Sakana AI's Fugu-Ultra v1.1 Beats GPT-5.5 and Claude on Coding Benchmarks
Sakana AI's Fugu-Ultra v1.1 upgrades its multi-model orchestration system with gains of up to 7.9 points across benchmarks, at the same price as v1.0
- Fugu-Ultra v1.1 is live: Sakana AI updated its multi-model orchestration system with gains of up to 7.9 benchmark points over v1.0, at no price change.
- Benchmark highlights: 82.1% on TerminalBench 2.1, 73.7% on SWE-Bench Pro, 95.5% on GPQA-Diamond, beating GPT-5.5, Opus 4.8, and Gemini 3.1 Pro.
- How it works: Fugu is a trained orchestrator that dynamically routes queries to a pool of frontier models (GPT-5.5, Claude Opus 4.8, Gemini 3.1 Pro) and coordinates their outputs.
- Pricing: $5/$30 per 1M input/output tokens for pay-as-you-go; subscriptions from $20–$200/month. Free second month if you subscribe before end of July 2026.
- Access: OpenAI-compatible API, also available on OpenRouter, Vercel, and opencode. Not available in EU/EEA.
- Caveat: All benchmarks are Sakana-reported and not yet independently verified; latency is higher than single-model calls for Fugu-Ultra.
Fugu-Ultra v1.1 is live. Sakana AI's orchestration-based model system gained up to 7.9 benchmark points over v1.0, with the sharpest improvements on ProgramBench and Terminal Bench 2.1. The price is unchanged, so existing users get a better model at no extra cost.
An orchestra, not a model
Fugu is a system that orchestrates a pool of existing frontier models behind a single OpenAI-compatible API. A learned conductor reads your query and decides which combination of GPT-5.5, Claude Opus 4.8, and Gemini 3.1 Pro should handle it, and how they should collaborate. Fugu is itself a language model trained to call various LLMs in an agent pool, including instances of itself recursively.
The underlying logic is that different frontier models have different strengths. GPT tends to lead in math, Gemini in scientific recall, Opus in software engineering and debugging. Fugu learns when to call each one and how to combine their outputs into something stronger than any single model could produce alone.
For v1.1, Sakana incorporated the latest frontier model releases into the agent pool. As the underlying models improve, Fugu routes to better workers, and the orchestration layer learns to exploit their new capabilities.
What the benchmarks show
Gains are concentrated in developer-relevant tasks:
- Terminal Bench 2.1: Fugu Ultra scores 82.1%, ahead of GPT-5.5 (78.2%), Claude Opus 4.8 (74.6%), and Gemini 3.1 Pro (70.3%). The benchmark tests agentic coding in a live terminal, including file manipulation, shell commands, and multi-step execution.
- SWE-Bench Pro: Fugu Ultra scores 73.7%, ahead of Claude Opus 4.8 (69.2%), GPT-5.5 (58.6%), and Gemini 3.1 Pro (54.2%).