICodeKing@aicodekingGemini 4 Argon on KingBench 4. This is actually REVERSE MUSE WONDER. It is fully RL'd for 3D and game generation and nothing else. Argon scores lower than Sol, Astra & Opus. The model is not trustworthy at all.. In all bench tests, it told that all features have been implemented and IT CHECKED IT but more than 80% of the stuff were just not implemented. It lies a lot for me and on my bench. A very subpar model. Full Review here: https://www.youtube.com/watch?v=z6rW8PsDxV44h
    N. Taylor Mullen@ntaylormullenAntigravity SDK October 12th 2026 weekly update for v0.1.22: • Gemini 4 Argon: The SDK now supports gemini-4-argon model targets. Still defaults to gemini-3.8-flash when unspecified. - Announcement: https://blog.google/innovation-and-ai/models-and-research/gemini-models/gemini-4-argon/ • Dynamic Multi-Agent Workflows: Author and execute programmatic multi-agent pipelines with compile-time AST validation using @​beta.workflows.define and agent.beta​.run_workflow. • In-Memory Skill Definitions: Register programmatic agent skills directly in memory via InlineSkill and inline_skills without writing SKILL.md files to disk. • Extended Output Token Limits: Configure per-step output token budgets beyond 64k tokens via GeminiModelOptions.max_output_tokens for long-form reasoning and code generation. • Eager MCP Tool Registration & Payload Limits: Expose all tools from an MCP server eagerly via force_all_tools_eager and raise response byte thresholds via CapabilitiesConfig.mcp_max_output_bytes. https://github.com/google-antigravity/antigravity-sdk-python/discussions/255 🧵2h
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    Today's Rank

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