[AINews] Gemini 4 Carbon tops leaderboards, launches for cyber defenders

What it claims

Google DeepMind's Gemini 4 Carbon, announced 27 October 2026 two weeks after Gemini 4 Argon, leads several independent leaderboards. It does not lead coding. Access is limited to cyber defenders in the Fairwind Program, and Google promises wider developer access "as soon as possible" with no date. The issue also reports independent numbers for GitHub Copilot Fusion, H-Net v2 and KV-cache work, plus user data on Claude Code quota burn.

Evidence

Specs and price. Carbon has a 1M-token context window and 1M max output, per Vals. It takes text, image, video and speech and returns text. Artificial Analysis lists $4/$20 per million input/output tokens, with a 50% launch discount that has no end date, and $0.20 per million cached input tokens. Phil Schmid quotes $2/$10 with an asterisk.

Artificial Analysis Intelligence Index v5. Carbon scores 59. Before Carbon, Opus 5.5 led at 58, ahead of GPT-6 Astra (57). Carbon leads 4 of the 9 index evals. It costs $7.76 per index task, against $10.04 for Opus 5.5 and $6.25 for GPT-6 Astra, and uses 123k output tokens per task, 29% fewer than Opus. Its hallucination rate rose from Argon's 4% to 11%, still second lowest measured. Opus 5.5 and Astra are both at 50%.

Coding. Carbon trails here. On the AA Coding Agent Index it scores 59 in Antigravity CLI, against 62 for Claude Code with Opus 5.5 [max]. On FrontierCode v1.1 it scores 51% against 56% for Opus. On FrontierSWE it scores 61.2%, behind GPT-6 Astra (65.5), Opus 5.5 (62.3) and Sonnet 5.5 (61.9). It sets a narrow best of 9.6% on SWE-sweep.

Knowledge work. Carbon scores 1609 Elo on AA-Briefcase, behind Kimi K3.1 Pro (1678). It is #1 on the Vals Finance Index and Legal Research Benchmark. On those tasks it produces 64% more output tokens than Argon, which raises cost.

Arena. Carbon is #1 in Text Arena (1528), #2 in Agent Arena at a $1.80 median cost per task, and #4 in Code Arena WebDev (1768).

Google's safety claims. Successful cheating on Terminal-Bench 4.0 is 0.0% and cheating attempts are 0.4%. Unsupported claims are down about 2x from Argon.

Other items with numbers.

• GitHub Copilot Fusion routes between Anthropic and OpenAI models at runtime. It scores 2 points below Opus 5.5 in Claude Code on the AA Coding Agent Index, at $5.59 per task against $11.42. It uses 7.2M tokens per task and leads Terminal-Bench 4.0 with 71.
• Cartesia's H-Net v2 learns tokenization from raw bytes. It reports 3 to 5x efficiency gains in controlled scaling and matches an open model trained on 11T tokens with about 10x less data and compute.
• AKV (Tsinghua and CUHK) cuts agent serving cost 27.7% and improves P95 latency 1.51x.
• SGLang HiCache offload to CPU DRAM adds 20 to 40% cacheable tokens at 12 to 16 concurrent agent sessions on B200, per SemiAnalysis.
• Default system prompts across 30 open coding harnesses range from 235 tokens (goose) to 11,974 (Gemini CLI), before tool definitions.
• Modular opened the full MAX source, including compiler, runtime and backends, with no royalties.
• NVIDIA Nemotron 3.5 Transcribe is a 30B MoE with about 4B active parameters and open weights. It scores 2.8% AA-WER and costs $2 per 1,000 minutes on DeepInfra. vLLM supports it in BF16, FP8 and NVFP4.
• Liquid AI's LFM3-1.7B has a 256K context, runs in about 1 GB at 4-bit, and works in llama.cpp.
• Ling-3.1-flash-1019 is a 560B total / 25B active MoE with a 1M context and a base checkpoint. Its SGLang README example must be changed to inclusionAI/Ling-3.1-flash-1019.

Limits

Carbon's coding-agent results were measured only in Antigravity CLI. Other harnesses are untested, as @Yuchenj_UW notes. The cyber benchmark scores come from Google and cannot be checked independently while access is restricted. Some users, including @scaling01, raise hallucination risk for cyber use given the higher 11% rate.

AA Index v5 runs 60% on private tests, which limits reproducibility. r/LocalLlama users dispute its cost-per-task figures and the drop of open-weight models: Kimi K3.1 Pro fell from 55 to 46.

On Claude Code, one Pro user's ccusage logs show 1.306B tokens on 27 October against a 161M daily average. Anthropic support reportedly said retries after service errors count toward usage limits and will not be credited.